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About EITT 2013

The Second International Conference of Educational Innovation through Technology (EITT 2013) provides a forum for researchers who study technology and education to publish research findings and exchange experiences in related topics. The conference is organized by Society of International Chinese in Educational Technology (SICET). It is hosted jointly by Tsinghua University and Virginia Tech. It collaborates with the annual Educational Technology Leadership Conference (ETLC) which is sponsored by Virginia Tech's Center for Instructional Technology Solutions in Industry and Education. EITT and ETLC will share opening and closing ceremonies and keynotes presentations while the concurrent sessions will be separated.

Founded in 2003, the Society of International Chinese in Educational Technology (SICET) is a nonpolitical, non-profit academic organization. The organization’s goal is to aggregate international Chinese scholars and experts in the field of educational technology to encourage academic cooperation and support among members. The mission of SICET is to establish and strengthen academic international connections, exchanges, research, and studies in educational technology for teaching and learning, as well as to promote the application of educational technology in Chinese education. For detailed information, visit SICET official Website at: http://sicet.org.

SICET sponsors two refereed international academic journals, The International Journal of Technology in Teaching and Learning (IJTTL) and The Journal of Educational Technology Development and Exchange (JETDE). Selected articles presented at EITT will be recommended to these journals. SICET also organizes Summer Fellowship trip to China every summer to provide a platform for the scholars in US and China to exchange their research results, share their teaching experiences, and establish possible collaborations in the area of educational technology.

During EITT 2012 conference held at Tsinghua University, Beijing, China, August 10-12, 2012, the Asia-Pacific Chapter of Society of International Chinese in Educational Technology (SICET- AP) was found. Asia-Pacific Chapter has over 30 affiliate universities and more than 300 members. Currently SICET members mainly locate in North America and Asia. Some members are in Australia and Europe. SICET is becoming a true International association.

EITT 2013 Organization

Organized by Society of International Chinese in Educational Technology (SICET)

Hosted by Educational Technology Institute (THETI), Tsinghua University Center for Instructional Technology Solutions in Industry and Education (CITSIE), Virginia Tech

Sponsored by Association for Educational Communications and Technology (AECT) China Association for Educational Technology (CAET)

Conference Chairs Jiangang Cheng, Professor, Tsinghua University, Beijing John Burton, Professor, Virginia Tech, Blacksburg Harrison Hao Yang, Professor, State University of New York, Oswego

Program Committee Chairs Xibin Han, Associate Professor, Tsinghua University, Beijing Shuyan Wang, Associate Professor, University of Southern Mississippi, Hattiesburg Barbara Lockee, Professor, Virginia Tech, Blacksburg Nian-Shing Chen, Professor, Sun Yat-Sen University, Kaohsiung

Program Committee Members (Alphabetical order) Li Chen, Professor, Beijing Normal University, Beijing Mingxuan Chen, Professor, Jiangnan University, Wuxi Pearl Chen, Associate Professor, California State University, Los Angeles Hsiu-Jen Cheng, National Kaohsiung Normal University, Kaohsiung Guoqiang Cui, Instructional Designer, Montclair State University, New Jersey Gangshan Fu, Professor, Shaanxi Normal University, Xi’an Liansheng Ge, Professor, Shandong University, Jinan Ray Yueh-Min Huang, Professor, National Cheng Kung University, Tainan Jui-Long Hung, Associate Professor, Boise State University, Boise Gwo-Jen Hwang, Professor, National Taiwan University of Science and Technology, Taipei Wu-Yuin Hwang, Associate Professor, National Central University, Jhongli Baocong Jiao, Professor, Capital Normal University, Beijing Yu-Ju Lan, Associate Professor, National Taiwan Normal University, Taipei Yi Li, Professor, Nanjing Normal University, Nanjing Geping Liu, Professor, Southwest University, Chongqing Leping Liu, Professor, University of Nevada, Nevada Yongqian Liu, Professor, China Association for Educational Technology, Beijing Chin-Hwa Kuo, Professor, Tamkang University, Tamsui Junjie Shang, Associate Professor, Peking University, Beijing Jihua Song, Professor, Beijing Normal University, Beijing Shian-Shyong Tseng, Professor, Asia University, Tamsui Chih-Hsiung Tu, Professor, Northern Arizona University, Flagstaff Hong Wang, Instructional Designer, Kansas State University, Kansas Jide Wang, Professor, Henan University, Kaifeng Lu Wang, Professor, Capital Normal University, Beijing Yuping Wang, Associate Professor, Griffith Univiversity, Brisbane Zhijun Wang, Professor, Tianjin Normal University, Tianjin Youru Xie, Professor, South China Normal University, Guangzhou Stephen Yang, Professor, National Central University, Jhongli Yi Yang, Associate Professor, Franklin University, Ohio Kuang-Chao Yu, Professor, National Taiwan Normal University, Taipei Shengquan Yu, Professor, Beijing Normal University, Beijing Hong Zhan, Associate Professor, Embry-Riddle Aeronautical University, Arizona Jianping Zhang, Professor, Zhejiang University, Hangzhou Ke Zhang, Associate Professor, Wayne State University, Detroit Shaogang Zhang, Professor, China Open University, Beijing Shuyu Zhang, Professor, Nanjing Normal University, Nanjing Chengling Zhao, Professor, Central China Normal University, Wuhan

Preface

The 2nd International Conference of Educational Innovation through Technology (EITT2013) is held in Nov. 4-6, 2013 at Williamsburg, Virginia USA. EITT provides a forum for researchers who study technology and education to publish research findings and exchange experiences in related topics. The conference intends to be organized annually by Society of International Chinese in Educational Technology (SICET) and hosted jointly by Tsinghua University and Virginia Tech in this year.

The final EITT2013 program consists of one keynote speech with two speakers, 35 concurrent sessions, 13 roundtable sessions, 12 poster sessions, and two panel sessions with a total of 62 presentations. More than 60 participants from the United State, Canada, Taiwan, Hong Kong and China Mainland attended the conference.

The conference proceedings collect 52 articles accepted out of 113 submissions in a standard peer-review process. The topics of the selected papers and the concurrent sessions include Emerging Technologies in Learning and Teaching, Innovative Approaches to Learning and Learning Environments, and Information Society and Culture

It is our great pleasure and honor to have received kind supports from many scholars in various ways that helped make this conference a reality. We are greatly thankful to all authors and speakers for their excellent contributions, to all session facilitators for their efforts and enthusiasm, and to all the program committee members and referees for their time and expertise in the paper review. Special thanks go to the Educational Technology Institute of Tsinghua University (THETI) and Virginia Tech's Center for Instructional Technology Solutions in Industry and Education (CITSIE) for their host to the conference in this year.

We heartily wish all EITT2013 participants enjoy attending the conference, meeting friends and colleagues, and having pleasant stays at Williamsburg.

Conference Chairs: Jiangang Cheng, Professor, Tsinghua University John Burton, Professor, Virginia Tech Harrison Hao Yang, Professor, State University of New York at Oswego

TABLE OF CONTENTS

Section One Emerging Technologies in Learning and Teaching

Some Eye Tracking Phenomena of Integrated Circuit Layout Debugging Hong-Fa Ho ...... 1-6 Motivating Chinese College Students’ Learning with Educational Games Shuzhuang Hao and Haiyan Wang ...... 7-14 Using Data Mining Technologies to Find Learning Objects Usability Rules for Web-based Learning Systems Qingtang liu and Ke Zhu...... 15-24 Design and Implement of Mobile Learning Platform Based on Android Wei Lv and Yichun Zhang ...... 25-32 Bookboard: Encouraging Early Childhood Students’ Love of Reading Hengtao Tang...... 33-48 Study on the Promotion of Electronic Textbooks in Universities Jide Wang and Xuexue Song ...... 39-42 A Study on IWBs’ Instructional Application Levels in China Mainland Lu Wang, Zhiguo Si, Xiaoliang Zhao, and Ke Xu ...... 43-58 Learning Analytics: Mining the Value of Education Data in the Era of Big Data Shunping Wei ...... 59-68 A Solution to Guarantee Undergraduate Thesis Quality by Information Technology Juan Yang, Xibin Han, Qian Zhou, and Jing Ma...... 69-76 The Contribution of Multimedia Teaching to Physical Education Minjie Zhang ...... 77-78 Design and Implementation of Reusable Survey and Test System Based on SSI Framework Qian Cao, Shuyi Zhou, and Shidong Xu ...... 79-84 Design and Implementation of Report Repository System: an Example of Educational Information Visualization Tools Wenjun Deng, Yingqun Liu, and Xibin Han ...... 85-88 The Cluster Analysis of Learners’ Behavior Characteristics in the Network Environment Gangshan Fu ...... 89-98 Adopting E-Booksin Curricular Sirui Wang, and Shuyan Wang ...... 99-104 Evaluating K-12 Online Program - An Data Mining Approach Jui-Long Hung, Yu-Chang Hsu, and Kerry Rice ...... 105-114 A Mobile Augmented Reality System Enhanced Inquiry-based Strategies to Improving Students’ Learning Achievement in Natural Science Learning Tosti H.C. Chiang, Stephen J.H. Yang, Vivi C.H. Liu, and Cynthia Y.C. Lin ...... 115-120 Design and Development of Educational Game Based on RETAIN Model Zhijun Wang, Lingling Yang, and Hong Li ...... 121-128

Section Two Innovative Approaches to Learning and Learning Environments

Model Design and Effects Research of Tutor-directed Online Teaching Jianjun Hou, Kuiyuan Zhang, and Yanli Qi ...... 129-140 Foster Reflective Thinking and Active Learning through Electronic Portfolios at Public Speaking Course to English as Foreign Language Students Ju Huang, Min Huang, and Chaoxian Qin ...... 141-146 The Effect of Online Games on Adolescents’ Physical, Mental Health, and Academic Performance Jian-Sheng Li and Huan Xu ...... 147-150 Physiological Evaluation of the Players’ Emotions in Different Educational Games Jian-Sheng Li, Yun-Xia Han, and Shan Liu ...... 151-158 Empirical Research on the Interaction between Learners’ Interactive Centrality and Quality in the Forum on MOOCs Qiujie Li and Qinhua Zheng ...... 159-168 Personalized Design of Online Learning Environments to Facilitate Self-Directed Learning Tongtong Li, Fati Wu, and Shihua Cao ...... 169-174 Study of Second Life Based on Learning Activities in Inquiry-Based Learning System Geping Liu, Yingbo Chen, and Yiliu Zhou ...... 175-182 On Using Corpus-integrated Peer Review for the EFL College Learners in China Junming Ma and Caiqiang Li ...... 183-192 The Exploration of Practice Model of Network Courses Effective Teaching Yong Nie, Tingting Jiang, and Sha Yue ...... 193-202 Deep Learning through Reusable Learning Objects in a MBA Program Rosalyn Rufer and Ruifang Hope Adams ...... 203-212 Students’ Experiences of Initial Designers in a Project-based Learning Case Hengtao Tang, Qiyuan Li, Yu Yan, and Yaozu Dong ...... 213-218 Using Mobile Technology for Active Learning in the Big Classroom Chakorn Techatassanasoontorn, Tutaleni Asino, Jessica Briskin, Sarah J. Stager, and Yu Yan ...... 219-222 Flipped Classroom: An Innovative Teaching Model in the Digital Age Shuyan Wang and Huiruo Chen ...... 223-228 Designing Immersive Virtual Language Learning Environments Yi Fei Wang , Stephen Petrina , Franc Feng, and Jing Zhao ...... 229-238 Using Teaching for Understanding Framework in High School Psychological Health Classes Yu Yan, Qiyuan Li, Hengtao Tang, and Yaozu Dong ...... 239-243 The Application Research of Intelligent Push Technology in Smart Learning Environment Chengling Zhao and Zhifang Huang ...... 245-252 The Investigation and Analysis about the Status Quo of the Resources in Visualization Teaching for Deaf Students Huichen Zhao and Man Zheng ...... 253-262

Section Three Information Society and Culture

The Relationship between Adult Students’ Characteristics and their Learning Styles Guoqiang Cui ...... 263-270 Assessing the Primary and Secondary School PE Teachers’ Educational Technology Abilities Jin Huo ...... 271-274 Research on Optimization of Online Education Service based on Analysis of Visiting Data to LMS Caiqiang Li and Junming Ma ...... 275-278 The Joint Live Global Classroom by the American Alliance for International Education and the University of Science & Technology Beijing Xinxin Li, Li Liu, and Zhiyi Zhao ...... 279-282 Analyzing the Distribution of E-learning Resources in Chinese Educational Websites Xiangzeng Meng, Weina Wang, and Lin Shi ...... 283-294 Computer Resources and Science Attitudes: The Effects on Eighth-Grade Science Achievement Yun Mo, Xibin Han, and Yingqun Liu ...... 295-302 The Enlightenment of Teacher Professional Development Based on Professional Leading on the In-Service Training of Rural Teachers Ximei Qu and Rong Miao ...... 303-308 The Construction of Quality Assurance System for Distance Education Based on Ecological View Xinyi Shen, Li Chen, and Ying Li ...... 309-316 Improving Digital Literacy through Self-study to Promote Continuing Professional Development Fang Su and Yajie Chen ...... 317-320 TrackVis: Track and Visualize Learners’ Activities in an Online Learning Environment Congwu Tao, Yu Yan, Jianqiang Zhang, Juan Yang, and Guoqiang Cui ...... 321-330 Information Technology Used in Environmental Education in China and Its Cases Study Wei Xu and Jianping Zhang ...... 331-342 Empirical Research of Enterprise E-learning in China Feng Wu and Junjie Shang ...... 343-350 Comparative Studies on the Educational Technology Organizations in Sino-US Higher Education Yanhui Wu and Weize Ding ...... 351-368 Empirical Research on e-Learning Environments for Higher-Order Thinking — Based on Writing Instruction for Primary Students of Grade 5 Yueguang Xie and Jie Jian ...... 369-378 Research on the Teaching for Understanding in Information Technology Curriculum Yang Xu and Ming-xuan Chen ...... 379-384 Access and use of ICT: An Exploratory Study of Canadian and Chinese Students Zuochen Zhang...... 385-392 Development of Visual Philosophy under Impact of Philosophy of Technology Li Zhao and Shuyu Zhang ...... 393-402 An Analysis of Teaching Behavior in the Open Course Jian-Sheng Li and Wen-Jing Xia ...... 403-410

Ho, H. (2013). Some eye tracking phenomena of integrated circuit layout debugging. Proceedings of International Conference of Educational Innovation through Technology, 1-6.

Some Eye Tracking Phenomena of Integrated Circuit Layout Debugging

Hong-Fa Ho National Taiwan Normal University Email: [email protected]

Abstract: Using eye trackers to explore reading processes is one of the ways to observe reading. Mental model may be better observed from the phenomena of the reading process by the help of eye trackers. This study aims to explore the phenomena of students’ reading processes in CMOS Integrated Circuit (IC) layouts. In this pilot study, eye movement data was used in analyzing the reading process and phenomena of five participants (N=5) who tried to find a bug in one IC layout. Data analysis of eye movements was based on nine types of Region of Interest (ROI) for IC layout. The experimental findings include: 1) the Well was not only fixated the highest number of times but also was fixated for the longest period of time; 2) PMOS was fixated earlier than NMOS; and 3) the Via had the longest duration of first fixation. The findings suggest some phenomena in the reading process of IC layout. These phenomena may provide fundamental reference in educational technology development for IC layout instructors, textbook writers, and researchers.

Keywords: reading process, eye tracking, CMOS IC layout, logic circuit

1. Introduction The enormous global market of the Digital Integrated Circuit (IC) in which CMOS IC is one of the mainstream technologies has a high demand for talents. The textbooks on IC design today only introduce the knowledge and rules of layouts. None introduces how to read layouts scientifically. For example, Rabaey, Chandrakasan and Nikolic’s (2003) textbook introduced layout’s design rules, layer representation, intralayer constraints, and interlayer constrains. However, when introducing layout verifications, it only introduced a piece of software named computer-aided Design-Rule Checking. In Wolf’s (2009) textbook Modern VLSI Design, it introduced only four different layouts of different gates. Marked arrows on the layout pictures indicated definitions of each area, and then the components of the layouts were introduced. Probably because writers of engineering textbooks believe students should know how to read layouts if they can design layouts, the writers are not familiar with layout reading processes, and the lack of literature in the reading processes of IC layouts, there are no textbooks that teach students how to read IC layouts scientifically today.

There are no literatures in engineering education regarding the method to educate students in reading layouts. Lin et al. (2010) put forward the content of layout education in their analog CMOS IC design courses. The course syllabus only showed the name of the layout and its tool—layout editor; no lesson on teaching students to read layouts could be seen. How do IC design students read layouts? Textbook writers obviously did not know, and instructors did not have any related studies to refer to, either. Finding bugs become hard if the reading process of the layout is unknown. This study aims to find solid evidence on IC layouts’ reading process and provide textbook writers with information for refining pedagogics. The objective of this study is to explore the reading process of debugging CMOS IC layout, which might help unravel reasons for students that encounter difficulties in understanding layouts when debugging and provide a better strategy in the learning and education of electronic engineering.

There are many procedures in the CMOS IC manufacturing process, IC designers use multi-layer diagrams to represent the abstracted circuit design. There are many geometric figures in each layer, and these figures must abide by many rules to insure the produced IC conforms to the design. Figure 1(a) shows a schematic logic circuit diagram. Its CMOS IC layout is shown in figure 1(b). In figure 1(b), Wire, Via, Connector, Well, NMOS transistor, PMOS transistor, Power Supply (Vdd in short), and Ground (Vss in short) are all common key elements in the CMOS IC layout.

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 1 Proceedings of International Conference of Educational Innovation through Technology

Engineers often need to examine whether the layouts designed by others conform to its electric circuit, or find bugs in the layouts. There are many kinds of bugs in the actual IC layouts, for example, there may be bugs in Wire, Via, Connector, Well, Power Supply and so on.

Figure 1. (a) Schematic circuit diagram of this study (b) Its CMOS IC layout with a bug

What is the IC layout debugging process? IC designers examine the IC layout for bugs after they draw its diagram (Figure 1). The different colored rectangles represent different materials/structures, for example, red rectangles represent metal, and orange rectangles represent via holes (Figure 1 (b)). When reading IC layouts, the reader examines the relationships among colored rectangles to check whether their meanings match the schematic circuit diagram, such as the one in Figure 1 (b). The debugging process is one of the reading processes of the IC layout.

Reading is considered a complicated cognitive comprehension process in information processing. First, the participants receive the text information that is coded into working memory. Then, the coded information is combined with the information and knowledge of long-term memory. According to the information processing theory, Gagne, Yekovich and Yekovich (1993) divided the reading process into four stages: (1) decoding, (2) literal comprehension, (3) inferential comprehension, and (4) comprehension monitoring. They added that all stages could be processed in parallel to each other. Gagne, Yekovich and Yekovich’s reading process is unsuitable for application in reading layouts since it focused on the reading process for text. The reading contents for IC layouts are colored rectangles of CMOS transistors, input signals, output signals, electric resistance, electric capacity, wiring, and so on.

Eye trackers are used in numerous fields such as neurosciences, psychology, industrial engineering, ergonomics, marketing/advertisement and computer science (Duchowski, 2002). In psychology, eye trackers are mostly used in reading (Radach, Inhoff, & Heller, 2002; Rayner, 1998), scene perception (Rayner, Smith, Malcolm, & Henderson, 2009), problem solving (Knoblich, Ohlsson, & Raney, 2001), auditory language processing (Sussman, Campana, Tanenhaus, & Carlson, 2002), attention (Kowler, Anderson, Dosher, & Blaser, 1995), and other information processing areas. The studies based on reading have contributed immensely to the society in reading and learning. Other studies on reading process includes word research, article reading model and process, mathematics, science, music score, program debugging and program development. The above literatures showed the eye tracker as a reliable experimental tool, and eye movement data based on the concept of Region of Interests (ROI) contributes to the society’s understanding of the reading process.

2 EITT 2013, Williamsburg, VA, USA, November, 2013 Some Eye Tracking Phenomena of Integrated Circuit Layout Debugging

Nine types of IC layout ROIs were defined for layout debugging:Circuit ROI, Wire ROI, Via ROI (including Connector), Well ROI, NMOS ROI, PMOS ROI, Vdd ROI, Vss ROI, and Rest ROI. The Rest ROI was any area excluding the other eight ROIs.

1.1. Research Questions and Hypotheses Some similarities do exist between reading CMOS IC layouts and reading text, albeit their differences. Regressive saccades and longer duration of fixations (Rayner, 1998, 2009), for example, imply that readers who are not familiar with the IC layout have difficulties in reading it. The following research questions try to demonstrate this point.

Q1: Which ROI is fixated the most?

Q2: Which ROI is fixated for the longest period of time?

Q3: Between PMOS ROI and NMOS ROI, which will be fixated first?

Q4: Which ROI has the longest duration of first fixation?

While every element in the schematic circuit diagram and every rectangle in the IC layout are crucial, IC designers do not fixate at every element and rectangle because it is time-consuming. The Well ROI consists of many elements, including transistors, wires, connectors, and vias. Since these elements have smaller areas and are important, the probability for them to be fixated is higher. In general, PMOS will be fixated first, and then the NMOS. This order may be due to the position of the power supply (Vdd), which is at the top and electric currents flows from the top to the bottom (Vss). This study is designed to examine the following hypotheses based on the above research questions and concepts.

H1: The Well ROI is fixated the most.

H2: The Well ROI is fixated for the longest period of time.

H3: Between PMOS ROI and NMOS ROI, PMOS ROI is fixated first.

H4: The Well ROI has the longest duration of first fixation.

2. Method 2.1. Participants One second year postgraduate student, one senior undergraduate student and three junior undergraduate students (N=5, four males and one female) of the Department of Applied Electronics Technology, National Taiwan Normal University were paid to participate in the experiment. They were asked to participate in the experiment because they had previously attended the IC layout design course. Their ages ranged from 21 to 28 years old, 23.00 (SD=2.83) years old on average. They had the knowledge of operating computers, and they had normal or corrected to normal vision. All the students who participated in this experiment signed written agreements.

2.2. Material One screen-based question was designed after taking students’ knowledge of IC layouts into consideration. The question comprised of a schematic circuit diagram and a corresponding layout in which a bug was embedded. Figure 1 shows the question. The participants should click on the bug in the layout with a computer mouse. A computer program was design to present the material and record the participants’ eye movement.

2.3. Design Participants must inspect the circuit and layout carefully to find the bug. The reading processes of eye movements among ROIs were recording and analyzed.

The visual information was more stable when the participants fixated at particular areas during the reading process. The participants also spent a longer time processing information when reading diagrams. Their eye movements reflect which symbols or rectangles were fixated or re-fixated. Logic forward fixations indicated

EITT 2013, Williamsburg, VA, USA, November, 2013 3 Proceedings of International Conference of Educational Innovation through Technology participants did not have difficulties in reading the layout, whereas logic regressive fixations indicated they did. Participants with difficulties in reading the layout would use the strategy of rereading symbols and rectangles, and then combining the information to help them understand it.

This experiment used a 9-factorial design. In order to observe the reading phenomena of IC layouts with eye movement data, the areas in which the eyes fixated were divided into different areas. The independent variables were types of ROIs including Circuit ROI, Wire ROI, Via ROI, Well ROI, NMOS ROI, PMOS ROI, Vdd ROI, Vss ROI, and Rest ROI. Dependent variables were the number of fixations (NOF), the total contact time (TCT), the latency of first fixationLFF ( ), and the duration of first fixationDFF ( ) of different types of ROIs. Reading process may be observed by these dependent variables.

2.4. Apparatus The EyeNTNU-180 eye-tracking system with 180Hz sampling rate was used in this experiment. The system consisted of an eyeglass frame, a mini camera, two infrared LEDs, and a notebook computer (CPU P4-2.2 GHz) which was also used to present the question and control the experiment. The computer screen was 15.6-inch. The reported angle error of accuracy of EyeNTNU-180 was 0.33°. A chin frame was employed to prevent the participants’ head movement and increase the measurement accuracy. The participant’s eyes and the screen were 60 centimeters apart. Software tools, ROI Splitter and Fixation Calculator, were employed for analyzing the eye movement data.

2.5. Procedure A CMOS logic circuit and its IC layout were given to the participants who were required to find a bug as soon as possible. Before the experiment, the author illustrated the procedure to the participants, adjusted the mini camera, and conducted a nine-point calibration. The participants were given samples of a circuit diagram and its IC layout so that they could familiarize the question type and procedure before the experiment. Eye movement data were collected during the experiment. Meanwhile, the points clicked and the number of clicks was recorded too. The participant took about 5 minutes to complete the question. In this study, the NOF of ROI increased one when the duration of fixation was longer than 80ms.

3. Data Collection, Analysis, and Results All participants found the bug correctly, and the eye tracker automatically collected their eye movement data. The ROI Splitter was employed to define the ROIs in the question. Since many ROIs were of the same type, the author combined them into an integrated ROI. The Fixation Calculator was used to calculate mean values of the number of fixations NOF( ), the total contact time (TCT), the latency of first fixationLFF ( ), and the duration of first fixationDFF ( ) of each ROI automatically. The results were shown in Table 1.

Regarding the NOF of ROI, the higher the NOF indicated more information should be obtained on that particular ROI to facilitate reasoning. Since Rest ROI, such as the button area in the screen, was not concerned in this study, it would not be considered for comparison. However, it was included in the tables in the interest of a complete database.

According to Table 1, the order of NOF from large to small was Circuit ROI > Well ROI > Wire ROI > PMOS ROI > Vdd ROI > Via ROI > NMOS ROI > Vss ROI. The Circuit ROI was considered the basis for correctness in debugging; therefore, it was fixated the most number of times. The number of fixation of PMOS ROI and Vdd ROI were higher than NMOS ROI and Vss ROI in the CMOS IC layout. This phenomenon indicated that participants’ habit of scrutinizing PMOS and Vdd first benefited the inspection of NMOS and Vss. Due to the higher number and smaller area of rectangles in Well ROI, which included PMOS ROI, NMOS ROI, and Via ROI, the mean number of fixation when searching for the bug were higher. Considering that all wires must be inspected, the Wire ROI had the highest number of mean fixations. Thus, H1 was supported.

4 EITT 2013, Williamsburg, VA, USA, November, 2013 Some Eye Tracking Phenomena of Integrated Circuit Layout Debugging

Table 1. Mean of NOF, TCT, LFF, and DFF of nine types of ROIs Circuit PMOS NMOS Via Wire Vdd Vss Well Rest NOF(times) 49.60 11.00 8.00 8.40 24.80 10.60 3.20 40.40 52.00 TCT(ms) 7601.40 1975.80 1440.00 1446.80 3907.40 1873.00 579.00 6963.20 8058.00 LFF(ms) 2061.20 2651.80 17739.80 76506.20 42243.60 13309.20 9495.40 8816.60 4571.20 DFF(ms) 185.60 234.00 210.00 738.00 442.80 174.00 187.40 328.00 142.60

The TCT of ROI stands for the total period of time ROI was fixated. The longer total average fixation time was, the more information of the ROI was needed in debugging to facilitate reasoning. According to Table 1, the order of TCT from high to low was Circuit ROI > Well ROI > Wire ROI > PMOS ROI > Vdd ROI > Via ROI > NMOS ROI > Vss ROI. The order here was exactly the same as the previous NOF order, thus it has the same meaning as NOF. H2 was supported.

The LFF of ROI stands for the latency of its first fixation. The smaller the LFF, the earlier it was fixated; the larger the LFF, the later it was fixated. According to Table 1, the order of LFF from low to high was Circuit ROI < PMOS ROI < Well ROI < Vss ROI < Vdd ROI < NMOS ROI < Wire ROI < Via ROI. It was also the participants’ sequence for obtaining ROI information in debugging for the first time. This indicated the order relation between the reading process and the first fixation. H3 was supported. PMOS ROIs were fixated mostly before NMOS ROIs because they always complemented each other in CMOS.

The DFF of ROI stands for the duration of the first ROI fixation. The smaller the DFF, the shorter time it takes to be fixated for the first time; the larger theDFF , the longer time it takes to be fixated for the first time. According to Table 1, the order of DFF from large to small was Via ROI > Wire ROI > Well ROI > PMOS ROI > NMOS ROI > Vss ROI > Circuit ROI > Vdd ROI. The order indicated the time participants spent on obtaining ROI information in debugging for the first time.

H4 was not supported. Two plausible reasons were: 1) the rectangle of Via completely overlaped with other rectangles, making reading more difficult; 2) the role ofVia determined the correctness of circuit connections, hence, it should be scrutinized carefully on the first fixaton; thus, the Via ROI of DFF was the largest.

4. Findings and Implications How do integrated circuit (IC) designers read IC layouts? Is the reading process of IC layouts different from the reading process of text? The basic skill for IC design engineers and students is to find bugs in CMOS IC layouts. By using the EyeNTNU-180 eye tracker and its software tools on five participants (N=5) who were required to find a bug in CMOS layout, the eye movement data and nature of the reading process was analyzed. To analyze eye movement data, nine types of ROI for CMOS IC layouts were designed. The eye movement statistics was analyzed based on ROI definitions.

The phenomena presented in this paper may provide a basic reference in educational technology development for IC layout instructors, textbook writers, and researchers. Educational software can display specific areas consecutively according to the LFF order, which helps learners read IC layouts in a better order. During the consecutive display, the order of DFF and the length of time determine the first display period; the order ofNOF and TCT and the length of time determine the following display periods.

To summarize, experimental results showed that: 1) the Well ROI was fixated the most number of times and was fixated for the longest period of time; 2)PMOS ROI was fixated earlier thanNMOS ROI; 3) the Via ROI

EITT 2013, Williamsburg, VA, USA, November, 2013 5 Proceedings of International Conference of Educational Innovation through Technology had the longest duration of first fixation. The findings revealed some phenomena of the reading process of IC layout debugging. These phenomena may offer some guidance for writers of IC design textbooks and instructors in refining pedagogies.

5. Limitations and Future Work In this study, the motive for reading the IC layout is to find bugs, yet, it is important to note that different motivations may lead to different visual behaviors in reading IC layouts and other information. The results of the pilot study were based on a small number of participants and one CMOS IC layout question. Larger samples and increasingly complicated CMOS IC layouts are needed for formal experiments.

References Duchowski, A. T. (2002). A breadth-first survey of eye-tracking applications. Behavior Research Methods,Instr uments,&Computers,34(4),455-470. Gagné, E. D., Yekovich, C. W., & Yekovich, K. R. (1993). The cognitive psychology of school learning (2nd ed.). New York: Harper Collins College Publishers. Knoblich, G., Ohlsson, S., & Raney, G. E. (2001). An eye movement study of insight problem solving. Memory & Cognition, 29(7), 1000-1009. Kowler, E., Anderson, E., Dosher, B., & Blaser, E. (1995). The role of attention in the programming of saccades. Vision research, 35(13), 1897-1916. Lin, W. L., Cheng, W. C., Wu, C. H., Wu, H. M., Wu, C. Y., Ho, K. H., & Chan, C. A. (2010). A novel analog integrated circuit design course covering design, layout, and resulting chip measurement. IEEE Transactions on Education, 53(2), 282-287. Rabaey, J. M., Chandrakasan, A., & Nikolic, B. (2003). Digital integrated circuits–a design perspective (2nd ed.): Prentice-Hall. Radach, R., Inhoff, A., & Heller, D. (2002). The role of attention and spatial selection in fluent reading. In E. Witruk, A. D. Friederici & T. Lachmann (Eds.), Basic Functions of Language, Reading and Reading Disability (pp. 137-153). Dordrecht, the Netherlands: Kluwer Academic. Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological bulletin, 124(3), 372-422. Rayner, K. (2009). Eye movements and attention in reading, scene perception, and visual search. The Quarterly Journal of Experimental Psychology, 62(8), 1457-1506. Rayner, K., Smith, T. J., Malcolm, G. L., & Henderson, J. M. (2009). Eye movements and visual encoding during scene perception. Psychological Science, 20(1), 6-10. Sussman, R. S., Campana, E., Tanenhaus, M. K., & Carlson, G. M. (2002). Verb-based access to instrument roles: Evidence from eye movements. Paper presented at the 8th annual Architectures and Mechanisms of Language Processing Conference, Tenerife, Canary Islands, Spain. Wolf, W. (2009). Modern VLSI design: IP-based design (4th ed.): Prentice Hall PTR.

Acknowledgement This work was supported in part by the “Aim for the Top University Project” from National Taiwan Normal University and the Ministry of Education, Taiwan, R.O.C. This work was also partially supported by National Science Council of Republic of China (NSC 101-2511-S- 003-046).

6 EITT 2013, Williamsburg, VA, USA, November, 2013 Hao, S. Z. & Wang, H. (2013). Motivating Chinese college students’ learning with educational games. Proceedings of International Conference of Educational Innovation through Technology, 7-14.

Motivating Chinese College Students’ Learning with Educational Games

Shuzhuang Hao, Haiyan Wang Yantai University Email: [email protected], [email protected]

Abstract: Investigating the motivations of educational games may provide insights into understanding the highly condensed features of individual needs for English online learning. Examining the educational games may broaden research into alternative online instruction strategies. This study is to explore possible relationships between educational games and English online leaning motivation of Chinese college students. Understanding the effects of gender, age and learners’ experience may have potential impacts on how online instruction can be more appropriately prepared, delivered, organized, and managed.

Keyword: Motivation, Educational games, online learning

1. Introduction The intention of this study is to explore possible relationships between educational games and English online leaning motivation of Chinese college students。

Investigating the motivations of educational games may provide insights into understanding the highly condensed features of individual needs for English online learning. Examining the educational games may broaden research into alternative online instruction strategies. Understanding the effects of gender, age and learners’ experience may have potential impacts on how online instruction can be more appropriately prepared, delivered, organized, and managed. (Prensky, 2001) This study can be helpful for both online course designers and instructors to make rational decisions regarding how to facilitate web-based instruction and how to motivate online learners.

Since early 20th century, studies on educational games gradually brought up and established itself as an empirical research area both in China and western world. (Ebner & Holzinger, 2007) Many researchers in the world get indulged in the development and implementation of educational games (Crawford. 2008). Among so many educational games, a more significant one is the “games- to-tech” project. The purpose of the project is to identify the methods to enhance English learning through the application of educational games. In China, educational games gradually gained its attention both in actual practice and academic studies from the last years of 20th century.

2. Research Design 2.1. Participants The participants of this research are college students of year 2009 of our University, who are majored mainly in English and Law. The data provided in this paper is draw-out according to the experimental data of 130 pieces of the total population.

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2.2. Data Collection Procedures Data was collected according to the following procedures: 2.2.1 Survey design.  Completed and signed questionnaire in text form.  Consent Text 2.2.2. Survey distribution. E-mail messages that contained a simplified content of the questionnaire were distributed to targeted sampled population.

2.2.3. Survey timing. Allowed one week for responding.

2.2.4. Response rate. Since it is a piloting study and the questionnaires were distributed to peers in the same grade either familiar or not familiar, so, the questionnaires distributed were all retrieved. The response rate was 100%.

2.2.5. Data coding. Data collected was coded and/or recoded via SPSS for Windows 11.0.

2.2.6. Data analysis and reporting. Used proper data analysis techniques, e.g., descriptive to conduct specific analysis that relates to research questions, and reported the results according to APA style. In this research, gender differences and the different attitudes of participants according to how long did they play video games are processed by line chart; and the outliers are reached by boxplot.

2.3. Metrical Tools In this research, 3 metrical indexes are used for the collection of research data, which are, age and gender of the participants, and how long did the participants play video games. The age of the participants are divided into two dimensions- five years as the division. The years of playing games are also divided into two dimensions- five years as the division. The questionnaire was tested by professors of our research center and peer evaluation. The data used in this paper are all from the questionnaire.

2.4. Working Definitions: Frequency: is the number of occurrences of a repeating event per unit time. It is also referred to as temporal frequency.

Mean: The mean is the arithmetic average of a set of values, or distribution; however, for skewed distributions, the mean is not necessarily the same as the middle value (median), or the most likely (mode).

Boxplot: a boxplot (also known as a box-and-whisker diagram or plot) is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation, lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation). A boxplot may also indicate which observations, if any, might be considered outliers.

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3. Data Analysis 3.1. Sample Demographics Table 1. Age of Sample Demographics AGE Frequency Percent Valid Percent Cumulative Percent 16-20 83 63.8 63.8 63.8 Valid 21-25 47 36.2 36.2 100.0 Total 130 100.0 100.0

Of the sample (n = 30), the sample ranged in age from 16 to 25 years. Those between 16 and 20 years took up 63.8% of the total sample. Those between 21 and 25 years were 36.2%.

Table 2. Gender of Sample Demographics GENDER Frequency Percent Valid Percent Cumulative Percent female 78 60.0 60.0 60.0 Valid male 52 40.0 40.0 100.0 Total 130 100.0 100.0

Of the sample (n = 30), 60.0% are females and 40.0% males.

Table 3. How long did the participants play video games of Sample Demographics YEAR OF PLAYING GAME Frequency Percent Valid Percent Cumulative Percent 0-5 16 53.3 53.3 53.3 Valid 6-15 14 46.7 46.7 100.0 Total 30 100.0 100.0

Of the sample (n = 30), regarding the experience of playing video games of the sample, 53.3% had an experience less than 5 years and 46.7% were more than 6 years.

3.2. From the Perspectives of Gender and Gaming Experiences 3.2.1. Achievement. Among the five items, males held a relatively higher perception level of achievement than females; those whose experience are more than 6 years took a higher perception level of achievement than those whose experience are less than 5 years; those between 21 and 25 years old held a similarly views with those between 16 and 20 years old.

The term “When I fail, the system encourages me to play it again.” received a relatively lower response ,but one outlier who is female and has a less than 5 years game playing experience with a positive response. Participants held a neutral attitude towards the item “I get a feeling of achievement when I play game.”

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3.2.2. Comparing video games with English learning. Among the five items, participants held a positive attitude towards this category. Females held a relatively higher perception level of comparing video games with English Learning than males; those whose experience are less than 5 years took a higher perception level of comparing video games with English Learning than those whose experience are more than 6 years; those between 21 and 25 years old took up a higher perception level of dominance than those between 16 and 20 years old.

One outlier who is female and had an experience more than 6 years held a negative attitude towards “When I play games, I do not worry about the bad things in my study.”; One outlier who is 21-25 years old, female, and had an experience more than 6 years held a negative attitude towards “I like the up-to-date information in the game than those in my English book.”

3.2.3. Dominance. Among the five items, participants held a positive attitude towards this category. Females held a relatively higher perception level of dominance than males; those whose experience are more than 6 years took a higher perception level of dominance than those whose experience are less than 5 years; One outlier who is female, and had an experience more than 6 years held a negative attitude towards “I can reach a new high in the game”.

3.2.4. Content of video games. Among the five items, participants held a positive attitude towards this category. Females held a relatively higher perception level of content of video games than males; those whose experience are more than 6 years took a higher perception level of content of video games than those whose experience are less than 5 years; those between 21 and 25 years old took up a higher perception level of content of video games than those between 16 and 20 years old.

3.2.5. Gaming interface. Among the five items, participants held a positive attitude towards this category. Females held a relatively higher perception level of gaming interface than males; those whose experience are less than 5 years took a higher perception level of gaming interface than those whose experience are more than 6 years; those between 16 and 20 years old took up a higher perception level of gaming interface than those between 21 and 25 years old.

One outlier who had an experience more than 6 years held a negative attitude towards “I like the beautiful music in the game.”; One outlier who had an experience more than 6 years held a negative attitude towards “I like the interesting navigation in the game. ”

4. Limitations of the Study The study only focused on participants who play educational games, thus excluding those who take online courses without playing video games.

In this research, participants are operationally defined as those who have the experience of video games, without the consideration of their online learning experience. As variety exists in different kinds of games, this diversity may bring about different attitudes and responses among participants, thus making it likely that one kind of motivational strategy is more appropriate than another.

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References: Chris Crawford. (2008). The Art of Computer Game Design, retrieved from: http://dev.csdn.net/ article/62/62062.shtm Ebner, M. & Holzinger, A. (2007). Successful implementation of user-centered game based learning in higher education: an example from civil engineering. Computers and Education, 49(3). Gayle V. Davidson-Shivers & Karen L. Rasmussen. 2006. Web- Based learning: design, implementation, and evaluation. Columbus: Pearson Merrill Prentice Hall. Batson, L. & Feinberg, S. (2006) Game Designs that Enhance Motivation and Learning for Teenagers. Retrieved from: http://ejite.isu.edu/Volume5/Batson.pdf Annetta, L. A., Cook, M., & Schultz, M. (2008). Video Games: A Vehicle for Problem-based Learning. Retrieved from: http://www.eegame.cn/show.aspx?id=877&cid=44 Prensky, M. (2001). Digital game-based learning. New York: McGraw Hill.

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Appendix Analysis of Motivation to Play Video Games of College Students The purpose of this survey is to take a rough overview of the relationships about motivations between ESL and computer games. It takes about 10 minutes to answer this survey: your time and cooperation is highly appreciated!

INSTRUCTIONS: 1. You do not have to complete the survey if you do not want to. 2. Please, circle the answer which is most suitable. There are 32 questions. 3. DO NOT FILL IN the following items on the answer sheet, since they will not be used: Last name, first name, grade, Signature. 4. The numbers 1-5 in part 2 stand for: Please check the appropriate number to the corresponding statements. 1= Strongly Disagree; 2=Disagree; 3=Not Sure/Not Applicable; 4=Agree; 5=Strongly Agree. 1) Strongly disagree 2) Disagree Neither agree nor disagree 3) Agree 4) Strongly Agree  Before the survey, let’s know a little bit about you. Please answer the following questions by filling in the blanks or circling the choice that is true for you. How old are you? ______Are you (circle your answer): Female (0) Male (1) What is your major? ______ Survey questions

Part 1: Your Video Game Experiences Please answer the following questions by filling in the blanks. By video games here mean games that you play on TVs (like Xbox or Playstation), on handheld devices (like Gameboy), or on computers (online or single computer games). 1. For how many years have you been playing video games? ______years

2. When you play video games, do you play alone or with others?

3. On a typical school day (Monday through Friday), do you play it every day？If your answer is yes，how long do you play per day?

4. On a typical weekend day (Saturday and Sunday), do you play it every day？If your answer is yes，how many hours do you play per day?

5. What is your favorite video game? Please write the name and the reasons why you choose it in the line below.

6. How often do you play your favorite video game?

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7. What is your second favorite video game? Please write the name and the reasons why you choose it in the line below.

Part 2: What Do You Think? These questions ask you about reasons you might have for playing video games. Please answer each question honestly. Circle the answer that shows how TRUE the reason is for you and tells why you like playing video games.

I LIKE PLAYING VIDEO GAMES BECAUSE… [Achievement] The system reward me when I do something well. 1 2 3 4 5 1) I get a feeling of achievement when I play game. 1 2 3 4 5 2) I am satisfied when I play the game. 1 2 3 4 5 3) I’d like to challenge new things rather than recite something. 1 2 3 4 5 4) When I am failed, the system encourages me to play it again. 1 2 3 4 5

[Comparing video games with English Learning] 1) When I play games, I do not worry about the bad things in my study. 1 2 3 4 5 2) Some video games help me know some English words. 1 2 3 4 5 3) Playing game is easier than understanding English grammars. 1 2 3 4 5 4) I can play with peers in games. 1 2 3 4 5 5) I like the up-to-date information in the game than those in my English book. 1 2 3 4 5

[Dominance] 1) I can reach a new high in the game. 1 2 3 4 5 2) I feel proud when my name is displayed in the top scores. 1 2 3 4 5 3) I enjoy the feelings to upgrade. 1 2 3 4 5

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4) Games testify that I can do something excellently. 1 2 3 4 5 5) I am proud when I talk about games with other people. 1 2 3 4 5

[Content of video games] 1) Playing games lets me do things rather than watching other people do things. 1 2 3 4 5 2) Playing games makes me a part of the activity. 1 2 3 4 5 3) I feel in control of the process when I play games. 1 2 3 4 5 4) Playing games lets me be in control of an action. 1 2 3 4 5 5) I like the competitive feels when I play games. 1 2 3 4 5

[Gaming interface] 1) I like the fantastic colors in the game. 1 2 3 4 5 2) I like the beautiful music in the game. 1 2 3 4 5 3) I like the interesting navigation in the game. 1 2 3 4 5 4) I like the framework in the game. 1 2 3 4 5 5) I like the role I can play in the game. 1 2 3 4 5

Thank you very much for participating in this survey.

14 EITT 2013, Williamsburg, VA, USA, November, 2013 Liu, Q. & Zhu, K. (2013). Using data mmning technologies to find learning objects usability rules for web-based learning systems. Proceedings of International Conference of Educational Innovation through Technology, 15-24.

Using Data Mining Technologies to Find Learning Objects Usability Rules for Web-based Learning Systems

Qingtang liu, Ke Zhu Central China Normal University Email: [email protected], [email protected]

Abstract: Researchers are interested to improve teachers’ and instructional designers’ performance in web-based learning systems. Learning ob�jects (LOs) are of great impor-importance at present, since they are the building blocks of different types of web-based learning systems. As the number of learning objects grows exponentially and our needs for learning expand equally dramatically, the lack of information or rules about the usability of learning objects places a critical and fundamental constraint on our ability to discover, manage, and use learning objects. This study presents a new approach of data mining and an assessment scheme by combining four computational intelligence theories, i.e., the Clustering Algo- rithms, the Classification Algorithms, and Association Algorithms, to identify the learning objective�� rules in web-based learning systems for teachers and instructional designers. Ex- perimental results indicate that the evaluation results of the proposed approach and scheme are improving the work of teachers in designing and searching, and also in the management of Los in a web-based learning environment according to the obtained learning objects usability rules.

Keywords: Learning Objects, Usability Rules, Data Mining, Learning Resources

1. Introduction As more of our commerce, entertainment, communication, and learning are occurring over the Web, the amount of data generated by online activities is skyrocketing. Commercial entities have led the way in developing techniques for harvesting insights from this mass of data for use in identifying likely consumers of their products, in refining their products to better fit consumer needs, and in tailoring their marketing and user experiences to the preferences of the individual. More recently, researchers and developers of online learning systems have begun to explore analogous techniques for gaining insights from learners’ activities online.

Around the world, large amounts of money have been spent on the development of courseware, computer applications designed to help people learn. With the advent of the World Wide Web in the late 1990s, it became possible to develop web-based courseware which was more adaptable and cheaper to create, but which lacked the educational and multimedia richness of the earlier monolithic applications (Polsani, 2003). Web is a large-scale service where information is stored in digital format and retrieved over networks and facilitates transmission of the information through internet. In recent years, learning objects as a new information transmission unit has become to be used on web (Boyle, 2008). A learning object:  is one or more files or ‘chunks’ of material, which might consist of graphics, text, audio, animation, calculator, or interactive notebook, designed to be used as a stand-alone learning experience,

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 is reusable—a single learning object can be used in multiple contexts for multiple purposes such as across curriculum areas, year levels, locales, and cultures, can be used as a component of a topic or unit of work alongside other digital and non-digital resources and tools,  is accessible from the world wide web and is referenced, located, and accessed by its metadata descriptors, and can be identified, stored, and tracked using a content or learning management system.

Learning Objects (LOs) are small in size, reusable digital resources that can be used with a web browser support. A short and explanatory definition suggested for LOs as interactive web based tools designed to enhance, amplify and guide learning. Polsani (2003) proposes an expanded definition about the Los: independent and self- standing learning content units predisposed to reuse in multiple instructional context. Opposed to traditional instructional media which can only be used in one place at a time, LOs can be reused in different contents. Reusability feature is based on the object-oriented paradigm of computer science, which is the main difference between LOs and classic web tools. LOs may be in the form of text, video, audio, graphics or multimedia. Teachers or instructional designers need an environment to manage, store and organize the LOs that are known as Learning Object Repository (LOR). LORs also help teachers or instructional designers create new courses on web that enable the applicability and reusability of LOs (Chitwood, 2000).

For organizations to take full advantage of the potential benefits of learning objects, learning objects must become an integrated part of the instructional technology infrastructure(South, 2000). Managing LOs is generally realized in a structured way as search operations in LORs. In order to create search operations, metadata that means “data about data” is used within LOs. Metadata is information about an object, be it physical or digital. As the number of objects grows exponentially and our needs for learning expand equally dramatically, the lack of information or metadata about objects places a critical and fundamental constraint on our ability to discover, manage, and use objects. Metadata has descriptive information about LOs for finding, managing, using and reusing them more effectively. Perhaps the main distinguishing feature of LO from other tools is their ready availability through web based repositories, collections that can be searched with standardized metadata (Brosnan, 2005). Metadata is traditionally found in the card catalogs of libraries. As information has become increasingly digital, metadata is also used to describe digital data using metadata standards specific to a particular discipline. By describing the contents and context of data files, the quality of the original data/files is greatly increased. For example, a webpage may include metadata specifying what language it is written in, what tools were used to create it, and where to go for more on the subject, allowing browsers to automatically improve the experience of users.

Metadata is defined as data providing information about one or more aspects of the data, such as:  Means of creation of the data  Purpose of the data  Time and date of creation  Creator or author of data  Location on a computer network where the data was created  Standards used

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For example, a digital image may include metadata that describes how large the picture is, the color depth, the image resolution, when the image was created, and other data. A text document's metadata may contain information about how long the document is, who the author is, when the document was written, and a short summary of the document.

The enormous growth of learning objects on the internet and the availability of preferences of usage by the community of users in the existing learning object repositories (LORs) have opened the possibility of testing the efficiency of��data mining technology ��on recommending learning materials to the users of these communities. It is known that LOR represent a special kind of digital ��col��- lection, in which the preferences about items can be considered to be related to contingent learning needs. In consequence, seeking learning resources can be hypothesized to be substantially different from selecting products for purchase or information resources. Learning objects have been analyzed from numerous perspectives. One area that has been largely overlooked is the learning objects usability rules. It is reasonable that this omission has occurred given that the investigation of learning objects is relatively new. This paper presents the advances in knowledge discovery activity applying the data mining (DM) techniques to the information that can be drawn from LOs.

2. Methodology 2.1. Data Sources in Learning Objects Information about LOs is diverse and often poorly structured. To conduct studies about usability rules of LOs, it is necessary to have an appropriate framework for studying. In recent years we have focused, among other things, to determine a set of attributes that can rep resent main LOs characteristics as fully as possible. We propose a characterization of LOs, based on ��four�� data categories to be processed:  LOs Metadata  The internal logical relationship of LOs  External assessments from questionnaire  Information obtained from user interacting Los

2.1.1. LOs metadata. Learning Object Metadata is a data model, usually encoded in XML, used to describe a learning object and similar digital resources used to support learning. The purpose of learning object metadata is to support the reusability of learning objects, to aid discoverabil- ity, and to facilitate their interoperability, usually in the context of online learning management systems (LMS). The IEEE 1484.12.1 – 2002 Standard for Learning Object Metadata is an inter- nationally recognized open standard for the description of “learning objects” (Friesen, 2005). Relevant attributes of learning objects to be described include: type of object; author; owner; terms of distribution; format; and pedagogical attributes, such as teaching or interaction style. This standard specifies the syntax and semantics of Learning Object Metadata, defined as the -at tributes required to fully/adequately describing a Learning Object. Learning Objects are defined here as any entity, digital or non-digital, which can be used, re-used or referenced during technology supported learning. Examples of technology supported learning include computer-based training systems, interactive learning environments, intelligent computer-aided instruction systems, distance learning systems, and collaborative learning environments. Examples of Learn- ing Objects include multimedia content, instructional content, learning objectives, instructional

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software and software tools, and persons, organizations, or events referenced during technology supported learning.

2.1.2. The internal logical relationship of LOs. We use ��thesaurus marking the relationship between Learning Objects. Four relationships are defined as follow: related terms, broader terms and narrower terms.terms. The technical route is fifirst rst to identify the Learning Objects, describesdescribe��s�� thethe relationrelation-- ship between the topics, then uses the theme graph grammar standardization of description, on the basis of the use of the thematic map processor, link resources and to organize these resources, finally to provide Interconnected network relationship map. Figure 1 shows the frame diagram of internal logical relationship of Topic.

Figure 1.The frame diagram of internal logical relationship of Topic

2.1.3. External assessments from questionnaire. In September 2012 we began to design a questionnaire that could be used to evaluate the level of inclusion of Learning Object under the support of our secondary development of Sakai learning platform. It was applied to more than 1121 Learning Objects. We consider evaluation around a set of quality indicators of educational multimedia objects, such as the coherence with the learning objectives, quality of the content, feedback, adaptation, motivation, design, presentation, usability, interaction, accessibility, reusability and compliance with standards (Zhu, 2012). The conclusions we obtained from this survey were the basis to redesign the questionnaire and refine the questions to have more and better results of the learning objects.

2.1.4. Information obtained from user interacting LOs. The interactions that Learning Objects have with students, with the instructors, and with educational resources are valuable indicators of the effectiveness of a learning experience. The increasing use of information and communi-

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cation technology allows these interactions to be recorded so that analytic or mining techniques are used to gain a deeper understanding of the Learning Objects usability rules and propose improvements.

2.2. LOs managing system Sakai is a community of academic institutions, commercial organizations and individuals who work together to develop a common Collaboration and Learning Environment (CLE). The Sakai CLE is a free, community source, educational software platform distributed under the Educational Community License (a type of open source license).

This paper proposes a framework of adaptive learning systems which use learning analysis technology. Figure 2 shows the Learning Object Management System Framework. Through the secondary development of Sakai learning platform, we integrated data analysis tool into it to achieve the function of adaptive learning system (zhu, 2012). The framework aims to provide an infrastructure that supports the development of instructional design activity. Particularly it provides solutions for LOs management.

Figure 2.The Learning Object Management System Framework

2.3. Integration and Checking Data Databases are highly susceptible to noisy, missing, and inconsistent data due to their typically huge size and their likely origin from multiple, heterogeneous sources (Menendez-Dominguez V, 2011). Low-quality data will lead to low-quality mining results. Data integration merges data from multiple sources into a coherent data store such a data warehouse. Careful integration can help reduce and void redundancies and inconsistencies in the resulting set. This can help improve the accuracy and speed of the subsequent data mining process.

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2.4. Data Cleaning Data cleaning routines attempt to fill in missing values, smooth out noise while identifying outliers, and correct inconsistencies in the data. We use a global constant to fill in the missing value. Use a measure of central tendency for the attribute.

2.5. Data Transformation and Data Discretization In this preprocessing step, the data are transformed or consolidated so that the resulting mining process may be more efficient, and the patterns found may be easier to understand. Data transformation routines convert the data into appropriate forms for mining. For example, in normalization, attribute are scaled so as to fall within a small range such as 0.0 to 1.0.Data discretization transforms numeric data by mapping values to interval or concept labels. For nominal data, concept hierarchies may be generated based on schema definitions as well as the number of distinct values per attribute (Kanellopoulos, 2012).

2.6. Apply Data Mining Result The range of possible solutions to the above problems is vast, extending far beyond our approach to instructional technology. While our approach to instructional technology alone cannot resolve all of the problems, it can have a significant impact on all of them. For this stage, we used SPSS（Statistical Product and Service Solutions）that provide data mining algorithms for clustering, classification, and association. Cluster analysis itself is not one specific algorithm, but the general task to be solved. It can be achieved by various algorithms that differ significantly in their notion of what constitutes a cluster and how to efficiently find them.

3. Results In this section, for each algorithm used in the study, the test characteristic and results obtained are shown. In each test, the number of clusters was calibrated to generate the greater amount of clusters having mutually exclusive attributes. In Table 1 some clusters obtained are presented.

Table 1. Some of the Best Rules Obtained with the Clustering Algorithms Cluster 1 Cluster 2 Cluster 3 Interface describes competen- Interface describes compe- Interface describes compe- cies: well tencies: very good tencies: scantly Component structure: se- Component structure: com- Component structure: iso- quenced pact lated Knowledge transfer: by web Knowledge transfer: by dem- Knowledge transfer: by quest onstrations problem solving Designer’s profile: Computing: Designer’s profile: Comput- Designer’s profile: Comput- advanced ing: average ing: average

Various tests were verified with ID3 algorithms with the already mentioned datasets. We ��ob��- tained a set of IF-THEN-ELSE rules from the algorithms. After an analysis, we eliminated those rules that were with irrelevant information .Table 2 shows some of the best rules obtained.

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Table 2. Some of the Best Rules Obtained with the Classification Algorithms Rules—Generated Rules—Interpretation format =PPT; knowledge transfer The LO has a high semantic density if it does =demonstrations; media balance = fulfill the next requirements: has a PPT for- regular => high mat contains demonstrations, and the media balance is regular. format =JPG; media balance = basic; structure =atomic =>low The LO has a high semantic density if it does fulfill the next requirements: has an JPG format, the media balance is basic, and the struc- format =MP3;educational resource ture is atomic. type = reading => high The LO has a high semantic density if it does fulfill the next requirements: has a MP3 format and is used as a reading in class.

The ��Apriori algorithm is a seminal algorithm for mining frequent item sets for Boolean association rules It explores the level-wise mining Apriori property that all nonempty subsets of a frequent item set must also be frequent At the kth iteration (for k≥2), it forms frequent k-item set candidates based on the frequent (k-1), and scans the database once to find the complete set of frequent k-item sets.

Table 3. Some of the Best Rules Obtained with the Association Algorithms Rules—Generated Rules—Interpretation version = final; environment = class- If the LO consists of the final version and room => aggregation level = 1 is used in perennial learning, then aggregation level is basic

structure = atomic; version =final; envir If the LO consists of atomic structure, final onment=classroom=>aggregation level version, and is used in perennial learning, = 1 then aggregation level is basic aggregation level= 1; version= final; If the LO is basic and security navigation easy navigation = security => environ- then it is used in perennial learning ment = classroom 4. Discussion If all of the properties of a course can be precisely defined in a common format, the content can be serialized into a standard format such as XML and loaded into other systems. When it is considered that some e-learning courses need to include video, mathematical equations using MathML, chemistry equations using CML and other complex structures the issues become very complex, especially if the systems need to understand and validate each structure and then place it correctly in a database (Wiley, 2000).

EITT 2013, Williamsburg, VA, USA, November, 2013 21 Proceedings of International Conference of Educational Innovation through Technology

This study investigated the rules which using Learning Objects. The findings generally derived from the model as well as earlier empirical studies. As mentioned earlier, we use LOs Metadata, the internal logical relationship of Los, external assessments from questionnaire and information obtained from user interacting Los as studying data source. It is possible for example, to package learning objects with SCORM specification and load it in adaptive learning systems which use learning analysis technology.

The findings indicate that the use of methods and data mining techniques are useful for the discovery of knowledge from information available in LOs. The result allows us to establish what elements are crucial to classify suggest, or recommend action values in a learning management system. Teachers are aware that they must plan learning experiences that match the differing competencies of their students. The findings also show that many teachers, however, are not familiar with how learning objects can make demands�� on students’ literacy, memory, and cognitive abilities. A mismatch in any area will result in a less successful learning experience for the student. Teachers need to understand this for both selection and use of learning objects.

5. Conclusions and Outlook In this paper, we presented an adapted methodology for the application of data mining techniques to Los, trying to discover relevant rule in its design and usage characteristics. This can help teachers to assess learning resource precisely utilizing learning objects usability rules in a web-based learning environment. Additionally, teachers can devote themselves to teaching and designing courseware since they save a lot of time in evaluating learning objects. More significantly, teachers could understand the factors influencing learning performance in a web-based learning environment according to the obtained interpretable learning objects usability rules. Students will have the benefit of access to the highest-quality learning resources available, making a significant impact on the quality of their learning experience and their learning outcomes.

Further collect data from other channel are required in future work. For example, it would be interesting to consider the situational of learning as an element to recommend teachers and students suitable learning objects with real environment. Also, it would be consider the location, equipment, even weather and something else related with learning.

References Brosnan, K. (2005). Developing and sustaining a national learning-object sharing network: A social capital theory perspective, In: J.B. Williams, & M.A. Goldberg (Eds.), Proceedings of The ASCILITE 2005 Conference, pp. 105-114, Brisbane: Australia. Chitwood, K., May, C., Bunnow, D., & Langan, T. (2000). Battle stories from the field: Wisconsin online resource center learning objects project. In D. A. Wiley (Ed.), The Instructional Use of Learning Objects: Online Version. Retrieved from: http://reusability.org/read/chapters/chitwood.doc. Kanellopoulos, D., & Kotsiantis, S. (2012). Evaluating and recommending Greek newspapers’ websites using clustering. Program: Electronic Library and Information Systems, 46 (1), 71– 91.

22 EITT 2013, Williamsburg, VA, USA, November, 2013 Using Data Mining Technologies to Find Learning Objects Usability Rules for Web-based Learning Systems

Zhu,�� K��. & Liu, Q.T. (2012). ��The Acceptance of Sakai Technology by the Chinese College Stu- dents, Advances in Information Sciences and Service Sciences, 4(17), 435–441. Menendez-Dominguez V, Zapata A, Prieto-Mendez ME, Romero C, Serrano-Guerrero J. (2011). A similarity-based approach to enhance learning objects management systems. In: 11th Interna��- tional Conference on Intelligent Systems Design and Applications. Friesen, N. (2005). Interoperability and learning objects: ��A��n overview of e-learning standardization. Interdisciplinary Journal of Knowledge and Learning Objects, 23–31. Polsani, P. R. (2003). Use and abuse of reusable learning objects. Journal of Digital Information, 3(4), Retrieved from: http://jodi.tamu.edu/Articles/v03/i04/Polsani/ South, J. B. & Monson, D. W. (2000). A university-wide system for creating, capturing, and delivering learning objects. In D. A. Wiley (Ed.), the Instructional Use of Learning Objects: Online Version. Retrieved from: http://reusability.org/read/chapters/south.doc. Wiley, D. A. (2000). Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. In D. A. Wiley (Ed.), the Instructional Use of Learning Objects: Online Version. Retrieved from: http://reusability.org/read/chapters/wiley.doc.

EITT 2013, Williamsburg, VA, USA, November, 2013 23 Proceedings of International Conference of Educational Innovation through Technology

Acknowledgement This work is supported by Humanity and Social Science foundation of Ministry of Education of China.No.11YJA880065.

24 EITT 2013, Williamsburg, VA, USA, November, 2013 Lv, W., & Zhang, Y.C. (2013). Design and implement of mobile learning platform based on android. Proceedings of International Conference of Educational Innovation through Technology, 25-32.

Design and Implement of Mobile Learning Platform Based on Android

Wei Lv, Yichun Zhang Nanjing Normal University Email: [email protected], [email protected]

Abstract: Android provides powerful support for the design and development of mobile learning platform with its open nature and other amazing futures. This paper designs and implements a mobile learning platform based on Android, which includes the main function modules of course learning, video learning,, informational content, learning tools and support and learning social network, and then develops a mobile course by the platform.

Keywords: Android, mobile learning platform, design, implement.

1.Introduction Mobile learning is a new learning form, which get educational information, educational resource, educational service by wireless mobile communication and wireless mobile devices. Mobile learning, in a broad sense, makes learners carry out learning activities by various mobile devices, such as mobile phone, Personal Digital Assistant (PDA), laptop computer and so on, via mobile communication network or WLAN (Wireless Local Area Network); while in a narrow sense, refers in particular to make learners use mobile phone to start learning activities via mobile communication network. As a new field of study,mobile learning makes anyone be able to acquire knowledge they wanted at anytime in anywhere, and really control their learning progress, and finally achieve the goal of lifelong education and learn socialization.

2.Android Futures Android provides powerful support for the design and development of mobile learning platform with its open nature and other amazing futures, such as full multi-touch, accelerometers, voice recognition, map and location services, support HTML5, OpenGL, etc.

Android, based upon a modified version of Linux kernel, is the first real open-source and completed mobile platform made for mobile devices. The following list highlights some of the most noteworthy Android features:

No licensing, distribution, or development fees, GSM, EDGE, and 3G networks for telephony or data transfer do not allow you to make or receive calls or SMS messages, or to send and retrieve data across mobile networks. Comprehensive APIs for location-based services such as GPS is multimedia hardware control including playback and recording using the camera. An integrated open source WebKit-based browser supports HTML5. Mobile-optimized hardware-accelerated graphics including a path-based 2D graphics library support for 3D graphics using OpenGL ES. An application framework that encourages reuse of application components and the replacement of native applications and a lightweight relational database for each application using SQLite

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allow your applications to take advantage of the managed relational database engine to store data securely and efficiently.

Android provides powerful support for the design and development of mobile learning platform with its open nature and other amazing futures.

3. Functions of Mobile Learning Platform With the growing popularity of smartphones, increasingly developed mobile operation system (OS), spread and application of 3G network and WLAN, the implementation mode of mobile learning grows from the traditional short message (SMS) to the developing client mode. A smartphone is a mobile phone built on a mobile operating system, with more advanced computing capability connectivity than a feature phone. The most notable feature of smartphone is that it provides a standardized interface and platform for user and developer to install or develop the third-party applications (App). Meanwhile, with the propagation of 3G networks and rapid development of WLAN, the quality of communication and speed of network transmission will not be the problems; therefore, smartphone-based mobile learning will have a wide application prospect in the future.

The following list is the main functions of mobile learning platform: Course Learning. Course learning mainly provides learning content for learner, along with the support and tools for learning and management of course and content. For teachers, they could manage the content of course information, syllabus, courseware, and extended resources, etc.; for learners, they could select course, learn course via browsing course information, courseware, extended resources, and interact with teachers, classmates or themself through various means like ask, discussion, comment, instant message, or publishing or sharing learning materials or feelings and experiences, etc.

Video Learning. Video, which is integrated of graphics, image, movement, sound and text, plays an important role in modern teaching, and so it is in mobile learning. Video learning provides video resource for mobile learning. For teachers, they could manage video resource by uploading, updating, recommending video and participate in interaction with learners; for learners, they could learn video resource through watching online, downloading video to local and interact with teachers, classmates or themself through various means like course learning above.

Informational Content. Informational content is designed to assist mobile learning and teaching management through providing content management and publish of educational information, notice and announcement and extended teaching resource. More importantly, it allows learners to subscribe the content they need and could push that content to their mobile client in time.

Learning Tools and Support. Mobile learning tools and support provide perfect learning tools and support for mobile learning. It is throughout the whole process of mobile leaning, and a distinguishing feature of mobile learning platform. What tools and support this platform provides includes comment, sharing, ask, blog, notebook, etc. Android, with its own features, provides powerful support for the design and development of those functions.

26 EITT 2013, Williamsburg, VA, USA, November, 2013 Design and Implement of Mobile Learning Platform Based on Android

Mobile Learning Social Network. Mobile learning pays more attention to the interaction and communication, both real-time and non-real-time, in learning procedure. This paper introduces Network-based Learning Community (NLC) to mobile learning and attempts to construct a mobile learning social network, which designed to gather learners and learners, learners and teachers to a mobile social network through the functions of friends, address book, news feeds, sharing, instant message (IM) and location based service (LBS), etc.

Figure 1. Functions of mobile learning platform.

All in all, mobile learning platform should be able to provide powerful features for helping and managing study to help learners to carry out self-regulated learning based on its advantage.

4.Design of Mobile Learning Platform This paper is to design and implement a mobile learning platform, under the prerequisite of take full advantage of existing course resources, ensuring communication safety, and for the propose that let anyone be able to acquire knowledge they wanted at any time in anywhere, and truly achieve self-directed learning.

4.1. Design Process This platform is designed under the principles of expandability, feasibility, practicability and security policy. The design and implementation of mobile learning platform has three stages: requirement analysis, design and implementation, as illustrated by the following figure.

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Start

Requirement Requirement Analysis Analysis

Server

Platform Architecture

Framework Design Client

Functional Design Design Functional Design

UI/UE Design Base Class

Base Class Module Design

Module Design

Implement Module Implement Module Implement

Application Application

End Figure 2. Mobile learning platform design flow chart.

4.2. Platform Architecture The platform uses client–server model (C/S). The server side includes various servers: Database server, Email server, instant message server (use Openfire [5] to implement), Streaming media server, Push server. Different servers which are combined by Web Application Server play different and indispensable roles in the platform. The client side refers primarily to Android based on mobile devices, including both mobile and tablet computers. GPS (Global Position System) satellite is used for LBS in the platform. The client side and server side communicate through mobile communication network or WLAN, as illustrated by the following figure.

Figure 3. Platform architecture sketch.

4.3. Server Side Design The server side is the core of the platform, which provides data content and data progressing for the platform. The design of server side includes system hierarchy design, access control process design, base class (includes interface, abstract class, utility class, common class) design, modules design, Application Program Interface (API) design, database design and optimization design, etc.

28 EITT 2013, Williamsburg, VA, USA, November, 2013 Design and Implement of Mobile Learning Platform Based on Android

4.4. Client Side Design The client side design is based on Android from the following functional modules: course learning, video learning, informational content, tools and support, mobile learning social network, etc. This paper designs each module from aspects of functional design, UI (User Interface) design, UE (User Experience) design, and interaction design.

In a word, the design of mobile learning platform should not only make the best of Android system, but also fully satisfy learners’ learning requirements.

5. Key Implementation 5.1. Development Environment Development language: Java Development operation system: Microsoft Windows 7 Development tools: Eclipse 3.7, ADT (Android Develop Toolkit) 2.1, JDK1.6.

5.2. Client API Related The client side and server side communicate through API. The business process in client side illustrated as the following figure.

Server

Request HTTP Client Response

API Service

VO JSON/XML ApiService To JSON/XML Parse To Parameters VO Callback

API Manager

Business Logic Components

Figure 4. Business process of client API.

The business logic components of client are invoked by API interface manager (ApiServiceManager); ApiService is responsible for converting Value Object(VO) to HTTP request parameter (Parameters); ApiService send an HTTP request to server by HttpClientInvoker; The server processes the request and sends back a response; ApiService parse response result (JSON/XML) into VO; ApiService provides Service Callback for business logic components to callback the result; ApiService returns VO to business logic components.

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Through the above analysis, the paper designs interface and class related to API, which mainly include ApiServiceManager, AbstractService, AbstractModelService, ServiceCallback, Auth etc. The class diagram illustrated as the following figure.

Figure 5. Class diagram of client API.

6.Application of Course Based on Mobile Learning Platform As a new learning form, mobile learning gets educational information, educational resource, educational service by wireless mobile communication and wireless mobile devices. Mobile learning promotes innovative practice of situated learning, social learning, and informal learning through penetrate into, associated with and blend with traditional learning mode. This paper takes “The Methods of Educational Technology Research” as an example to construct a mobile course by using the mobile learning platform.

6.1. Course Analysis “The Methods of Educational Technology Research” is one of the main courses of Educational Technology, which aims to lay theoretical and methodological foundations for research work and to cultivate students to do scientific research on the phenomenon and the law of educational technology. As educational technology research is an abstract concept, the important goals of the course are to solve the following questions: how to understand educational technology resource, how to carry out communication activities, how to conduct a self-assessment and how to apply educational technology, etc.

6.2. Application Strategy To achieve the goals of the course, this paper applies the following strategies according to the above analysis. To migrate and integrate course contents from traditional class or online learning to mobile learning platform, learners thus can learn course at any time in anywhere on demand through mobile terminals.

With the help of video learning function, learners can, on the one hand, learn repeatedly with a real sense of class teaching, on the other hand, broaden class teaching by watching non-class video content and take part in the related discussion.

30 EITT 2013, Williamsburg, VA, USA, November, 2013 Design and Implement of Mobile Learning Platform Based on Android

Assisted by the function of informational content, learners can subscribe personalized content according to their own demands to extend class learning. It greatly expands class-teaching content and promotes the development of learners’ research ability through providing and pushing forefront information of informational technology in time.

Mobile learning platform provides rich tools and support for mobile learning, by which it could alleviate the interactive problem in the large-scale classroom teaching and promote the communication, discussion and Q&A (question and answer) between learners and learners, learners and teachers.

Through the function of mobile social network, learners and teachers can construct a mobile learning social network to share the learning conditions, experience and class notes or to discuss questions, do timely communication and cooperative learning very easily.

6.3. Course Development According to the structure and function of mobile learning platform, and characteristics of course, the paper develops the mobile course of “The Methods of Educational Technology Research” as follows.

Course recommend Course content Course resources Course video Figure 6. Course of “The Methods of Educational Technology Research”

About. Include the basic information about the course such as Course Introduction, Study Guide, Syllabus, Course History and Teachers Information, etc. Content. Include 11 chapters’ course contents and each chapter contains 5 parts: Learning Reflection, Reading Literature, Card of Knowledge, Courseware and Exercise and Homework. These contents are especially designed to mobile learning, which is compelling and compressed for fragmented learning. Video. It provides more than 100 short videos and animations for learners to help them to solve the important and difficult issues of course. Resource. It provides extended course content in the form of special topics, which includes Technical Terms, Basic Theories, Basic Conception, Research Tools, Standard Specification, Research Focus, Research Projects, Frequently Asked Questions (FAQ), etc. and continue to add new resources.

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More. Other functions of the mobile learning platform are also applied to the course throughout the whole process of mobile leaning, such as comment, sharing, blog, ask and social network, which provide strong support for communication and interaction.

The course of “The Methods of Educational Technology Research”, as a practical example, implements the idea of mobile course design, and shows the functions of mobile learning platform based on Android. Similarly, other course could be developed according to the case.

7.Summary This paper is a completely original design in order to implement a mobile learning platform based on Android and takes “The Methods of Educational Technology Research” as an example to construct a mobile course by using the mobile learning platform. The mobile course migrates and integrates course contents from traditional class and online learning website to mobile learning platform and combines course contents, teaching video, learning resource, research tools and communication together, which are beneficial for educational technology majors to expand the way to study theories and methodologies and to cultivate their research abilities.

References Li, Y. B. ,& Zhang, S. (2005). Research overview of mobile learning. Modern Distance Education Research, (2), 30-34. Wang, G. Q. (2007). Research on learning strategy based on autonomous learning in distance education. E-education Research. Ye, C. L., Xu, F. Y., & Xu, J. (2004). Research overview of mobile learning. E-education Research, (3), 12-19.

32 EITT 2013, Williamsburg, VA, USA, November, 2013 Tang, H. T. (2013). Bookboard: encouraging early childhood students’ love of reading. Proceedings of International Conference of Educational Innovation through Technology, 33-38.

Bookboard: Encouraging Early Childhood Students’ Love of Reading

Hengtao Tang The Pennsylvania State University-University Park Email: [email protected]

Abstract:It has been widely recognized that reading interests are integral to engage early childhood students in reading materials and contribute to their reading acquisition; as such reading is advocated to start at early ages when children experience the “critical period” for learning.Bookboard is a subscription service for children’s books and now can be installed on mobile devices, such as iPhone/iPad, tablets, and etc. The mobile app, integrating game dynamics, constructivism, and metacognition, brings new hope of encouraging early childhood students’ love of reading. This paper will examine the potential for Bookboard to be integrated intothe early childhood students’ curriculum to stimulate their sustainable reading interests.

Keywords: Bookboard, Game Dynamics, Constructivism, Metacognition, Early Childhood Students, Reading Interests.

1. Introduction 1.1. Early Childhood Students’ Reading Interests Children’s reading literacy is significant for their future success in both schools and workplaces. Sheldrick-Ross, McKechnie, & Rothbauer (2006) implyilliterate boys will grow up to be at best unskilled laborers and lose their jobs and opportunities. Those illiterate people have to live in quiet desperation and, what is worse, become homeless or criminals (Stauffer, 2007).

Reading is considered as a form of language acquisition and supposed to start when early childhood students are in the age of most rapid improvement in language acquisition and symbolic thinking (Soderbergh, 1977; Pasts, 1976; and Lado, 1976). Psychologists, neuroscientists, and learning scientists ever propose children will experience a “critical period” for learning as they grow up from different perspectives. If learners can receive the appropriate“stimulus” during the “critical period”, early language acquisition will be significantly facilitated. As a form of language acquisition, the acquisition of reading also requires the appropriate stimulus to motivate children’s love of reading. Based on a series of researches on public libraries, Sheldrick-Ross, et al (2006) summarized children’s reading attitude turns out to be more negative as their age increases. Nielsen Book (2013, cited by Dredge, 2013) conducted a survey of 2,000 British children and parents and suggested that children’s reading shrinks in contrast to the rise of adoption of mobile devices and digital entertainment. Those trends of decrease in children’s reading necessitate new forms of “stimulus”,which will help early childhood students to develop and sustain their love of reading.

1.2. Bookboard Bookboard is a subscription service for children’s books that has a library of more than 300 books targeted at children ages 2-7 (Bookboard, INC, 2013). Now the subscription service has its own mobile app and can be available for mobile devices, such as tablets, iPhone/iPad, and etc. The

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 33 Proceedings of International Conference of Educational Innovation through Technology mobile app, integrating game dynamics, constructivism, and metacognition, brings new hope of encouraging early childhood students’ love of reading.

Featuring with game dynamics, Bookboard allows students to progressively unlock books to drive the engagement. For the initial set of books, Bookboard introduces artificial scarcity so that only limited choices are available for early childhood students. Provided with limited options, early childhood students are motivated to readthose books through and see what will come next. Upon the completion, more challenges of unlocking books serve as a reward mechanism to stimulate children to get attached with reading. Additionally, Bookboard invites parental involvement in creating a collaborative context for children to construct their reading literacy. Parents can open the account and creates profiles both for themselves and their children, which enables parents to participate in the inquiry process and get clearer about their kids’ learning progress. Finally, Bookboard also has its own database of the library that can record and visually represent the process and, with metadata on hand, the librarian can help decide next relevant books to read and apply collaborative filtering techniques to recommend books.

2. Curriculum-related Features of Bookboard 2.1 Game Dynamics Game dynamics are temporal evolution and patterns of both the game and the players that make the game or any gamified activity more enjoyable (Wu, 2012; Altrock & Traulsen, 2009). Priebatsch (2010) described four types of game dynamics, techniques used by game designers to make games fun and addictive, including appointment dynamic, influence and status, progression dynamic, and communal discovery. The progressive-unlock dynamic, used in Bookboard, adds the serendipitous surprise to the relatively more routine points and achievements of game mechanics.

When children read the book through Bookboard, they are provided with a series of challenges to unlock more books. For the first book, Bookboard will provide a narrow scope of selection for children to pick up, which is called tyranny of choice. Tyranny of choice is a prevailing psychological theory that states people feel overwhelmed and overloaded when provided with too many choices and are therefore unlikely to pursue any of the options available (Roets, Schwartz, & Guan, 2012; Ying, 2013; Schwartz, 2007). It is noted that the ratio of time spent browsing titles to time spent reading was too high for children. Therefore, Bookboard embedded artificial scarcity for the initial set of books which also helps avoid the waste of time to browse titles and the time spent reading is approximate to time spent with the mobile app. After the initial book is completed, children will face the next challenge that requires them to finish the second book to unlock the third one, which simulates a scenario that those children act like heroes in the video games and have to go through each inning to achieve the triumph.

In the gamification, challenges navigate game players to accomplish missions and then get rewardedfor doing so (Bunchball, INC., 2010). Additionally, it is challenges that help players set goals and enable them experience the actual feeling in certain scenarios (Bunchball, INC., 2010). There is a fair amount of literature examining the use of game dynamics to encourage participation and attachment to activities in multiple disciplines including commerce, education, and etc. (Cardaliaguet & Cressman, 2012; Hofbauer & Sigmund, 2003). However, even within these education-related studies, the great majority seldom sheds light on the early childhood students,

34 EITT 2013, Williamsburg, VA, USA, November, 2013 Bookboard: Encouraging Early Childhood Students’ Love of Reading especially on reading interests and acquisition.Bookboard innovatively applies game dynamics in stimulating children’s reading interests and presents great potential in engaging early childhood students. Hopefully, those challenges of unlocking new books will dynamically motivate users to read through current books and see what will come next.

2.2. Parental Involvement Vygotsky (1978) emphasizes the role of social environment, such as people, tools, agents, and etc., in human’s learning. He proposes the zone of proximal development that draws more attention to parents and capable peers’ influences in challenging and extending children’s efforts to understand (National Research Council, 2000). Children are possible to demonstrate more expertise in a higher level than where they areas long as they get proper scaffolding. Reading acquisition, as a form of learning activity, can be achieved by early childhood students via simply playing with their parents while reading, using large written words that children show intense interests (Soderbergh, 1977). It can be inferred that parental involvement significantly contributes to children’s reading acquisition. Bookboard allows parents to open an account in their name and continue to add more than 4 profiles under this account. With their own accounts, parents, in fact, will not interfere children’s reading but participate as an observer or facilitator who helps motivate early childhood students and provide scaffolding for those young childrento construct reading acquisition.

2.3. Visual Metacognition Metacognition is the “cognition about cognition” and “knowing about knowing” (Metcalfe &Shimamura,1994).Perceived as an inner thinking process rather than a visible activity, metacognition is not visible for learners to track in traditional settings. Therefore learners cannot monitor or reflect their original thoughts or proceeding plans. Researchers(Bransford, Brwon, & Cocking, 2000; Tanner, 2012; Resnick, 1987; and Collins & Ferguson, 1993)thus proposevisible metacognitionas an innovative approach in pedagogical practices.Bookboard has its own database that collects information of children’s reading for future analysis. Each time children complete reading on the app, Bookboard can save the record and creates a Progress Report for users which can provide different charts or pictograms to demonstrate users’ reading history and compare with certain standard.

Four categories of information can be tracked in the Progress Report. The first part reports readers the number of books they have read. Bookboard illustrates a ruler to measure the height of these books stack and compare with one animal’s height. Here is an example of the progress report that the height of books approaches Bear’s height: “8 books read. Stacked end to end, that’s 7 feet. Read 3 more books to match the height of an elephant!” The second part addresses the length of reading time. The system will automatically record the reading time andmake a comparison with other activities that consume the same length of time. Following the Bear example above, it will describe in this way: “Bear’s reading time: 0:58 spent, about how long it takes to watch 1 TV show.” Then the last two parts are analysis of the number of pages that children have read and the amount of money that has been saved through unblocking books.

Based on the data above, parents and children can track the metacognition data for their reading history and the visual representation of metacognition enables early childhood students

EITT 2013, Williamsburg, VA, USA, November, 2013 35 Proceedings of International Conference of Educational Innovation through Technology to conduct self-regulated learning and self-assessment on their reading. Zimmerman (2002) defines self-regulated learning as an activity that involves not only detailed knowledge of a skill but also“the self-awareness, self-motivation, and behavioral skill to implement that knowledge appropriately” (p. 66). His research further indicates that the practice of self-regulation can be a source of motivation for learners that will be a significant finding for researchers to stimulate children’s reading interests through facilitating them to conduct self-regulated learning.

3. Discussion and Future Research As a subscription service, Bookboard integrates game dynamics to provide more entertainment and engagement, invites parental participation to motivate early childhood students’ reading interests as constructivism implies, and supports visual metacognition to enable early childhood students to conduct self-regulated learning. Game dynamics have been proven to enable encourage participation and attachment to human activity in many disciplines but for education of early childhood students. In fact, the integration of game dynamics is also promising for early childhood students’ reading activities. Based on game players’ fundamental needs and desires, including desire for reward, status, achievement, self-expression, competition, and altruism among others, game dynamics inserts a series of challenges, trophies, rewards, and etc. to help define the goal for gamers and navigate them to move forward. Within the mobile app of Bookboard, game dynamics combines with tyranny of choice which can save more time in selection and enforce learners to concentrate on challenges, which is unlocking books. This enhanced experience will further address childhood learners’ desires for rewards, achievements, and self-altruism, and etc. and it will help them stimulate the love of reading. Constructivism emphasizes the role of social interaction in the learning and is a widely recognized theory in the realm of learning and instruction. Parents’ participation, as an essential element in constructing the social community for children’s learning, is highlighted in the service provided by Bookboard. Even though they will not directly participate in children’s reading activities but observe and motivate, parents’ focus, social interaction, and communication will potentially benefit children’s reading and increase their interests. Bookboard also addresses the desire for visual metacognition and make it possible for self-regulated learning. Provided with direct and fresh data on their reading records, early childhood students are probably to conduct self-regulated learning, which in turn can further stimulate children’s interests in reading. More significantly, those children turn out to be a prospective self-regulated learner who will examine acquisition as a controllable system and will assume greater responsibility for their achievement (Borkowski, Carr, Rellinger, & Pressley, 1990; Zimmerman & Martinez-Pons, 1986, 1990)

As above, Bookboard is quite promising in increasing early childhood students’ reading interests with its peculiar curriculum-related features. However, all the current assumptions are based on the literature and textual analysis which more empirical evidences are expected to be provided. Perhaps certain disadvantages can decrease the adoption rate and its achievement in increasing children’s reading interests. For example, Bookboard provides free apps and free trial version but its service charges a certain amount of fees, which may force users to balance the cost and the advantage of Bookboard and decrease the adoption rate. Researches demonstrate children’s interest and engagement in reading is essential in developing an affinity for reading (Soderbergh, 1977; Ross, McKechnie, & Rothbauer, 2006). Early childhood students’ reading interests feature with properties of participation, efficiency, stability, tendentiousness, and universality (Li, 2008), which

36 EITT 2013, Williamsburg, VA, USA, November, 2013 Bookboard: Encouraging Early Childhood Students’ Love of Reading

lends credibility to the assumption that testing early childhood students’ reading interests in terms of reading spontaneity, length of reading time, and mutual interaction. For future researches, in order to examine how game dynamics, parental participation, and visual metacognition equipped in Bookboard increases children’s reading interests, a qualitative research that will apply observation andphenomenography methodology to investigate the difference in children’s reading spontaneity, length of reading time, and mutual interaction between the use of Bookboard and other mobile apps for reading, such as Adobe Acrobat, iBook, and etc., will be expected to provide more insights and explanation for the social phenomenon.

References Altrock, P. & Traulsen, A. (2009). Fixation times in evolutionary games under weak selection, New Journal of Physics,11. Bookboard, INC. (2013). http://bookboard.com. Bookboard. Borkowski, J. G., Carr, M., Rellinger, E., & Pressley, M. (1990). Self-regulated cognition: Interdependenceof metacognition, attributions, and self-esteem. In B. Jones & L. Idol (Eds.), Dimensions of Thinking (pp. 53-92). Hillsdale, NJ: Erlbaum Bransford, Brwon, & Cocking, 2000 Bunchball, INC. (2010). Gamification 101:An introduction to the use of game dynamics to influence behavior. Retrieved from: http://www.bunchball.com/sites/default/files/downloads/ gamification101.pdf Cardaliaguet, P.& Cressman, R. (2012).Advancesin dynamic games: Theory, applications, and numerical methods for differential and Stochastic Games, New York, New York: Birkhauser. Collins, A., & Ferguson, W. (1993). Epistemic forms and epistemic games: structures and strategies to guide inquiry. Educational Psychologist, 28, 25-42. Dredge, S. (2013). Children’s reading shrinking due to apps, games and YouTube, http://www. theguardian.com/technology/appsblog/2013/sep/26/children-reading-less-apps-games Hofbauer, J.,& Sigmund, K.(2003). Evolutionary game dynamics, Bulletin (New Series) of the American Mathematical Society, 40,(4), 479-519. Lado, R. (1976). Early reading as language development. (R. Lado and T.Andersson, eds.) Georgetown University Papers on Languages and Linguistics, Number 13. Early Reading. Washington, D.C.: Georgetown University Press. Li, X. (2008). Research on the structure and developmental traits of early childhood students’ reading interests, Shenyang Normal University, Master Thesis. Metcalfe, J., &Shimamura, A. P. (1994). Metacognition: Knowing about knowing. Cambridge, MA: MIT Press. National Research Council. (2000). How people learn: brain, mind, experience, and school: expanded edition. Washington, DC: The National Academies Press, 2000. Past, K. (1976). Acase study of preschool reading and speaking acquisition in two languages’. Georgetown University Papers on Languages and Linguistics, No. 13:Early Reading. R. Lado and T. Andersson, eds., Washington D.C.: Georgetown University Press. Priebatsch (2010). The game layer on top of the world. TED Talk. Retrieved from: http://www. ted.com/talks/seth_priebatsch_the_game_layer_on_top_of_the_world.html Roets, A., Schwartz, B. & Guan. Y.J (2012). The tyranny of choice: A cross-cultural investigation of maximizing-Satisfying Effects on Well-Being. Judgment and Decision Making, 7(6),689- 704.

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Resnick, L. (1987). Education and learning to think. Washington, DC: National Academy Press. Schwartz, B. (2007). There Must be an Alternative. Psychological Inquiry, 18(1),48-51. Sheldrick-Ross, C., McCechnie, L. & Rothbauer, P.M. (2005).Reading Matters: What the research reveals about reading, libraries and community. Oxford: Libraries Soderbergh, R. (1977). Reading in early childhood. A linguistic study of a preschool child’s gradual acquisition of reading ability. Washington, D.C.: Georgetown University Press. Stauffer, S. (2007). Developing children’s interest in reading, Library Trends,56, (2). Tanner, K. D. (2012). Promoting student metacognition. CBE—Life Sciences Education,11,113- 120. Vygotsky, L. (1978). Interaction between learning and development, Mind and Society, pp. 79- 91. Cambridge, MA: Harvard University Press. Wu, M. (2011). Gamification from a Company of Pro Gamers, Lithosphere. Retrieved from: http://lithosphere.lithium.com/t5/science-of-social-blog/Gamification-from-a-Company-of- Pro-Gamers/ba-p/19258 Ying, C. (2013). Bookboard launches app to encourage children to read more by limiting their choices. Retrieved from: ttp://techcrunch.com/2013/03/21/bookboard-launches-app-to- encourage-children-to-read-more-by-limiting-their-choices Zimmerman, B.J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64-70. Zimmerman, B.J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25(1), 3-17. Zimmerman, B. J.& Martinez-Pons, M. (1986). Development of a structured interview of assessing student use of self-regulated learning strategies. American Educational Research Journal, 23, 614-628 Zimmerman, B. J. & Martinez-Pons, M. (1990). Student differences in self-regulated learning: Relating grade, sex, and giftedness to self-efficacy and strategy use.Journal of Educational Psychology, 82, 51-59.

38 EITT 2013, Williamsburg, VA, USA, November, 2013 Wang, J. & Song, X. (2013). Study on the promotion of electronic textbooks in universities. Proceedings of International Conference of Educational Innovation through Technology, 39-42.

Study on the Promotion of Electronic Textbooks in Universities

Jide Wang, Xuexue Song Henan University Email: [email protected],[email protected]

Abstract: Because of their own characteristics, the electronic textbooks are gradually popularized and applied in the field of education. The promotion of electronic textbooks in universities has its unique advantages and value. Therefore, this study defines the concept of electronic textbooks, theoretically analyzes the feasibility of the promotion of electronic textbooks, and then prepares the questionnaire and distributes in the teachers and students of Henan University according to the innovation diffusion theory, to investigate the factors influencing the promotion of electronic textbooks, and finally tries to provide some corresponding promotion recommendations.

Keywords: Electronic textbooks, innovation diffusion, University

1. Introduction In recent years, the demands of lessening the school load in primary and secondary schools are increasing. Although electronic schoolbag is controversial, as a modern solution strategy, it gradually begins to promote and is used in primary and secondary schools in some big cities. As Electronic schoolbag’s core, Electronic textbooks have been one of the scholar hotspots in the domestic and foreign.

In 2011, the New Media Consortium in the United States released “Horizon report”, which pointed out that e-book technology would have a wide impact on the global higher education, in the next year or even a short period of time, e-book technology would become the mainstream media of teaching, learning and creativity, and be accepted by the vast number of educators and used in teaching practice.

The development of Chinese education information not only requires the education system, methods of information, but also needs the modern form content and of the textbook . As one of the main sources, from which the students learn and acquire knowledge, textbook electronic is an inevitable trend in the information age. The research on the promotion of electronic textbooks in universities has great theoretical and practical significance.

2. The Concept of Electronic Textbooks There is no uniform definition of electronic textbooks at present, and it can mainly be divided into the following categories: publications, teaching software, teaching system and learning environment. This paper thinks that the electronic textbooks are narrowly textbooks, referring to the special class of e-books, which meets specific content standards (curriculum standards) and integrates text, images, sound, video and other forms of information. And their use must be considered three core elements: the contents of textbooks, reading software and electronic reading terminal at the same time.

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The teaching content should conform to a certain curriculum standard and the learners’ cognitive characteristics based on the educational and teaching principle, which integrates text, pictures, sound, video and other forms of information. Reading software is running program, with search, font adjustment, bookmarks, notes, bookstores and shelves etc., which meets the requirement of teaching and reading. Electronic reading terminal is the terminal which displays the electronic teaching content, including computer, iPad, intelligent mobile phone, e-book reader etc.The iPadis the most ideal reading terminal because of its portability and suitability for reading.

3. The Feasibility of Electronic Textbooks’ Promotion in Universities 3.1. The Special Requirements of Teaching in Universities University teaching has its own teaching objects and objectives. First of all, the students are the new generation, who grownup with the popularity of computers and the Internet. Information technology has subtly changed their brain structure and cognitive style, their innate technical accept ability and fast retrieval capabilities, which provided convenience for the promotion of electronic textbooks. Secondly, most college students have formed their own unique style of learning. As for the knowledge imparted by teachers, they will not accept fully, and accept, or neglect, or rejection according to some standards.

Besides, the teaching process in universities is mainly to guide students independently to explore knowledge. So the students can control their own time, learning approaches, learning content. Therefore, it is needed to provide rich resources in universities, which are easy to understand and attractive learning environment for students. We can promote electronic textbooks in universities, in order to achieve this goal.

3.2. The Advantage of Electronic Textbooks Electronic textbooks have large capacity, which can provide students rich resources. At the same time they are easy to carry. According to the needs of teaching, the teaching content in electronic textbooks can be revised and updated by downloading from the network.

In addition, the electronic textbooks breakthrough paper textbooks only text and little pictures, take the combination of words, pictures, sound and video in the aspects of visual, auditory and tactile, or dynamically or statically to convey information to students, which can stimulate the students’ desire for knowledge and interest. The electronic textbooks can make up for the shortcomings of traditional textbooks. Therefore, the promotion of electronic textbooks is possible.

3.3. The Application Experience of Electronic Textbooks In foreign countries, textbooks are expensive as well as technology developed, the electronic textbooks have been successfully applied in universities. Constellation is one example. The textbook system is compiled by Ashford University in the United States, mainly for its school curriculum.

It has a variety of access such as Constellation web browser, iPhone, Kindle and iPad, and you can read online, or download to the local. In addition, the Constellation also provides rich learning materials, including basic reading, audio-visual materials, interactive exercises etc., to help students achieve learning goals faster. In future, Constellation will be used more and more widely,

40 EITT 2013, Williamsburg, VA, USA, November, 2013 Study on the Promotion of Electronic Textbooks in Universities some undergraduate and postgraduate courses will use it too. Electronic textbooks’ application experience in foreign universities provides strong support for the promotion in universities.

4. Investigation and Analysis of Electronic Textbooks’ Promotion in Universities Based on the current study and the innovation diffusion theory, This study investigated the influencing factors of electronic textbooks promotion in universities, from the basic cognition, hardware technology support, personal factors, teaching support, environmental factors and textbook selection dimensions. Questionnaires were randomly distributed into the teachers and students in Henan University, and the survey results were counted and analyzed by SPSS 18.0. The results are as follows:

(1) Most of the teachers and students thought that they needed electronic textbooks, and knew and understood the electronic textbooks through the network, but used them a little. Therefore, the possibly of using method of electronic textbooks is primarily paper textbooks and supplemented by electronic textbooks or the coexistence of paper and electronic textbooks at the same time.

(2) The style of using electronic textbooks is mainly for reading at any time, the second is obtaining the frontier subject knowledge, improving the learning interest and efficiency, reducing the workload, increasing the interaction between teachers and students and so on. But it can’t reduce the learning cost. Affecting health is the largest obstacle of electronic textbooks using. In addition, there are also some obstacles, such as depending on the hardware equipment.

(3) The price of electronic textbooks reading device that students can generally accept is less than 500 Yuan, and the standby time is more than 10 hours. Electronic textbooks should have the functions of searching, class notes, learning tools, classroom recordings, job management, marking and real-time communication. Teachers and students have different opinions in teachers monitoring. In addition, both the teachers and the students thought that electronic textbooks should have the same standard and sufficient bandwidth to support and the instructional design would be the key.

(4) Teachers and students were willing to explore and try new things, students generally thought that they could use electronic textbooks skillfully, and teachers preferred to recommend electronic textbooks to others. The textbooks using in universities are mainly determined by the school authorities or verified by school. The teachers choose Textbooks mainly according to the correlation with teaching content, authors and editors and publishers. The school educational administration department and the bibliography mailed by press, the teachers can obtain the information of textbooks through the network.

(5) Both the teachers and the students thought that electronic textbooks should provide abundant curriculum materials; need to protect the content and network security, and the school should adopt policies to accelerate the promotion of electronic textbooks. The students thought that the school should reduce the price of electronic equipment, ensure the quality, and construct digital campus and so on. The teachers thought that the school should open a pilot, experiment promotion, and skills training. In addition, the students also believed that teachers would have great influence on the promotion of electronic textbooks.

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5. The Proposal of Electronic Textbooks’ Promotion 5.1. The Improvement and Standardization of Electronic Textbook Itself The key to electronic textbooks’ promotion is that electronic textbooks have their own advantages, but they still have some shortcomings. The survey results show that: the main reason hindering the promotion of electronic textbooks is that it can affect reader’s health. In addition, teachers and students are reluctant to use them, because they cannot achieve good reading effect, depend on the hardware equipment.

With the development of technology, the application of the technology such as electronic paper can reduce radiation on the body. At the same time, human interface design can make reading more comfortable; Special maintenance service also can further improve the use of hardware devices. Only in this way, we can continuously improve the function of electronic textbooks and fully meet the needs of users, the electronic textbooks will be better to promote.

5.2. The Shift of Reading Consciousness With the popularity of the Internet, the network is quietly changing the reader’s reading and thinking habits, generating and cultivating the new reading culture of digital age. The main characteristics of new culture are the autonomy of the reader, which has a huge impact on the traditional reading pattern. Besides, it is predicted that the cheaper and more convenient electronic publications will fully replace the traditional paper books in the future.

The students in universities generally have electronic reading devices, such as computers, mobile phones etc., but the real use of electronic textbooks is rarely. On one hand, because some supporting facilities are not perfect, such as wireless network service and charging socket. On the other hand, the concept of students’ reading also needs to change. We must be aware that electronic reading is an inevitable trend and should make full use of their function. Therefore, the learning process should start to use electronic textbooks and try to adapt electronic reading at present.

5.3. Demonstration of the Opinion Leaders Opinion leaders refer to the “active” persons, who provide information for others in interpersonal communication network and influence others. In the process of electronic textbooks’ promotion, teachers have great influence on it. Teachers can be regarded as opinion leaders through the demonstration of some backbone teachers can better and promote electronic textbooks faster. In addition, the school authorities have the right to determine textbook, its support to the promotion of electronic textbooks will have strong authority. So the promotion strategies of electronic textbooks in universities should take full account of the opinion leaders and make promotion access according to the specific situation. In this way, the promotion will have a multiplier effect.

As a new thing, the research related to electronic textbooks is just beginning. The following research about promotion model and the test of practice is the key, which requires joint efforts of more and more researchers!

42 EITT 2013, Williamsburg, VA, USA, November, 2013 Wang, L., Si, Z., Zhao, X., & Xu, K. (2013). A study on IWBs’ instructional application levels in China mainland. Proceedings of International Conference of Educational Innovation through Technology, 43-58.

A Study on IWBs’ Instructional Application Levels in China Mainland

Lu Wang, Zhiguo Si, Xiaoliang Zhao, Ke Xu Capital Normal University Email: [email protected], [email protected], [email protected], [email protected]

Abstract: In recent years, Interactive whiteboards (IWBs) have been rapidly promoted and popularized in elementary and secondary schools. However, studies have shown that IWBs have not been effectively used in those schools. In terms of this issue, stratified sampling method was used to gather 40 teaching videos with IWBs involved. After using content analysis, video case analysis and statistical analysis methods, a framework of IWBs’ instructional application levels was concluded. It includes 3 first-level elements, and 8 second-level elements. Authors have found that, there are three obvious application levels of IWBs’ use in elementary and secondary schools: the primary level echoes IWBs’ application level of visual aiding tools, the intermediate level echoes IWBs’ application level of resource-based learning, and the advanced level echoes IWBs’ application level of collaborative construction; Teachers are the key elements determining IWBs’ instructional application levels. It can be concluded from the application levels and key elements found in this study that, teacher trainings can be stratified: the starting point is cultivating IWB- based core values, the frame is providing analyzing cases as scaffolds, and the main goal is developing IWB-based strategic knowledge.

Keywords: IWB, teaching elements, TPACK, teachers’ training course

1. Introduction In recent years, many countries have experienced of IWBs’ rapid popularization in elementary and secondary schools. For instance, a UK national study in 2005 showed those 49% elementary teachers, 77% secondary math teachers, and 49% secondary English teachers were using IWBs (Miller, Averis, Door, & Glover, 2005). The IWB includes IWB and interactive television (ITV). Since IWBs can provide interesting opportunities and learning environments for learners’ construction and the interaction between learners and electronic content (De Vita, Verschaffel, & Elen, 2012); effectively improve class presentation and instruction’s “stereoscopy”; deepen inquiry depth between students, as well as teacher and students; broaden the extent of electronic resources’ processing; help teachers apply their plans; make learning deeper and faster (Becta, 2004), IWBs have changed classroom instruction and teachers’ professional development (Annetta & Minogue, 2004).

However, in last 10 years, experience gathering from worldwide promotion of information and communication technologies in education has shown that those technologies would not automatically benefit education. In educational system, integrating information and communication technologies is a complex and multidimensional process. It involves technologies themselves, as well as curriculum, teaching method, educational system, teacher capacity, and constant funding support, among which, providing teachers with enough primitive resources and trainings is the easiest way to promote technologies (Anderson, 2002). As pointed by many researchers, the huge popularization of electronic interactive devices, such as IWBs, hasn’t largely improved instruction, EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 43 Proceedings of International Conference of Educational Innovation through Technology and the devices have not been thoroughly used. Actually, in many schools, the application of IWBs is on the trial stage, and few teachers studied and used this kind of technological device in schools (Parigi, 2011; Chen & Chen, 2007). Due to the reasons mentioned above, the issue that IWBs have not been effectively used has caught more and more researchers’ attention.

In terms of the issue mentioned above, research has been done on IWB’s acceptable technological model, teachers’ attitudes towards IWBs, and IWB’s application levels (De Vita, Verschaffel & Elen, 2012; Aseei & Majed, 2012; Glover & Miller, 2004). This paper starts from the cases that using IWBs in instruction, bases on instructional elements, analyzes IWBs’ stratified standards and characteristics, and finds out existing issues, which provides constructive suggestions for improving the application of IWBs, as well as tries to fill the blank in the field of study on IWBs’ application.

2. Literature Review 2.1. Instructional Elements Related to Instructional Application Levels Instructional elements are the units or elements constituting instructional activities (systems). Researchers in the field of educational theory have done various researches in terms of instructional elements. However, due to many reasons, researchers hold different, even divergent views on instructional elements (Dong, 2005). Like F. C. Butler says, in most cases, there are some normal elements, conditions, and processes affecting most learning styles; No matter how learning style, teaching content, teaching method, and student’s characteristic changes, some elements must be taken into consideration, some conditions should be satisfied, and some processes will happen for sure (Sheng, 1990).

Thus, by selecting and integrating existing views, the instructional elements involved in this study should constitute an effective and holistic structure, which can help us learn more about teaching process based on electronic interactive instructional devices, and provide sound and realistic guidance for various staff that use electronic interactive teaching devices in teaching processes. Thus, this study categorizes instructional elements as instructional systematic elements, instructional procedural elements, and instructional environmental elements.

2.1.1. Instructional systematic elements. Basic instructional elements should be sufficient and necessary conditions for constituting instructional activities. Former Soviet Union educational theorist Babansky firstly points out when analyzing instructional process’s structure, instruction is a kind of human activity, and it’s double-sided. It is an interaction between teacher and students on certain instructional physical condition, mortal psychological condition, and aesthetic condition. In his opinion, elements teacher, student, and condition are instructional systematic elements, which are instructional system’s systematic elements.

2.1.2. Instructional procedural elements. Instructional theorists in Berlin, Germany think that the basic elements affecting instructional process are instructional intention (purpose), instructional topic (content, audience), media (tool), and media’s prerequisites (anthropological and sociological conditions). F. C. Butler says, major elements affecting instructional process are (1) context: conditions having effect on learning new knowledge or skills, including students’ external contextual motivation, (2) motivation: reasons to learn new knowledge or skills, (3)

44 EITT 2013, Williamsburg, VA, USA, November, 2013 A Study on IWBs’ Instructional Application Levels in China Mainland organization: structures and characteristics of new and necessary old knowledge or skills, (4) application: trial of new knowledge or skills, (5) evaluation: evaluation of the trial of new knowledge or skills, (6) repeat: practice of new knowledge or skills, (7) conclusion: transfer new knowledge or skills to new contexts. Chinese scholar also proposed a framework in terms of an effective class’s basic elements, which is comprised of context and question, reading and thinking, interaction and guidance, and practice and feedback (Yu, 2007).

2.1.3. Elements of instructional environment. According to the notion of instructional environment explained in Simplified International Pedagogical Encyclopedia: Instruction (A), classroom environment includes psychological environment and learning environment. Psychological environment refers to the atmosphere in the class as a social group, which has potential influence on students’ learning. Learning environment includes physical learning environment, devices, tools and resources for training. Prof. Tian (Tian, 1993) pointed out that elements constituting instructional environment are complex. The instructional environment is a complex system comprised of various elements, and almost everything in the school, physical and psychological, tangible and intangible, can be called as a basic element constituting instructional environment. These different elements are interrelated and interplayed, which create a school’s specific systematic instructional environment.

In conclusion, among teacher, student, and conditional systematic elements, IWBs belong to conditional elements. In an informationized instructional system with IWB involved, to find out instructional process elements, we should consider Prof. Butler’s views: firstly find out must- consider elements, must-meet requisites, and must-happen processes. We can infer that instructional procedural elements, operational activities, control regulation, and instructional evaluation are must-consider elements and will-happen processes; when it comes to environmental elements, device configuration and information environment should serve IWBs.

2.2. Technological Pedagogical Content Knowledge (TPACK) Teachers are elements of an instructional system, key factors of informationized education and technology integration, and initiative actors. Considering the issue that in the field of information technology and curriculum integration, more attention is paid to “technology” and “student” rather than “teacher”, Innovation and Technology and Committee, American Association of Colleges for Teacher Education as chief editor, 18 scholars as authors published Technological Pedagogical Content Knowledge: Educator Manual, based on the research of Doctor Matthew J. Koehler and Doctor Punyas Mishra from Mississippi State University. This manual introduces “technological pedagogical content knowledge (TPACK)” to elementary school teachers as their knowledge’s framework. TPACK stresses that in instructional process, teachers should focus on content knowledge (CK), pedagogical knowledge (PK), technological knowledge (TK), as well as the intersections of them, Pedagogical content knowledge (PCK), technological content knowledge (TCK), technological pedagogical knowledge (TPK), technological pedagogical content knowledge (TPACK), which is shown in figure 1.

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Technological Pedagogical Content Knowledge (TPACK) Pedagogieal Knowledge Content Knowledge (PK) (CK) Pedagogical Content Knowledge C P (PCK)

Technological Content Knowledge Technological Pedagogical (TCK) Knowledge T (TPK)

Technological Knowledge (TK)

situation

Figure 1. TPACK’s framework (Koehler, Mishra & Yahya, 2007) A scholar from Singapore concludes the definitions and examples of seven kinds of knowledge created by TPACK framework.

Table 1. Structure of TPACK (Chai, Koh & Tsai, 2011) Structure of TPACK Definitions Examples Knowledge CK Knowledge on subject Science or math knowledge Knowledge on students’ learning, teaching method and Teach different knowledge PK process, different pedagogical (light or electricity) using theories, and instructional PBL method evaluation on a subject Knowledge on technologies’ Know how to use web 2.0 tools TK characteristics, performance, (such as wiki, blog, Facebook) and application. Knowledge on how to use different instructional strategies Know how to teach math PCK to help students better concepts using analogy understand Knowledge on using technology Know how to use animation TCK to present content in various technology to present solar ways system Know how to use wiki Knowledge on how to use technology as an online tool TPK different known technologies to to encourage collaborative support instruction learning Know how to use wiki Knowledge on how to as communication tool TPACK “teach and learn” with actual to improve collaborative technologies involved performance

46 EITT 2013, Williamsburg, VA, USA, November, 2013 A Study on IWBs’ Instructional Application Levels in China Mainland

It can be seen from table 1 that, like Shulman mentioned, CK includes concept, theory, perception, organizational framework, evidence, proof, and practice and method of the development of certain subjects. PK is teachers’ deep understanding of instructional process and practice, which requires teachers to understand developmental theories of cognition, society, and learning, and how they can be applied to students. Comparing to CK and PK, TK is more unstable, which makes it very hard to define and name it. It should be noticed that the conceptualization of TK has no assumed “end state”, instead, it is developmental, involving, and is able to interact with diversified technologies.

TPACK is a kind of thinking method, which requires CK, PK, TK, and more importantly, the complex interactions among these three elements. PCK is the intersection of CK and PK. PCK is in line with and assembles the concept of instructional knowledge noted by Shulman, which covers basic knowledge of teaching and curriculum-based learning in certain subject, as well as the assessment of that learning. TCK requires teachers to understand that technology and content are affecting and limiting each other: firstly, the show-up of new technology has radically changed pedagogical content we need to consider; Secondly, technology is not neutral, different technologies will encourage different attitudes and ways of thinking. Thirdly, the change of technologies has provided new metaphorical meanings and cognitive thinking of the world. TPK requires sufficient understanding of a certain technology’s potential advantages and limitations, which will help teachers to develop instructional design and strategies in accordance to subject development. Moreover, TPK specially stresses that teachers should understand the flexibility of necessary tools, which are used to meet certain instructional goals; possible specific-type learning activities; and the best application of related technologies in educational environment. TPACK is a new form of knowledge, which surpasses the vital part formed by CK, PK, and TK. TPACK is also a new form of knowledge, which created by teachers by integrating technology, instructional techniques, and subject content. TPACK has four vital elements: holistic idea on integrating technology into teaching specific subject; knowledge on curriculum and resources on integrating technology with learning on specific subject; knowledge on students’ use of technology to understand, think and learn; and knowledge on instructional techniques and presenting forms of using technology to teach specific subject.

Until now, from research on elementary and secondary school teachers’ use of various technologies in teaching, it has been proved that teachers have not finely use technologies in technological environment, and their applications are limited in terms of breadth, variety, and depth, that is, they have not appropriately integrated technology into curriculum-based teaching and learning (Groff & Mouza, 2008; Levin & Wadmany, 2008).

2.3. Levels of the Integration of Electronic Interactive Instructional Device and Curriculum According to international research (Ma &Yu, 2002; Wang, 2009; He, 2012a; He, 2012b), on the levels of the integration of information technology and curriculum, considering the characteristics of IWBs or ITV and their three instructional procedural elements: operational activities, control regulation, and instructional evaluation, authors concluded that there are six levels of the integration of IWB-based information technology and curriculum, as explained in table 2.

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Table 2. Levels of the integration of electronic interactive instructional device and curriculum Operational process Instructional strategy No Device Level Teacher’s Student’s Control Instructional configuration role role regulation evaluation IWB/ITV Electronic interactive Paper test and its Knowledge To be Didactic 1 instructional device Oral supplemental giver instilled teaching as presenting tool responses devices IWB/ITV Mostly to Electronic interactive and its Knowledge be instilled, Didactic instructional device supplemental giver, have chances teaching Paper test 2 as communicating devices Activity to participate One-on-one tool +intranet/ organizer actively coaching internet Electronic interactive IWB/ITV instructional Guide and Explorative Test/ and its Active 3 device as resource- helper of learning students’ supplemental participant providing supporting instruction strategy works devices platform IWB/ITV Knowledge Electronic interactive and its giver Individual Test/ instructional device supplemental Learning Active learning 4 students’ as information devices guide participant Collaborative works processing platform +intranet/ Activity learning internet organizer Comprehen-- Learning sive Learning Electronic interactive IWB/ITV guide strategies Learning instructional device + video Learning Active such as 5 result-based as collaborative conference helper participant problem assessment platform system Activity solving and organizer mission driven Mostly discovery Learning Active Works learning, Electronic interactive guide explore assessment IWB/ITV+ empirical instructional device Learning active creates 6 recording learning, as developing helper discover valuable system mission- platform Learning Active and new driven promoter construct knowledge learning strategies

48 EITT 2013, Williamsburg, VA, USA, November, 2013 A Study on IWBs’ Instructional Application Levels in China Mainland

2.4. Conclusion Based on what has been discussed above, there are three first-level elements related to instructional application level: teacher, technology and student.

Teachers are elements of an instructional system, key factors of informationized education and technology integration, and initiative actors. Teachers are knowledge actors, whose activity is knowledge-based, and whose knowledge is practical. Based on TPACK framework, teachers as actors in instructional process, their practical knowledge related to technology integration includes: TK, TCK, TPK, TPACK. Thus, first-level element teacher includes 4 second-level elements.

Technology is a process of systematic using science or other organized knowledge in practical activities. It is also a collaborative system comprised of method, approach and rule to meet specific goal, is experience, knowledge and techniques in farming. Technology includes three sets of key elements: wisdom and experience, methods and skills, tools and measures. In the field of educational technology, educational wisdom and experience, and educational methods and skills are on the implicit level, educational tools and measures are on the explicit level. Educational technology’s implicit level is a kind of intangible, un-physical, but objective technology, which works in real social practices. It is as important as explicit physical technology, and it cannot be replaced by explicit physical technology. It is an intelligent technology, and its typical example is instructional design technology. Educational tools and measures on educational technology’s explicit level are physical. In the terms of IWBs’ application, explicit technology is IWB-based or ITV-based instructional interactive technology, which includes (1) information presenting technology, (2) information communicating (interacting) technology, (3) information processing technology, (4) information collaborating technology. In educational system, intelligent technology and physical technology interact and affect each other, which determines IWBs’ role in instructional activities. Thus, technology as first-level element, it includes four second-level elements, instructional design, instructional interactive technology, role of IWBs, device configuration level.

Students are the subjects of information processing, and the active constructor of information’s meaning. In informationized environment, students’ role in instructional activities has been reconsidered, it has been widely recognized that students are the subjects of educational activities and learning activities. Information technology-integrated curriculum enables students to actively and positively select and accept educators’ educational influence, rather than passively and negatively do. Moreover, students can actively gain learning resources according to their own cognitive needs, actively participate in learning activities according to their own and social needs or requirements, actively assimilate external educational influence using existed knowledge and experience, cognitive structure, and affective structure. Moreover, they can digest process and modify learning objects, and then construct their own learning objects. Thus, Information technology-integrated curriculum can obviously strengthen students’ subject consciousness, skills, and personality. In the terms of information technology-integrated curriculum’s influence on students’ subjectivity, there are four elements: (1) autonomy, (2) motility (3) creativity, and (4) interoperability.

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3. Research Design 3.1. Data Collecting Authors used stratified sampling method sampled 40 IWB-based instructional videos coming from different areas, educational levels, teacher attributes, subjects, application levels. Among them, 22.5% videos are from rural area schools, and 77.5% from urban ones; 37.5% are from elementary schools, and 62.5% from secondary ones; 52.5% are from science classes, and 47.5% from arts classes; 41.9% are from experienced teachers (teaching age >10), 16.2% are capable teachers (5

3.2. Research Method Under the guidance of empirical research paradigm and positivism paradigm, this research adopted content analysis (CA) method, video case analysis (VCA) method, and statistical analysis (SA) method, which are explained as below.

Table 3. Brief introduction of research method Method Brief intro of method Use in this study name

A method that systematically processes To extract instructional element data text, images and symbols, then from literature and teachers’ educational CA present resource’s meaning by gradual design text, to create this study’s concentration, and finally explains qualitative coding system. resource’s meaning. A quantitative or qualitative modeling To extract instructional element method on classroom video cases, it VCA codes in video cases according to has two kinds of systems: coding and coding system. semiotic. A quantitative research method based To comprehensively process on statistical mathematics. This study qualitative data, and help SA uses descriptive statistical analysis and researchers find out inherent rules deductive statistical analysis. in data.

4. Data Analysis and Discussion 4.1. Framework of IWB’s Instructional Application Levels Under the guidance of experience, based on grounded theory, authors used content analysis method to analyze literature, and then concluded a framework of IWB’s instructional application levels, which is shown in table 4.

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Table 4. Framework of IWB’s instructional application levels Instructional First-level application instructional Second-level instructional element level element Understand IWBs’ or ITV’s basic features, TK functions, and applications Understand IWBs’ or ITV’s frequent-used instructional tools on their own subjects, TCK and can use them to present instructional content in various ways Teacher Be capable of using IWBs or ITV to element TPK present, develop basic in-class practices, tutor individually on their own subjects. Have holistic ideas on integrating technology with specific subject, have ideas TPACK on integrating technology and learning Primary with curriculum and resources on their own application subjects. Be able to design instruction mixed by Instructional lecturing and tutoring. design Mostly mixed by information presenting Instructional technology and information communicating interactive technology Technology technology element Device IWBs/ITV and supplementary facilities configuration Electronic interactive instructional device as Role of IWB presenting tool and communicating tool Mostly to be instilled, have chances to Student element participate actively

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Understand IWBs’ or ITV’s major features TK and functions, as well as key applications Understand IWBs’ or ITV’s frequent- used instructional tools on their own subjects, and can use various supplemental TCK instructional tools to re-process, present and flexibly use resources. Teacher Can use IWBs or ITV to develop element TPK explorative learning, collaborative learning and test/students’ works’ presenting Have holistic ideas on integrating technology with specific subject, have primary knowledge and skills on integrating TPACK technology and learning with curriculum Intermediate and resources on their own subjects. application Be able to design instruction mixed by Instructional lecturing and tutoring. design Mostly mixed by information presenting Instructional technology, information communicating interactive technology, and information processing technology technology Technology element Device IWB/ITV and its supplemental devices configuration +intranet/internet Electronic interactive instructional device as resource-providing supporting platform and Role of IWB collaborative platform Active participants Student element

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Comprehensively understand IWBs’ or ITV’s major features, functions, limitations, TK as well as key applications Based on IWBs’ or ITV’s instructional tools on their own subjects, and their supplemental facilities, TCK teachers can use various resources and present information collaboratively from distance. Can use IWBs or ITV and supplemental facilities to develop explorative learning, empirical learning and task-driven learning TPK on their own subjects, and then evaluate Teacher students’ works generated by their new element knowledge. Have holistic ideas on integrating technology with specific subject; have knowledge and skills on integrating technology and learning with curriculum and resources on their own subjects; can Advanced TPACK think and develop an idea that students application can use technology understand, think and learn; have instructional strategies using technology to teach specific subject, and knowledge and skills to present. Be able to design instruction mixed by Instructional lecturing, tutoring and question-based design learning.

Mostly mixed by information presenting Instructional technology, information communicating interactive technology, information processing technology, Technology technology and information collaborative technology element IWB/ITV+ recording system+ professional Device internet supporting platform configuration Electronic interactive instructional device Role of IWB as collaborative platform and developing platform

Student element Can actively explore, find out, and construct

It can be inferred from table 4, in elementary and secondary schools, IWB’s application elements in instruction are comprised of 3 first-level elements, teacher, technology, and student; and 8 second-level elements, TK, TCK, TPK, TPACK, instructional design, instructional interactive

EITT 2013, Williamsburg, VA, USA, November, 2013 53 Proceedings of International Conference of Educational Innovation through Technology technology, device configuration, and the role of IWB. There are three levels of the application of IWB in classes, primary level, intermediate level and advanced level.

4.2. Subtract Characteristics of IWB’s Instructional Application Levels Firstly, after basic training of using table 4, framework of IWB’s instructional application levels, second, third and fourth authors were back to back to code sampled 40 class videos, and got 1520 codes. After calculating three authors’ codes’ consistency coefficient, it is 79.7%, which means, good.

Secondly, authors use SPSS 13.0 to conduct stepwise K-Means Cluster analysis on 1520 codes to gather initial Cluster centers.

Table 5. Initial cluster centers Cluster Center Cluster Coding Element 1 2 3 TK 3.00 1.00 3.00 TCK 2.00 2.00 2.00 TPK 3.00 2.00 6.00 TPACK 4.00 2.00 2.00 JXSJ 3.00 1.00 3.00 JXJH 2.00 1.00 3.00 SBPZ 3.00 1.00 1.00 JXZY 2.00 1.00 5.00 XSJS 2.00 6.00 6.00

It can be inferred from table 5 that there are 3 initial clusters, and their centers reflect 9 coding elements’ levels, but they don’t differentiate each other very much. Thus, better cluster centers need to be found via iterative operation. Table 6 reflects the change in 3 cluster centers.

Table 6. Stepwise iteration records Change in Cluster Centers Iteration 1 2 3

1 2.802 2.331 1.803 2 .000 .000 .000

We can infer from table 6 that after iteration 1, 3 cluster centers has changed 2.802, 2.331, and 1.803. After iteration 2, the change of 3 cluster centers is less than 0.01 separately, this meets cluster criterion. It can be seen from the final cluster analysis’ cluster member list that cluster 1 has 20 cases, cluster 2 has 18 cases, and cluster 3 has 2 cases.

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Table 7 provides SPSS 3 clusters’ final cluster center values. Table 8 presents distance matrix between clusters. Table 7. Final cluster centers Cluster Center Cluster Coding element 1 2 3 TK 2.30 1.78 3.00 TCK 2.45 2.39 2.50 TPK 2.60 2.11 5.50 TPACK 3.25 2.17 3.00 JXSJ 1.35 1.50 2.50 JXJH 1.55 1.22 3.00 SBPZ 1.20 1.00 1.50 JXZY 2.15 1.33 4.50 XSJS 2.50 3.94 5.00

Table 8. Distances between final cluster centers Cluster 1 2 3 1 2.148 4.925 2 2.148 5.407 3 4.925 5.407

It can be inferred from table 7 and 8 that the distance between 2 cases from cluster 3 and 18 cases from cluster 2 is the furthest. 2 cases from cluster 3 have larger values than cases from other clusters. 18 cases from cluster 2 have smaller values than cases from other clusters. Cases from cluster 1 are in the middle.

4.3. IWB’s Instructional Application Levels Firstly, it can be seen from stepwise clustering that there are 3 application levels in sampled 40 cases. Among them, 2 cases from cluster 3 are on the highest application level, that is, the advanced application level in table 4; 20 cases from cluster 1 are in the middle, which is, on the intermediate level in table 4; 18 cases from cluster 2 are on the lowest level, that is, on the primary level in table 4.

Secondly, in 2 cases from cluster 3, the highest application level, it can be seen from final cluster centers that the indicators of TPK, role of IWB, student's role are higher than corresponding indicators in other clusters, while the indicator of device configuration is as same as cluster 2, the lowest application level. It can be concluded that on IWB’s advanced application level, device configuration is not a major element, while TPK, role of IWB, student's role are very important elements, besides, instructional design and instructional interactive technology elements are also important.

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Thirdly, in 18 cases from cluster 2, the lowest application level, it can be seen from final cluster centers that the teachers have high-level student-centered idea, while their TK, instructional design, instructional interactive technology and understanding of IWB’s role have obvious gap with the highest level’s. Thus, to improve IWB’s instructional application levels, we should firstly help teachers improve their TK, develop their capability of instructional design, cultivate them to grasp various instructional interactive technology, and change their basic understanding of the role of IWB. This conclusion has undoubtedly provided point cut and direction for trainings of IWBs.

Fourthly, in 20 cases from cluster 1, the intermediate application level, it can be seen from final cluster centers that the indicators of TPK, instructional interactive technology, role of IWB, and student's role are obviously lower than the corresponding indicators on the advanced level, while the indicators of TPACK and device configuration are much higher than other levels’. This result has confirmed again that three elements TPK, role of IWB, student's role play a vital role in determining which IWB’s instructional application level is on, and only TPACK and device configuration can lead to high-quality instructional application of IWB with TPK, and the transforms of IWB’s role and student’s role.

5. Conclusion Based on the results of data analysis, authors can conclude that: the framework of IWB’s instructional application levels is a scaffold for guiding the use of IWB in elementary and secondary schools, improving instructional quality, developing towards advanced application level. In the framework, 44% elements are teacher-related, 44% are technology-related, and 12% are student- related. After empirical study, authors have found that there are three application levels of IWBs’ using in elementary and secondary schools: the primary level echoes IWB’s application level of visual aiding tools, the intermediate level echoes IWB’s application level of resource-based learning, and the advanced level echoes IWB’s application level of collaborative construction. On the visual aiding level, IWBs are only visual aiding tools in classes, and teachers’ teaching methods and instructional strategies cannot integrate with IWBs’ functions. On the resource-based learning level, IWBs are resource-managing and resource-processing platforms, and teachers’ teaching methods and instructional strategies begin to integrate with IWBs’ functions. On the collaborative construction level, IWBs are platforms for knowledge construction, and teachers’ teaching methods and instructional strategies begin to integrate deeply with IWBs’ functions.

Secondly, teachers are the key elements determining IWBs’ instructional application levels. This study has found that TPK, role of IWB, and instructional interactive technology have high positive relationship with IWBs’ instructional application levels. These three elements are directly related to teachers’ view on technology, and the application of teachers’ practical knowledge such as strategic knowledge, beliefs, and contextual knowledge. This study also found that the key elements determining IWBs’ instructional application level is not device configuration, or TK, but teachers’ understanding of IWBs’ vital values. After analyzing 40 cases from stratified sampling, it can be concluded that the application of IWB is on the beginning stage. Among 40 cases, only 5% are on the advanced level, 50% are on the intermediate level, and 45% are on the primary level. According to Someck’s research (Somekh, Haldane, Jones, Lewin, Steadman, Scrimshaw & Woodrow, 2007); teachers need to integrate their experience into instructional practices of IWBs. Although in this research, we haven’t found that TPACK has obvious relationship with

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IWBs’ instructional application levels, authors think that it probably because teachers’ TPACK is normally little.

Thirdly, the status of IWB’s instructional application levels and the existence of key elements mean that in the future, when we are developing IWB’s training courses for teachers, the starting point is cultivating IWB-based core values, the main goal is developing IWB-based strategic knowledge, and the scaffold is analyzing instructional cases with IWBs involved. To improve the current IWB’s application level, we can firstly use the framework of IWB’s instructional application levels to determine teachers’ application levels. And then, for primary-level teachers, we can firstly help them grasp basic TK and operational skills, and then help them learn more about IWBs’ functions in terms of TCK, TPK, TPACK, and teachers’ vital beliefs towards IWBs. For intermediate-level teachers, the training should emphasize on improving teachers’ TPK, instructional interaction techniques, understanding of IWBs’ role and students’ role, and their own application levels. For advanced-level teachers, the training should focus on improving teachers’ innovative application abilities with TPACK as the core, and innovative design on classroom interactive activities based on IWBs, to promote the transfer of teachers’ practical experience and instructional wit to high-quality and high-effect classroom instructional efficiency.

Fourthly, this study has some limitations. In future research, authors should test and modify the framework of IWB’s instructional application levels in a broader scope, and then gradually develop it into an evaluation tool with good validity and credibility. Meanwhile, authors also need to elaborately perfect the design plans of stratified trainings, and gradually form a system of teacher training courses for those teachers on three application levels.

References Anderson, J. (Ed.). (2002). Information and communication technology in education. Unesco. Angeli, C., & Valanides, N. (2005). Preservice elementary teachers as information and communication technology designers: an instructional systems design model based on an expanded view of pedagogical content knowledge. Journal of Computer Assisted Learning, 21(4), 292-302. Annetta, L. A., & Minogue, J. (2004). The Effect Teaching Experience Has on Perceived Effectiveness of Interactive Television as a Distance Education Model for Elementary School Science Teacher’s Professional Development: Another Digital Divide?. Journal of Science Education and Technology, 13(4), 485-494. Aseei, A. & Majed, A. J. (2012). Teachers’ Attitudes Toward Using Interactive White Boards in the Teaching and Learning Process in Jordan. International Journal of Instructional Media, 39(4), 319-330. Becta. (2004). Getting the most from your interactive whiteboard: a guide for secondary school: effects on pedagogy Research Bursary Reports. Coventry: Becta. Betcher, C., & Leicester, M. (2009). The interactive whiteboard revolution: Teaching with IWBs. ACER Press. Chai, C. S., Koh, J. H. L., & Tsai, C. C. (2011). Exploring the factor structure of the constructs of technological, pedagogical, content knowledge (TPACK). Chen, Q., & Chen, L. (2007). Current status and trend of IWBs’ application in elementary and secondary schools. China Modern Educational Equipment, (11), 5-9. De Vita, M., Verschaffel, L., & Elen, J. (2012). Acceptance of interactive whiteboards by Italian

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mathematics teachers. Educational Research, 3(7), 553-565. Dong, Z. (2005). Instructional basic elements and their mode of operation. Theory and Practice of Education, (7), 52-55. Glaser, B. G., & Strauss, A. L. (2009). The discovery of grounded theory: Strategies for qualitative research. Transaction Books. Glover, D., & Miller, D. (2004). Leadership Implications of Using Interactive Whiteboards: Linking Technology and Pedagogy in the Management of Change. Management in Education, 18(5), 27-30. Groff, J., & Mouza, C. (2008). A framework for addressing challenges to classroom technology use. AACE Journal, 16(1), 21-46. Harris, J., Mishra, P., & Koehler, M. (2009). Teachers’ technological pedagogical content knowledge and learning activity types: Curriculum-based technology integration reframed. Journal of Research on Technology in Education, 41(4), 393-416. He, K. (2012). TPACK: New development on methods of American “Integration of information technology and curriculum”. E-education Research, (5), 5-10. He, K. (2012). TPACK: New development on methods of American “Integration of information technology and curriculum. E-education Research, (6), 47-56. Koehler, M. J., Mishra, P., & Yahya, K. (2007). Tracing the development of teacher knowledge in a design seminar: Integrating content, pedagogy and technology. Computers & Education, 49(3), 740-762. Levin, T., & Wadmany, R. (2008). Teachers’ views on factors affecting effective integration of information technology in the classroom: Developmental scenery. Journal of Technology and Teacher Education, 16(2), 233-263. Ma, N. & Yu, S. (2002). Levels of the integration of information technology and curriculum. China Educational Technology, (1), 9-13. Miller, D., Averis, D., Door, V., & Glover, D. (2005). How can the use of an interactive whiteboard enhance the nature of teaching and learning in secondary mathematics and modern foreign languages? Report made to the British Educational Communications and Technology Agency. Parigi, L. (2011). About IWB: teachers’ attitudes, beliefs, expectations, ANSA (National Agency for Development of School Autonomy). Retrieved from: http://www.scuoladigitale.it/index. php?act=read&id_cnt=20201 Sheng, Q. (1990). Systematic analysis of instructional process: model of interplayed seven elements (A). Foreign Educational Resources, (3), 12-20. Somekh, B., Haldane, M., Jones, K., Lewin, C., Steadman, S., Scrimshaw, P., & Woodrow, D. (2007). Evaluation of the primary schools whiteboard expansion project. London: Report to the Department for Education and Skills. Tian, H. (1993). Discussion on the system, elements and structure of an instructional environment. Instructional Review,(3), 22-25. Wang, L. (2009). Interactive Whiteboards and instructional innovation. Beijing: Higher Education Press. Yu, W. (2007). Basic elements of effective classroom teaching. Exploring Education Development, (7), 38-42.

58 EITT 2013, Williamsburg, VA, USA, November, 2013 Wei, S . (2013). Learning analytics: mining the value of education data in the era of big data. Proceedings of International Conference of Educational Innovation through Technology, 59-68.

Learning Analytics: Mining the Value of Education Data in the Era of Big Data

Shunping Wei The Open University of China Email: [email protected]

Abstract: Currently, the era of big data has arrived and the field of education has also accumulated huge amounts of data. In the field of education, more and more software systems have been deployed and massive data on learner profiles and learning process have been stored in these systems. How could we make the best use of the massive educational data and transfer the data into useful information and knowledge in order to reach scientific educational decisions and optimize instruction? These are the concerns of educators and learners. Learning analytics could be employed for realizing the value of learning process data. The author introduces current local and international studies of learning analytics, sums up the key technologies and analytical model of learning analytics, and demonstrates application process of learning analytics in analyzing online learning process with three examples from different user perspectives of managers, tutors and learners.

Keywords: era of big data, education data, learning analytics, key technologies, analytical model

1. Introduction The term ‘big data’, which was mentioned increasingly in 2012, is used to describe and define huge amounts of data generated in the era of information explosion, and to name associated technology development and innovation (Huang, 2012). The research results of the International Data Corporation (IDC) indicate that the amount of data generated globally in 2008 was 0.49ZB (1ZB=270bit), in 2009 it was 0.8 ZB, in 2010 it grew to 1.2ZB, and in 2011 it reached as high as 1.82ZB, equivalent of data of above 200GB (1GB=230bit) generated each person globally. It is McKinsey, the world-renowned consulting firmthat first proposed the era of “big data”, “Data have swept into every industry and business function and are now an important factor of production, alongside labor and capital. The use of big data will underpin new waves of productivity growth and consumer surplus. ”

In the field of education, “ learning analytics” was included in the NMC Horizon Report: 2013 Higher Education Edition as one of the emerging technologies that will influence learning, teaching and innovation of the field of higher education in two to three years. It was stated in the report, “Learning analytics, in many ways, is ‘big data,’ applied to education” and “ Learning analytics is the field associated with deciphering trends and patterns from educational big data”. It was predicted that “big data and learning analytics” will become the mainstream technology in two to three years(Johnson, Adams, Cummins, Estrada, Freeman, & Ludgate, 2013).

2. Literature Review In the First International Conference on Learning Analytics and Knowledge, it was agreed that learning analytics refers to measurement, collection, analysis and report of data on students EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 59 Proceedings of International Conference of Educational Innovation through Technology

and their learning environment for understanding and optimizing learning and its environment. The NMC Horizon Report: 2012 Higher Education Edition also gave the similar definition, “learning analytics refers to the interpretation of a wide range of data produced by and gathered on behalf of students in order to assess academic progress, predict future performance, and spot potential issues.”(Johnson, Adams, & Cummins, 2012) These definitions indicate that targets of learning analytics are students and their learning environment and its purpose is to assess students, identify potential problems, understand and optimize learning based on huge amounts of data.

Before the advent of the concept of “learning analytics”, the associated technology, tools and applications have been developed. The“intelligent tutoring system” and “artificial intelligence system” born in higher education in 2004 set off a craze of research on “education data mining”, and contributed to the birth of learning analytics that focuses on learner behavior (Baepler,& Murdoch, 2010). Based on the analysis of more than 10 years of research on education data mining, Romero & Ventura (2007) summarized the following methods of education data mining: statistical analysis and visualization, clustering (clustering, outlier analysis), forecast (decision trees, regression analysis, time-series analysis), relationship mining (association rule mining, sequential pattern mining, relevant mining) and text mining. In addition, with the growing popularity of e-learning and learning management system, data mining method has been applied to learning management systems, and initiated research on analyzing learner behavior employing network analysis technology. The log analysis of Moodle by Romero, et al (2005) is such a good model . Data of learner behavior is recorded in the learning management system, real-time data report is then generated through aggregation, classification, visualization, and analysis of association rules and other operations, or a predictive model is generated using the norm reflected from the behavior data. With further development of research and practice on learning analytics, besides the method of data mining, methods that originally belong to the field of social sciences such as social network analysis, discourse analysis, content analysis have been successfully applied as the key technologies of learning analytics. Behavior analysis on teacher-student interaction is one of such typical applications of these methods.

Studies of several researchers have proved that learning analytics is of great value for students, teachers, managers, researchers and technology developers(Johnson, Adams, & Cummins, 2012; Chen, Heritage, & Lee, 2010; Gu, Zhang, & Cai, 2012). In addition, learning analytics will be promising in the field ofonline higher education helping monitor learning process and assure quality of education. Development of learning analytics depends on systematic and structured mass data, while the online higher education, due to its comprehensive use of learning management system and education management information system, has accumulated a large number of systematic and structured data. Employing learning analytics, survey on the status quo of learners learning online in online higher education including the main features of learners, characteristics of online learning behavior, factors influencing learning behavior and related learning outcomes, will contribute to mastering the rules of adult online learning in order to optimize the learning process, improve learning outcomes and enhance the quality of education.

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3. Key Technologies of Learning Analytics and Modes of Analysis The key technologies of learning analytics involve content analysis, discourse analysis, social network analysis, system modeling, and a series of data mining methods of statistical analysis and visualization, clustering, forecasting, relationship mining and text mining.

Students’ learning is the natural object of learning analytics. Addressing different types of problems, applications of learning analytics involve three types of situations, i.e. analysis on characteristics of learners answering the question of “who are learning”, analysis on learning process answering the question of “what to learn and how to learn”, and analysis on learning outcomes answering the question of “what is the result of learning”. Thus three modes of learning analytics will be developed in order to provide a reference to similar mining tasks.

The mode of learning analytics is composed of three elements of “processes of learning analytics”, “tools and algorithms”, and “data and information”(Ge, Zhang, & Wei, 2012). “Processes of learning analytics” includes such stages as data collection, data pre-processing, analysis, forecasting and application. The stages differ according to the different application contexts; “tools and algorithms” provides support for “processes of learning analytics”, and is selected from “the key technologies of learning analytics and major tools”; “data and information” includes both input data to the “tools and algorithms” and output information or knowledge from the “tools and algorithms”.

4. Application of Learning Analytics Based on User Prospectives As above mentioned, learning analytics is of unique value for online learning. Taking the learning management system of the Open University of China as an example, the paper looks into application of learning analytics through user perspectives of managers, tutors and learners based on log data of the learning management system and data of education management information system on enrollment, curriculum and teachers.

In this paper, a training program for practitioners from online education is chosen as the study sample to show the application of learning analytics in the Open University of China. The training program has been started in 2009 and is based on Moodle LMS. Mass data of training process has been stored in the Moodle database.

4.1. Application of Learning Analytics from the Perspectives of Managers As teaching managers, they generally use learning analytics to understand the overall teaching of an educational institution such as the number of teachers and students, quantity of students’ various activities and its average, quantity of various activities of teachers and its average. “Learning analytics and visualization” is the frequently used method.

Here is an example for the manager of online education practitioners training program to use learning analytics. The training manager can be aware of training situations of each training class by learners’ engaged time and all kinds of learning performance such as browsing learning resources, posting messages and replying in the forum, submitting assignments. In the first semester of 2012, there are six training classes with 132 learners. Table 1 shows the basic information about these six training classes.

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Table 1. Bacis information of six training classes Id Class Name Starting date Learner Number 57 Online course design(C57) 2012-04-09 12 58 Learner support service(C58) 2012-04-09 17 59 Online learning tutoring(C59) 2012-04-09 20 61 Learner support service(C61) 2012-04-16 40 66 Online learning tutoring(C66) 2012-04-09 20 75 Learner support service(C75) 2012-04-16 23

The training manager could create a data list about training situation of each class by gathering and analyzing data of learners’ engaged time and all kinds of learning performance such as browsing learning resources, posting messages and replying in the forum, submiting assignments. The result is shown in table 2.

Table 2. Data list of training situation Training Class

Online Learner Online Learner Online Learner course support learning support learning support design service tutoring service tutoring service (C57) (C58) (C59) (C61) (C66) (C75) Engaged days per learner 35 27 30 23 27 33 Browsing resource 44 34 41 53 33 47 frequency per learner Posting messages number 27 12 16 18 18 26 per learner Interaction degree among 33 23 34 38 76 54 tutor and learner% Assignment finishing rate by 75 97 84 59 58 48 learner% Assignment correction rate 0 0 99 49 98 100 by tutor%

According to table 2, a radar map as figure 1 could be made.In the radar map, several classes such as C59, C66, C75 cover larger area. These classes could be judged as well-done training classes. On the contrary, several classes such as C58,C61 cover small area. These classes could be judged as not well-done training classes. Among the training classes for the same course “Learner Support Service” such as C58, C61, C75, C75 has been done a better job than C58, C61.

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Figure 1 a radar map for the performance of each traning class

According to the data shown as table 1 and figure 1,training manager could accurately evaluate the performance of each trainining class and then reasonably make Rewards and punishments measures.

4.2. Application of Learning Analytics from the Perspectives of Tutors Regarding tutors, the analysis was conducted based on courses they tutor including statistical description of learners’ online learning performance (inputs of learning time, frequencies of learning activities, browsing of learning resources, test scores and etc.), analysis of learners’ path of autonomous learning, tutor-learner interaction, analysis of various factors that affect adult learners’ performance in online learning, and so on. Uses of learning analytics technology will be flexible such as content analysis of threads of tutors and learners, social network analysis of interaction between tutors and learners as well as a series of data mining methods such as statistical analysis and visualization, clustering, association rules and sequential pattern mining.

Here is an example based on “online learning tutoring ” training class happening from May 2011 to July 2011. The tutor of the training class uses SQL SERVER Analysis Service to map the learning route of learners.

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During the training process, tutor and learners mainly use forum, wiki, assignment, resource, user modules in the Moodle LMS. The mdl_log table in Moodle LMS records each modules’ action of each user such browsing a document, posting a message, submitting an assignment, etc.. Based on mdl_log table (records example show as table 3), the author used “Microsoft sequence analysis and clustering analysis algorithm” in SSAS to map the learning route of learners and the mining results are shown as table 4 and figure 2.

Table 3. Records example in mdl_log Visiting id User id Visiting date module action 255674 397 2011-3-30 course view 255675 397 2011-3-30 forum view forum 255835 403 2011-3-31 course view 255851 398 2011-3-31 course view 255852 398 2011-3-31 course recent

Table 4. Jumping probability between two modules Source module Object module Jumping probability [begin] forum 54.971% [begin] resource 15.789% [begin] assignment 14.620% [begin] user 8.772% [begin] wiki 5.848% forum forum 48.498% wiki wiki 8.747% resource resource 5.827% assignment assignment 4.265% resource forum 3.901% forum resource 3.477% forum assignment 3.089% assignment forum 2.459% user user 2.459% user forum 2.108% forum user 2.096% wiki forum 2.060% forum wiki 1.854% assignment resource 1.187% resource wiki 1.030% assignment wiki 1.018% wiki resource 0.981% resource assignment 0.812% wiki assignment 0.812%

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As shown in table 3, when learner logs in the Moodle LMS, he or she would probably visit module “forum”(the probability is 54.971%).

Figure 2. Jumping situation between different modules.

As shown in table 3 and figure 1, all the jumping probability from user, resource,assignment,wiki to forum are high, which shows that module “forum” is learner activities center and is also an important intermediary module. Besides, module “resource” is also an important module which supports the activities happening in the forum and assignment module. When a learner logs in the Moodle LMS, he or she visits resource module with the probability of 15.789%. the probability of jumping combination such as “forumresrouce”, “assignmentresource” is relatively 6% and 13%, which are higher.

4.3. Application of Learning Analytics from the Perspectives of Learners As to learners, understanding their own behavior and relationship with others will be the main purpose of the learning analytics. Through the "learner activity reports" function of the learning management system, the learner can learn his performance and behavior in each chapter of the course and the frequency distribution along the time dimension, and be aware of most frequently accessed modules. Learners’ activities in the learning management system is not isolated. The learner would also like to know his relationship with the tutor and other students. Such relationships could be non-oriented such as common focus on certain resource, while the relationships could be oriented such as relationship between replying and being replied. The presentation of such relationships can be done through social network analysis. For example, when a learner completes a course, he would like to learn about replying and being replied in the forum. Then a network analysis of learner-centered teacher-student interaction can be conducted.

Here is an example based on “online learning tutoring ” training class happening from May 2011 to July 2011. The learner of the training class uses UCINET which is a kind of social network

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analysis tool to map the interactive network among tutor and learners and understand himself or herself’s position in the training class.

Based on the records of posting messages and replying messages(there are 743 messages posted by 23 learners and 1 tutor), learner uses “netdraw” function in the UCINET to map the interactive network among tutor and learners. The result is show as figure 3.

Figure 3. the interactive network among tutor and learners.

Shown as figure 3, learner “406”(red diamond shape) interacted with many other learners and plays an important role in the training class.

5. Conclusion In 21st century, with the advancement of informatization process in the field of education, especially vigorous promotion of digital campus construction and online higher education, the field of education has deployed a number of learning management systems where massive data on learner profiles and learning process have been stored. How could we make the best use of the massive educational data and transfer the data into useful information and knowledge in order to reach scientific educational decisions and optimize instruction? How shall we avoid “being drown in a sea of data but enduring hunger of information”? These are the concerns of educators and learners. In this case, learning analytics, which is dedicated to measurement, collection, analysis and reporting of data on students and their learning environment for understanding and optimizing learning environment, contributes to giving full play to the value of learning process data so that the data could become an important basis for prudent decision-making and process optimization.

66 EITT 2013, Williamsburg, VA, USA, November, 2013 Learning Analytics: Mining the Value of Education Data in the Era of Big Data

For the future, the author proposes three aspects which should be further promoted: (1) learning analytics involves a variety of methods and tools. They need to be collated and compared in order to find different methods and applicable occasions for tools; (2) there are various issues to be addressed by application of learning analytical. Typical applications of learning analytics need to be sorted out so as to sum up a number of typical tasks and integrate certain methods and tools of learning analytics for developing the mode of learning analytics; (3) the application fields of learning analytics need to be further expanded, such as the entire field of online higher education, so that a greater value will be added serving both micro decision-making and macro decision- making.

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References Baepler, P. & Murdoch, C. J. (2010). Academic analytics and data mining in higher education. International Journal for the Scholarship of Teaching and Learning, 4(2), 170-178. Chen. E., Heritage, M., & Lee, J. (2010) Identifying and monitoring students’ learning needs with technology. Journal of Education for Students Placed at Risk, 3,309-332. Ge, D., Zhang, S., & Wei, S. (2012). Mining of educaiton data: methods and applications. Beijing, China: Educational Science Press. Gu, X., Zhang, J., & Cai, H. (2012). Leanrning analysis: emerging data technology. Distace Education Journal, (1), 18-25. Huang, H. (2012). Today’s focus: arrival of big data era. Ban Yue Tan (China Comment), (17). Johnson, L., Adams, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2013). NMC horizon report: 2013 higher education edition. Austin, Texas: The New Media Consortium. Johnson, L., Adams, S., & Cummins, M. (2012). The NMC horizon report: 2012 higher education edition. Austin, Texas: The New Media Consortium. Romero, C. & Ventura, S. (2007) Educational data mining: a survey from 1995 to 2005. Expert Systems with Applications, 33, 125-146. Romero, C., Ventura, S., & Garcia, E. (2005). Data mining in course management systems: Moodle case study and tutorial. Computers & Education, 51(1), 368–384.

68 EITT 2013, Williamsburg, VA, USA, November, 2013 Yang, J., Han, X., Zhou, Q., & Ma, J. (2013). A solution to guarantee undergraduate thesis quality by information technology. Proceedings of International Conference of Educational Innovation through Technology, 69-76.

A Solution to Guarantee Undergraduate Thesis Quality

by Information Technology

Juan Yang, Xibin Han, Qian Zhou, Jing Ma Tsinghua University Email: {Juan-yang, hanxb, zhouqian, jing-ma12}@tsinghua.edu.cn

Abstract: Thesis is recognized as the opportunity for students near the graduation to learn to conduct research work independently and the assessment tool for university to evaluate students. Supervisor is regarded as the best facilitate to guide the students through the lonely journey. However, overloaded supervisors cannot provide sufficient support to students. Based on the analysis on the thesis regulations of nine top- universities in China, and the literature investigation, students’ perception on good supervising and approaches guiding students through the progress step by step are studied. The possibility of the application of information technology in every type of approaches is analyzed and an information-technology supported solution is proposed.

Keywords Undergraduate thesis, supervising, supervisor, quality, information technology

1. Introduction In recent years, with the sharp college expansion, the whole higher education in China is filled with the anxiety of undergraduate thesis quality declining. To increase the thesis quality is the urgent affairs of higher education institutions and also the common concern of policy maker and researchers. Ministry of Education (2004) issued notification to strengthen the undergraduate thesis quality management.

On the premise that stage examinations can guarantee thesis quality, information technology is highly evaluated by researchers and higher education institutions since information system can execute stage examinations through forcing and auditing supervisors’ and supervisee’s timely submission of stage reports during the thesis process. Therefore, thesis stage management system is widely designed and applied in the higher education institutes in China (Jin etc, 2003; Zhu, 2006; Pan, et al., 2009).

For most students thesis is the first time for them to undertake a large-scale long-term (about 12-18weeks) research work independently (Rowley, 2000; Cook, 1980; Armstrong, 1983; Todd, 2006). Supervisors’ support is the best facilitate to guide the students through the lonely journey. In fact, in the era of mass higher education, even stage examinations cannot force those overloaded supervisors to provide as much support as supervisees wish. It is impossible to guarantee thesis quality without enough supervising.

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This paper tried to find the proper applications of information technology in the thesis process to aid supervisors to provide sufficient supervising for students and achieve the quality thesis.

This paper will conduct investigations on the following questions (1) How to define quality thesis and how to guarantee quality thesis?

Based on the investigation on the thesis regulations of nine top-class universities in China, the whole thesis process is decomposed into a series of steps including topic selection, title defining, proposal, methodology choice, research carry-out (data collection, design, and experiment), thesis writing and oral presentation. The quality thesis is transformed into a set of approaches in three categories: knowledge, skills and ability (Zuber-Skerritt & Fletcher, 2007). The specific approaches of every step are analyzed. After advancing step by step, a student can finish with a quality thesis.

(2) How can students go through the whole process successfully? When and how can information technology help to provide a good supervising?

Based on the literature investigation, students’ perceptions on good supervising and approaches to achieve good supervising are analyzed in every step. The possibility of applying information technology to save supervisors’ time in those approaches is studied.

(3) The whole solution to provide a good supervising using information technology.

2. Literature Review In China, reasons caused thesis quality declining were investigated and illustrated as insufficient supervising from tutors(Zhao etc, 2011;Zhang etc, 2012;Luo etc,2012,Liu etc,2012) resulted by increasing student population and overloaded teaching resource students’ negative attitudes caused by restricted topic selection(Xiang etc,2008) improper topic selection(Liao etc,1005) and the big pressure of job hunting or postgraduate entrance examination(Luo etc,2012). Strategies to increase the thesis quality were proposed, including improving students’ understanding of the importance of undergraduate thesis in the ability cultivation(Liu etc,2012), providing two-way topic choice(Ruan ,2012;Zhou 2008) and proposing career related or practical topic(Zhao,2011) in order to stimulate students’ initiative and optimizing the supervising structure in order to provide more guidance for students with the limited amount of teachers(Li,2011;Mao & Han, 2006). The most important measure mentioned by many researchers is to stress the whole process management. It is believed that process management is most effective way to guarantee thesis quality by examining and regulating both supervisors’ and students’ performance. Information technology is highly recommend in the implementation of whole process management(Ruan,2012; Jin etc,2003;Zhu,1006; Li,2007; Pan etc,2009).

However, using information technology in the whole process management in order to guarantee quality thesis is administration perspective. It focuses on examination instead of support. Sufficient guidance is the key to guarantee the quality of whole process and the product (Malcolm, 2011). The requirements of both supervisors and supervisees are ignored in those

70 EITT 2013, Williamsburg, VA, USA, November, 2013 A Solution to Guarantee Undergraduate Thesis Quality by Information Technology researches. From supervisees’ perspective, they need supervisors’ timely guidance in the key steps. On the other hand, from those heavy loaded supervisors’ perspective, they need support to provide sufficient guidance for supervisees. This research tried to find a solution for this seemingly irreconcilable problem.

3. Analysis on the Handbooks Question 1. What is quality thesis and how to achieve quality thesis? Dissertation module guidelines/handbooks from nine initial universities of 985 Project were reviewed. Handbooks are the manuals for both supervisor and supervisee undertaking a dissertation with the ultimate aim of guaranteeing completion and submission of good work (Harrison & Whalley, 2008).

The theme of the handbooks is analyzed (see table 1). The aims of undergraduate thesis are illustrated by all universities and those are recognized as the ultimate rules to assess the quality of thesis.

Table 1. Common themes in dissertation handbooks Theme Num of handbooks containing the theme (sample size=9) Aims 9 Process 9 topic selection topic selection 5 title defining 1 proposal 6 mid-term report methodology choice 3 research carry-out 2 (data collection, design, experiment) thesis writing 9 presentation thesis assessment 9 oral presentation 9 requirement for supervisor 9 Assessment method and standard 6

The process is described in detail by all universities. In the former research in China, for the convenience of management, thesis process is usually cut into three stages: topic selection, mid- term report and oral presentation. In this research, it is further cut into eight stages according to actual process of the thesis. From the data of table 1, it seems that the universities attach importance to the outcome of the process since all the handbooks contain the theme of thesis writing, thesis writing and oral presentation while fewer handbooks address those formative stages such as topic selection, title defining, proposal, methodology choice and research carry-out.

On the other hand, all the handbooks require that supervisors should provide regular guidance and timely feedback in the whole process. From this point, supervisors’ sufficient guidance is crucial to the thesis quality.

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Majority handbooks contain the method and standard assess the thesis. Aims mentioned in the handbooks are checked in the assessment. As table 2 showed, handbooks define the tasks teachers and students should undertake. Those tasks can be translated into different approaches which can be classified into three categories, including cognitive, affective and skill development oriented approaches (Zuber-Skerritt & Fletcher 2007).

Table 2. Approaches on the stages Stage tasks defined in the handbooks Approaches to fulfill Approach categories * the task S1 Teacher proposed topic choices, Information cognitive affective Student proposed own topic or collection chose topic (two-way choice) bibliographic skill Teacher provided a reference list for database students. literature review skill

S2 Teacher helped student define the brain storm, mind skill title map S3 Student wrote a proposal including Writing cognitive the literature review creative skill research point and research plan etc S4 Student chose the proper methodology choice cognitive methodology under the guidance of skill teacher.

S5 Student carried out research. data collection, cognitive Teacher provided regular meeting design, experiment, skill with student and timely feedback to data analysis student’s problem. S6 Student wrote first draft, verified cognition on the Cognitive draft and final thesis. format Teacher read the draft and provided writing skill feedback. S7 Committee members read the thesis cognition on cognitive and marked it regulation assessment skill S8 Student made an oral presentation Oral presentation Skill and the committee marked it. Knowledge on the research topic *S1- topic selection; S2- title defining; S3- proposal; S4- methodology choice;S5- research carry- out; S6-thesis writing;S7- thesis assessment; S8- oral presentation

72 EITT 2013, Williamsburg, VA, USA, November, 2013 A Solution to Guarantee Undergraduate Thesis Quality by Information Technology

The aim of undergraduate thesis is to improve students’ capabilities in investigation, information collection, literature review, methodology choice, integration of theory and application, research, thesis writing and oral presentation. Thesis quality should be assessed from those aspects. Supervisee can achieve ultimate good work if he/she takes approach stage by stage successfully.

In order to make the process move forward smoothly, supervisors should provide proper support in different stage. In this paper, the application of information technology would be analyzed in different stages in order to help supervisors provide supervising.

Question2. How can students go through the whole process successfully? When and how can information technology help to provide a good supervising? Ideally, students will turn to supervisors for help when they get problems during the process of undergraduate thesis. Supervisors’ timely help is the key for students going through the whole process successfully.

However, undergraduate thesis is the independent work of students and the role of supervisors is to provide general guidance and help with the dissertation journey(Heinze 2009). It is impossible for overloaded supervisors to provide guidance whenever students need help. Supervisors should make it clear when they should provide guidance and when students should find out solution by themselves. It makes the border clear with the help of the approach categories. It is relatively easy for students undertake cognitive approach independently. On the other hand, supervisors should provide proper guidance in the skill development oriented approaches and provide direct or indirect support for affective approaches.

Information technology can be applied to decrease supervisors load comprehensively. By handing out reference list through information technology, supervisors can help students undertake cognitive approaches initiatively. Through the demonstration of case by information technology, students can go through skill development oriented approaches smoothly. And with the help of information technology, students can find peer support or more expert support facing the affective approaches. With the help of information technology, good supervising can be provided to students even in the situations of limited supervisor number.

4. Solution A whole solution to provide a good supervising using information technology is proposed in this paper including two parts: one is the repository-based supporting system to deal with the cognitive approaches and partial skill approaches (see figure 1 on the next page) and the other is multidimensional supervising structure (see figure 2 on the next page) to deal with the affective and partial skill approaches.

For most students, undergraduate thesis is the first time to conduct a complex project independently. Advice provided by graduates to later students is to “start early” and “do as much as you can in the vocation” (Harrison 2008). The application of repository-based platform makes it possible that all the students can contact with the undergraduate thesis at the very early stage.

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Figure 1. Repository supported supervising platform

Figure 2. Information technology supported Multidimensional Supervising Structure

Expert repository is established to aid the two-way topic selection. Topic choice is the start and crucial in the process of thesis for student. On the other hand, it is hard for a teacher to supervise a student in a totally unfamiliar topic. Therefore, the two-way topic selection means the two- way selection of teacher’s research interest and student motivation. Good choice means a good start and it helps to mach student’s initiative and teacher’s guidance. Expert repository publishes the information of teacher’s research interest, former guidance experience, former topics, future interested topics and the requirements for supervisee. Students can figure out suitable supervisors and the gap between the supervisor demand and their own status by upper information. As a result, students can make proper supervisor choice and can start to fill the gap early in order to prepare for the thesis.

The data of expert repository includes two parts, the initial input data and in-progress data. Teachers should publish research interests, interested topics and requirements for supervisee at the beginning. Then the progress data including the guidance experience and former topics will enter the database automatically at the summary stage. With the operation of the platform, teachers’ information will become more and more comprehensive. It can help students get through understanding of future supervisors and help them to make more rational choice.

During the process, students’ cognition approaches and partial skill development oriented approaches can be supported by reference repository and case repository. Guidelines, handbooks, topic-related reference, and skill-related training reference can be published in the reference repository. With the aid of the repository, supervisees can get most of the cognitive knowledge including topic related knowledge and methodology knowledge, and also can get the reference on the skill training such as mind-map, brain storm, writing skill and oral presentation skill.

74 EITT 2013, Williamsburg, VA, USA, November, 2013 A Solution to Guarantee Undergraduate Thesis Quality by Information Technology

Case repository is the makeup of reference repository. At the summary stage, the high mark thesis will enter the case repository. Through vivid example, students learn what the qualified thesis is and learn how to choose the proper topic, write a proposal, execute research correctly, write a qualified thesis and make clear oral presentation. Guided by these examples, students can learn how to undertake undergraduate thesis independently and how to produce a qualified product.

Repository can relatively decrease the demand for supervisor. However, in the affective and skill development approaches, students still need supervisors’ support. The multidimensional supervising structure is proposed to utilize peer support, supervisor supervision and expert support comprehensively.

The whole undergraduate thesis process is a lonely journey for most students since almost all the handbooks clearly noted that student should undertake a topic independently. It seems that supervisor’s supervision is the only accompany in the whole progress. It is impossible for supervisor to provide timely support whenever student gets affective problems or skill problems. In fact, undergraduate thesis also stresses team work sprit and social skill. With the aid of social network, students can find out the peer researchers and experts who are conducting the similar or related researches. Conversations with the peer researchers and experts can help to improve the understanding of thesis. Students not only can get specific support when they get topic-related problems and also they can find affective support when they get frustrated or anxious facing the urge achievement within a specified time limit.

5. Conclusion This paper tried to propose a whole solution to provide a good supervising using information technology in the situation of limited number of supervisors. This paper investigated undergraduate thesis guidelines/handbooks of nine top universities in China and cut the process into eight stages. It analyzed task requirements for both supervisor and supervisee and translated them into three categories of approaches. Repository-based platform is proposed to support students made proper topic choice and further purchase an independent research through providing comprehensive expert information, reference and case samples. In order to cultivate students’ team work spirit and social skill and to meet the affective requirement, the multidimensional supervising structure is proposed.

References Armstrong, M. & Shanker,V.(1983).The supervision of undergraduate research: Student perceptions of the supervisor role. Studies in Higher Education, 8(2), 177-183. Cook, M.C.F. (1980).The Role of the Academic Supervisor for Undergraduate Dissertations Sci- ence and Science-Related Subjects. Studies in Higher Education, 173-185. Harrison, M.E. & Whalley W.B. (2008). Undertaking a Dissertation from Start to Finish: The Pro- cess and Product. Journal of Geography in Higher Education, 32(3), 401-418. Heinze, A. & Heinze,B.( 2009).Blended e-learning skeleton of conversation: Improving formative assessment in undergraduate dissertation supervision. British Journal of Educational Technol- ogy, 40(2), 294-294. Higher Education Department of the Ministry of Education in China, the Notification to Strength-

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en the Management of Undergraduate Research (thesis), [2004] No.14 Jin, X., Xu,Z., et al.( 2003) .Development and research of degree thesis management system. Jour- nal of Tianjin Institute of Urban Construction, 9(3). Li, B. (2011). Evaluation of graduation design’s organization structure based on entropy theory. In International Conference on Management Science and Industrial Engineering (MSIE). Har- bin IEEE. Liao, Z., Liu,Y.& Sun, Y.( 2005). Analysis and Countermeasures on Affecting Factors of the Di- ploma Project’s Quality of the Undergraduates, Journal of EEE ,27(1),110-113 Liu, L. & Zhang. C. (2013). The Strategy of Improving the Quality of Undergraduate Graduation Design (Thesis). In Proceedings of the 2012 International Conference on Cybernetics and Informatics Lecture Notes in Electrical Engineering, 163, 187-193 2012. Luo, H. & Jiang.W. (2012). Teaching reform and discussion on improving the quality of graduation design. In The 7th International Conference on Computer Science & Education: IEEE. Maio, X.& Han, L.(2006). Practice and Exploration to Improve the Quality of Final Year Projects of the Undergraduates, Journal of Chongqing University( Social Science Edition) 112(16),133- 136 Malcolm, M. (2012) .Examining the implications of learner and supervisor perceptions of undergraduate dissertation research in Business and Management. Teaching in Higher Education. 17(5), 565-576. Pan, H., Wei, W., Song T. et al. (2009). Design and application of college undergraduate thesis whole-process management system. China Electric Power Education. (113). Rowley, J. (2000) .Thirteen tips for successful supervision of undergraduate dissertations, Staff and Educational Development Association, 1:p14-15. Ruan, G., Li, Z. & J. Wang (2012). The design and implementation of intelligent management system of undergraduate graduation thesis. In 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet). 2012: IEEE. Todd, M.J., K. Smith& Bannister,P.(2006) .Supervising a social science undergraduate dissertation: staff experiences and perceptions. Teaching in Higher Education, 11(2),161-173 Xing, X. & Xue, B. ( 2008). Study on Graduation Thesis Design Mode of Management Specialty in the Construction of Research University. In Proceedings of 2008 International Seminar on Education Management and Engineering. Zhang, Q., Lan,Y., Feng, J., et al. ( 2012). Teamwork approach for senior research projects for college undergraduates. In the 7th International Conference on Computer Science & Education (ICCSE 2012).Melbourne, Australia: IEEE. Zhao, X. &Zhang, R. (2011). Actively Developing Joint Direction for Optimization of Graduation Design Approaches Based on Data Integration., Springer Berlin Heidelberg: Berlin, Heidel- berg. p. 41-45. Zhou, S., Liu, A., & Fu,J.( 2008). The Process Management and Quality Control of Graduation Design. In International Symposium on Computer Science and Computational Technology. 2008: IEEE. Zhu, H., Xue, H., Wang, D., et al (2006). Analysis and implementation of degree thesis management system. Journal of Sichuan Institute of Technology. 19(5). Zuber-Skerritt, O. & Fletcher, M. (2007). The quality of an action research thesis in the social sciences. Quality Assurance in Education, 15 (4),413-436

76 EITT 2013, Williamsburg, VA, USA, November, 2013 Zhang, M. (2013). The contribution of multimedia teaching to physical education. Proceedings of International Conference of Educational Innovation through Technology, 77-78.

The Contribution of Multimedia Teaching to Physical Education

Minjie Zhang Inner Mongolia University of Technology E-mail:[email protected]

Abstract: With the expanding of the field of high technology, a kind of science and technology with a combination of electrical, optical and image has come into school in a sharp unstoppable momentum; it is applied to the education of interdisciplinary teaching, and is greatly developed as a kind of efficient method, which provides a convenient and effective path for the teaching.

Keywords: multimedia teaching, physical education, sports teaching

First, the application of multimedia to sports teaching could improve teaching effect. Integrating information technology into physical teaching to re-design the teaching not only can improve teaching methods and means of teaching greatly, but also can make up for the weaknesses of teachers’ quality, that is, to promote the dialectical unification of the dominant and the subject. In some projects such as gymnastics and fosbury flop, the teacher can not make a comprehensive demonstration according to the requirement in the classroom, and it is impossible to complete in slow motion as in learning contents. Using computer assisted instruction; the teacher can divide a whole into “parts” according to his needs and teach his students with realistic sound effects. In this way, not only can the students grasp its main points and understand its essence, but also it can ensure the progress and quality of the teaching.

Second, it can optimize the environment of physical education effectively and improve the quality of teaching. Nowadays, the students are more interested in the intuitive, visual and infectious images, and are willing to accept them. The multimedia teaching software in modern information technology is to satisfy their interests, and can adapt to the condition of their weak rational thinking and poor endurance, etc. The application of the multimedia teaching software raises the students’ main body function, expands the area of their knowledge, shortens the time of teaching, improves the quality of teaching, and stimulates the students’ creative thinking. Therefore, multimedia teaching is one of the important means to improve the teaching effect, and optimize the teaching.

Third, the application of multimedia can stimulate students’ interests and enthusiasm for learning. The use of multimedia teaching for action demo in training and game and for game analysis with image and data analysis, stimulates the students’ learning interests and learning enthusiasm, and has obtained the good effect.

Fourth, the use of small multimedia classroom improves the abilities of analyzing and solving problems. According to the schedule of teaching, appropriate arrangements for some sports practice teaching, such as: for team cohesion, we can let the students themselves design the multimedia courseware about the definition of influence factors on team cohesion and how

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 77 Proceedings of International Conference of Educational Innovation through Technology to improve team cohesion, and discuss in class to improve the ability of problem analysis and innovative ability.

Fifth, the application of multimedia can cultivate teamwork ability. Combining inside and outside class and the teachers and students together with lecture slides and other practical ways can cultivate the students’ innovation ability, teamwork ability and practical ability to work.

78 EITT 2013, Williamsburg, VA, USA, November, 2013 Cao, Q., Zhou, S., Xu, S., & Li, D. (2013). Design and implementation of reusable survey and test system based on SSI framework. Proceedings of International Conference of Educational Innovation through Technology, 79-84.

Design and Implementation of Reusable Survey and Test System Based on SSI Framework

Qian Cao, Shuyi Zhou, Shidong Xu Beijing University of Technology Email:{caoqian, zsy,xushidong}@bjut.edu.cn

Dong Li Beijing University of Technology Email: [email protected]

Abstract: Questionnaire and test are very important in educational activity. And on-line survey system is more and more popular for its convenience and accuracy. With the need for further practice of e-learning on campus, this paper analyses the current commercial survey systems, gives the details of the design and implementation of a reusable survey and test system based on SSI framework.

Keywords: questionnaire, framework, reusable, network teaching

1. Introduction Surveys or questionnaires are ordinary means for information collecting. On campus, teachers are getting used to obtain the feedback about the effect of pedagogic activities by the aids of questionnaires and test papers. With the development of information technology, the practices of surveys or questionnaires are changing from the traditional paper-and pencil surveys and manual processing method to online surveys or questionnaires and computer analysis method, by which the convenience and accuracy of survey data statistic are improved. In today’s world, there are some online survey systems aimed at commerce, of which the free version only supplies limited function, whilst the superior application needs to be paid. For this reason，it is difficult to satisfy the need of teaching and learning. Also, the limitation of the bandwidth of internet retards the easy application based on the campus network, not to speak of the smooth connection with different platforms of network teaching engaged in our school, as well as the integration to the existing database of students and faculty in college.

2. System Construction In view of the need of network teaching in practice, we have designed and implemented a reusable on-line survey and test system. According to the fact that the campus platform of network teaching in service is already based on Struts framework in Java, we employed the reliable SSI integrated framework for the development, namely, the three kinds of open-sourced web framework, Struts, Spring and Ibatis, are combined reasonably. In detail, Struts is mainly in charge of presentation layer which fulfils the display of page and responses to user’s request; Spring is in chargeof service logic layer which fulfill the service logic and routine process of application system; Ibatis is of persistence of data which engaged in the interaction with data layer. Such combination endows the system with high flexibility, expansibility and practicability. Figure 1 illustrates the

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work flowchart among three parts. Strut can supply a lot of labels easy-to-use. Meanwhile, with the aid of supplementary technologies as Ajax, SiteMesh and JQuery, the system provides improved system performance, optimized user interface so as to offer better experience for users.

Figure 1. SSI work flowchart

The user database of the survey system directly calls the database of network teaching platform（http://eol.bjut.edu.cn，calling it EOL for short）, in which the information of student users is imported by teachers through the educational administration information system. For this reason, enrolled students can login and use the system directly without extra registration step. The data of questionnaire are stored in the database of survey system. This kind of separated data storage is convenient for further system spread in the future and avoids the data redundancy.

There are questionnaire of two types in the survey system: questionnaire based on investigation and test page based on course test. The role of users in the system can be divided into three kinds: administrators, teachers and students. The administrators hold the supreme authority of the system, including management of all the questionnaire & test page, data record and system configuration. In addition, the administrators also can create questionnaire and initiate new survey.

80 EITT 2013, Williamsburg, VA, USA, November, 2013 Design and Implementation of Reusable Survey and Test System Based on SSI Framework

The main assignment of teachers in the system is to create questionnaire and test page. In most circumstances, the questionnaire & test page established by teacher are sent to the students of the class he instructed via the instating spread. Also, it can be spread to all the teachers and students in the system. In addition, the role of teachers in the system is the answerer to the questionnaire & test page. That is, they are able to either answer the questionnaire & test page established by others or review the answer records of themselves.

The main assignment of students in the system is the answer to the questionnaire & test page. They can answer the questionnaire & test page established by others or review the answer record themselves, but they don’t have the right to create questionnaire & test page. Figure 2 illustrates the general structure of the function module of system.

The survey & test system

Questionnaire Answer System Homepage Management of Management of the questionnaire the test page pool record configuration

List search All Newest of Hottest question questionna Log newest of questi questi Test page quest question naire ire in questio onnair onnair type ionna issue naire e e type attachment ire nnaire

Questionn Content Attrib Statics aire Inspect Edit of Status Copy and Download and ute Spread Check & establishm ion ion questionn switch delete export edition analysis ent aire

Figure 2. General structure of the function module of system

2.1. Homepage The homepage of system includes four parts: login, the list of questionnaire, the newest issue, and the search of questionnaire. After login, user will be connected to the user database of EOL, for the reason that the user database used by this system is the one of EOL. Meanwhile, there are two lists of questionnaire on the homepage: the newest questionnaire and the most popular questionnaire, in which the former is sorted by the issue time, and the latter is by the amount of answerers. These questionnaire listed on homepage is visible only when its attribute “anonymity can answer” is set to be true. The newest issue is arranged in the frequently-used dynamic display. This system mainly shows three kinds of the newest issue: questionnaire issued, answered and

EITT 2013, Williamsburg, VA, USA, November, 2013 81 Proceedings of International Conference of Educational Innovation through Technology questionnaire spread internal. The search of questionnaire can be used by fuzzy search to look up the questionnaire in system.

2.2. Management of the Questionnaire and Test Page Management of the questionnaire includes questionnaire establishment, inspection, attribute edition, questionnaire edition, spread, check, statics & analysis, trial, status switch, copy or delete, download or export, which is the same as Management of the test page. In fact, test page is an extension of questionnaire in function. Scoring function is added in the management of test page compared with the one of questionnaire. Every objective question in test page, either simple selection or multiple selections, has one correct answer, by which the system can give a score automatically after the test page is finished. Due to the answer of subjective question which can not be identified by the system, the teacher who established the paper needs to check the answer and give a score manually. After the score of each subjective question is determined, the total score appears by the calculation of system.

2.3. Questionnaire Pool Questionnaire pool implements two functions: the first one is at client side. In questionnaire pool, users can search the questionnaire concerned, browse the questionnaire or view the statics of answers. The second one is at server side. User can search questionnaire in database, if only he choose “creating from questionnaire database” option prior to establish a new questionnaire. Once the satisfied questionnaire is found out, it can be transferred to user’s own space directly, amended and transformed into his own questionnaire. It should be noted that the questionnaire will be put in questionnaire pool only when its attribute “anonymity can answer” is set to be true, or the questionnaire will be the user’s private questionnaire and would not be found in the questionnaire pool.

2.4. Answer Record Every user logged in the system can check the answer record himself, including the questionnaire and test page. But the anonymous user can not check it.

2.5. System Configuration Only administrator can examine and alter the system configuration including questionnaire type setting, questionnaire attachment management, and test page type management.

3. Implementation of Reusable Questionnaire In common surveys system, the establishment of questionnaire online is formed by questions one by one, and supplied to user for answer. Such a surveys system is lack of flexibility, and brings about some disadvantages, for example, 1) all the questionnaire are created in the manner of questions one by one, which is troublesome, 2) all the data is stored in system, which may leads to the missing of all the questionnaire in system once there are any breakdown occurred in the database of system. 3) Unable to utilize the abundant existing survey resources in internet. 4) Inconvenience in fully utilization of the existing survey resources in the system.

On the basis of analysis above, the titled system can create questionnaire in three ways with flexibility.

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The first one: creating questionnaire by questions one by one. There are five question formats supplied by the system to user for chosen: information column, simple selection question, multiple selection questions, single line input question, and multiline input question. The information column can be used for sectioning the questionnaire. The simple selection and multiple selection questions belong to objective part. The single line and multiline input questions belong to subjective part. For example, the web page for the establishment of simple selection question is shown in Figure 3.

Figure 3. Establishment of questionnaire question

The second one: creating questionnaire by importing the text of existing questionnaire into the system directly. The rule of import for question format is designed in the system, namely, adding a question format identification label to the text of questionnaire. On the web page for the establishment of questionnaire, example is displayed in the importing frame so as to supply a reference for teacher to create new questionnaire. The concrete rule of importing questionnaire is shown in Figure 4. As for the mistakes of question occur during the leading, the system would provide detailed information about the mishandling of user in order that the user can finish the questionnaire import correctly.

Figure 4. Rule of import

The third one: creating questionnaire by means of the questionnaire existed in questionnaire pool. When the attribute of questionnaire in the system is set to be publicly, it will be listed in questionnaire pool. Therefore, user can search the questionnaire he needed in the listed publicly questionnaire in the system when he select to create new questionnaire in this way. User can search the questionnaire needed, and click the “apply to my questionnaire database” button, and create his questionnaire, then amend it combined with the two ways above-mentioned until finish the establishment of questionnaire.

The fourth one: exporting the questionnaire as DOC file. User can choose to export the questionnaire established in system in WORD format, and save locally or print it out for conventional paper-and pencil survey or test.

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4. Conclusion Now, this system has been embedded smoothly into the EOL platform. As a result of the adoption of developing framework based on SSI, the degree of the system coupling is reduced, and the system also has been connected to the multimedia classroom service platform (http://class. bjut.edu.cn/Questionnaire/). There are some teachers who have performed course examination in the form of test paper online continuously for several semesters on EOL, also some teachers who have implemented surveys online by means of questionnaire online. In practice, teachers can check the situation of examination or investigation at any time in network. The system can display the result of statics & analysis instantaneously in graph. The result can be exported in DOC format or XLS format selected by teachers. The surveys system enriches the means of network teaching, and is proved to be suitable to the practical application so as to support further development of network teaching.

References Cao,Q., Zhou,S.Y., Xu ,S.D.& etc. (2008). The analysis of web-based instructional platform and the data translation when changing platforms. Modern Educational Technology, 18(11), 107- 109. IJmker, S., et al. (2008). Test-retest reliability and concurrent validity of a web-based questionnaire measuring workstation and individual correlates of work postures during computer work. Applied Ergonomics, 39(6), 685-696. Yang, S. J., Shi, S. T., Niu, Z. M., & Wang, Q. (2010). On Spring+Struts+iBatis composite frame based science and technology plan project managment system and its implementation. Computer Applications and Software, 27(11),111-113+116. Zhang, L. (2010). Application of data persistence tier based on ibatis and desing pattern. Journal of Anhui University (Natural Science Edition), 34 (03), 43-48.

84 EITT 2013, Williamsburg, VA, USA, November, 2013 Deng, W., Liu, Y & Han, X. (2013).Design and implementation of report repository system: an example of educational information visualization tools. Proceedings of International Conference of Educational Innovation through Technology, 85-88.

Design and Implementation of Report Repository System: an Example of Educational Information Visualization Tools

Wenjun Deng, Yingqun Liu, Xibin Han Tsinghua University Email: [email protected], {liu-yq, hanxb}@ tsinghua.edu.cn

Abstract: Visualizing educational data help education administrator to find educational problem and make wise educational decision. How to create the concept of information visualization which is simple and consumable for users is a problem. In this paper, we design and implement a report repository system to find out users’ information visualization requirement. The implement results show that a sample repository of information visualization system can help customers to easily find out what information visualization they want, and then improve effectiveness of information visualization.

Keywords: report repository; information visualization; educational information system

1. Introduction Academic management system(AMS) provide all the tools to manage students’ information as they move towards program completion and graduation. AMS have been widely used for years and have accumulated huge amounts of educational data, including student data, teacher data, course data and score data(En-hua, 2004). How could administrator use the massive educational data and transfer the data into useful information and knowledge in order to make scientific educational decision and teaching and learning quality. Data analysis includes three parts: information collection, information process and information visualization. Information visualization can be an effective mean to deal with larger amounts of data in order to sustain the cognitive load of educators at an acceptable level (Ali et al, 2012). The hardest part of information visualization is how to create the concept which is simple and consumable for users (Hibbard, 1999). The objective of this research is to study customized methods and techniques for information visualization to improve visualization effectiveness by design and implement a report repository system.

2. Materials and Method A report is a statement of the results of an investigation or of any matter on which definite information is required. The information is presented in a clearly structured format making use of sections and headings so that the information is easy to locate and follow. Report system is an effective means of the information visualization.

In AMS, reports are developed one by one for customers’ requirement. Generally, this customization process is described as figure 1. Firstly, a report designer discuss with customers about the report design, which includes concept, structure and style. Secondly, according to the report design, the designer writes a document and gives it to a report developer. Thirdly, the developer develops the report and gives it back to designer. Finally, designers show the report to customers. There is a problem in this process: your customers do not always know what they want.

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Steve Jobs said: “You can’t just ask customers what they want and then try to give that to them. By the time you get it built, they will want something new.” To solve this problem, we design a report repository system which has a repository of report samples. The report repository system provides three functions. The first is browsing reports, the second is picking up reports and the third is authorizing the report to other users. Firstly, report repository can help customers to find out what report they want, because customers can browses reports and pick up the report they want which can be the sample of the discussion with designer. Secondly, designers can put the report that used most into the repository. The report customization process with report repository is described as figure 2.

Figure1. Report customization process

Figure2. Report customization process with report repository

In report repository system, report creation process includes three parts: determine the scope of data, processing data analysis, outputting analysis result. Every part corresponds to a interface which complete the work belong the part. The ParameterHandler interface handles the scope of data, the BeanSouce interface processes data analysis, and Template interface output analysis result. Every interface has several implementations, and every implementation can be reused by a few of reports. For example, the Template interface has four implementations, one for outputting PDF file, one for XLS file, one for DOC file and one for plain text file. All reports use one of these implementations to output analysis result. Code reuse reduces development times and ease deployment. So do the ParameterHandler interface and the BeanSource interface. Every composition of three implementations of the three interfaces respectively defines how to create a report. So we define a class ReportRenderConfig to represent this composition. And we define a class ReportRenderController to control the process of creating a report. The figure 3 shows the relation between two classes and three interfaces.

86 EITT 2013, Williamsburg, VA, USA, November, 2013 Design and Implementation of Report Repository System: an Example of Educational Information Visualization Tools

3. Result and Discussion The report repository system was implemented to thirty universities who use academic management system of THOEL. After implementation, effectiveness of report development and degree of satisfaction of is improved. Report development time is reduced by 80%, from 5 days to 1 day. The main reason for reduction is that time of discussion between customers and designer is reduced and customers change their requirement less.

4. Conclusion A sample repository of information visualization system can help customers to easily find out what information visualization they want, and then improve effectiveness of information visualization.

Figure3. Design of the report repository system

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References Ali, L., Hatala, M., Gašević, D., & Jovanović, J. (2012). A qualitative evaluation of evolution of a learning analytics tool. Computers & Education, 58(1), 470-489. En-hua (2004). The Academic Management System Reform in China’s Universities: A Governance View [J]. R&D Management, 4, 018. Hibbard, B. (1999). Top ten visualization problems. ACM SIGGRAPH Computer Graphics, 33(2), 21-22.

88 EITT 2013, Williamsburg, VA, USA, November, 2013 Fu, G. & Wang, G. (2013).The cluster analysis of learners’ behavior characteristics in the network Environment. Proceedings of International Conference of Educational Innovation through Technology, 89-98.

The Cluster Analysis of Learners’ Behavior Characteristics in the Network Environment

Gangshan Fu Shanxi Normal University Email: [email protected]

Gaihua Wang Xi’an Vocational and Technical College Email: [email protected]

Abstract: With the rapid development and wide spread application of the computer and network, Web-based- learning or online learning is now an important component of the education system. Therefore, it is crucial to explore the characteristics of learners’ behavior in the online learning environment in order to effectively expand online learning and to construct digital resources, which is also the focal point of this research. The participants of this study were 2801 students enrolled in the “Modern Educational Technology” online learning system in Shanxi Normal University. Thru data mining, this study explored the characteristics of learners’ behaviors in online learning environment, and discussed the relationship between behavior characteristics and learning outcomes. Findings of this study showed two types of learning behaviors for male students: high immersion type and low immersion type; and seven types of learning behaviors for females students: high immersion and high achievement type, high immersion and low achievements type, moderate high immersion and active type, moderate high immersion and reflective type, moderate immersion type, low immersion and continual type, and low immersion and continuous type. Findings of this study also showed that learning behavior was closely related to the learning outcomes, and the immersion states had a positive impact on learning performance. Learners’ with high immersion state tended to have better learning performances.

Keywords: network environment, online learning, behavior characteristics, clustering, data mining

1. Introduction and Literature Review With the rapid growth and development of computer and network usage, online learning has become an important component of school teaching and learning. Online learning has expanded beyond the time and space constraint of the traditional education, changed students’ learning method, and made students’ independent learning possible (Berman & Tinker, 2000; Mambretti, 1999; Pelgrum & Anderson, 2001). Because of this expansion, studies about online education have become a critical component of educational research. More and more researches are being conducted to investigate the adaptability of students in the online education system (Brusilovsky, 2000, 2001, 2002, 2003, 2004; Cristea, 2004, 2005). A major challenge of adaptive learning is to understand the characteristics of the students and to create a more effective education model (J. Michael Spector et al., 2007). However, the evidence on effective learning model is limited and the theoretical research is weak (Shapiro & Niederhauser, 2004). According to Judy Kay (2006), numerous researches proved that the challenge could be solved by collecting students’ learning records (such as the date from database and weblog documents).

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The literature review indicates that numerous studies on learner characteristics in the online environment focused on the physiological aspects; for instance, the learners’ background knowledge, demographics and sociological variables, emotional state, cognitive ability, learning styles, etc (Shih et al, 2006; Conchas, 2006; Conati, 2002; Craig et al., 2004; Kinshuk & Lin, 2004). There is not enough focus on the behavior aspects of the students. The research methods for learners’ behavior in the network environment mainly include interviews, surveys, observations, experimentations, database data, Weblog documents, Web messages, etc. The main method implemented is still surveys; however, in recent years, more and more researches are utilizing learner’s Web entries, comments, and database data for quantitative analysis. In addition, the author found other cons in the current researches. First of all, the quantity of research subject sample was too small, and data mining requires a large quantity of data to derive effective and useful information. A small data would affect the quality of the analysis; therefore, the reliability of the research results would require further verification. Secondly, with the diversity of online learning, what types of learning behaviors exist in the network environment was not studied in a complete systematic manner, which requires further research.

For example, Drick Boyd (2004) distributed a survey to study the online learning behaviors of college students, and summarized the online learning characteristics of the successful students. Nian-Shing Chen and Kan-Min Lin (2002) used qualitative and quantitative analysis (percent, T test, difference comparison, Content Analysis, Protocol Analysis) to investigate 74 Master’s student at National Sun Yat-sen University about the types of online learning behaviors and the influence of these behaviors on their learning quality. They found those student behaviors could be categorized into continuous learner/ continual learner and active learner /non-active learner. The interaction could be categorized into positive interaction /non-interaction, only ask questions/only answer questions/neither ask nor answer questions/ask and answer questions. They also found a strong correlation existed between the learning behavior and the final grade; the more students participated in various study activities, the higher their grades were. Jui-Long Huang and Ke Zhang (2008) used statistical models and machine study such as data mining to analysis the Web entries of 98 college students. Their research found students could be characterized into active and passive learners in the network environment.

This study utilizes data mining technique to conduct a quantitative analysis on the online learning behavior characteristics (data in the database) of large learning groups. The purpose of the study is to explore the types of online learners’ behavior and to discover the relationship between behavior characteristics and the learning outcomes. The results of the study not only can help educators better understand the individual learners and develop teaching strategies based on the learners’ behavior characteristics; but also recommend more suitable and personalized resources for students based on students’ behavior, thus providing a theory foundation for the adaptive learning system in a web setting and for effective learning.

2. Methodology 2.1. Research Framework The learning behavior characteristics mentioned in this research refer to the learners’ behavior data from the online learning platform database, which include study time span, total study time

90 EITT 2013, Williamsburg, VA, USA, November, 2013 The Cluster Analysis of Learners’ Behavior Characteristics in the Network Environment duration, study time frequency, the average duration of online learning, repetition rate, discussion and communication, study notes and the quantity of text messages received.

This study utilizes the cluster analysis technique from data mining to explore the following research questions: (1) How many categories can students be grouped? (2) What are their study behavior characteristics for each category? (3) What is the effectiveness of learning in each category? (4) How will teachers select the appropriate resources and encourage learning in order to achieve effective learning for the students in different categories.

2.2. Participants and Settings The research participants were 2936 students (2687 junior undergraduates and 249 adult education masters student) from Shanxi Normal University who took the “Modern Educational Technology” online course in the second semester of the 2011- 2012 school year. After the initial data mining analysis, the number of valid participants was 2801 students.

There were some specialties of this research. First of all, this research covered a wide range of majors, including students from 16 schools and 20 majors in liberal art, science and engineering, and arts. Second of all, this research utilized a multiple learning styles to investigate steady student groups. The students were limited to one semester of online learning, which was a well-developed learning system. Thirdly, the research had a large subject pool. The database recorded the data about over 2800 learners’ online learning process. Finally, this online learning system had all necessary functions to support students’ diversified learning styles. This network environment had already achieved positive results. This course had been ranked as a national high quality course in 2006 and named a national teacher educational resource excellence course in 2013. Therefore, using these data to explore learners’ behavior characteristics in the network environment made it easier to discover patterns, to verify the reliability of research results, and the help with the representation and persuasiveness of the related results.

2.3 Introduction of the Online Learning Platform The “Modern Educational Technology” online course at Shanxi Normal University is an open educational resource (the website is http://edutech.snnu.edu.cn/). The learning objectives of the course are to perceive the education reform in the information age and adapt to the needs of social development; to understand the curriculum innovation in the information age and experience new class structures; to learn the basic theories of educational technology and gain basic knowledge of multimedia teaching skills; to understand the characteristics of teaching and learning in the information age and master basic teaching skills with information technology; to apply the theories to the practices and enhance information literacy. This learning platform was mainly formed by classroom learning, study guides, multimedia learning, discussions, software downloads, and other aiding utilities (i.e. high quality homework, information subscription, class notes, homework management, messages to instructor). Over the years, through practice and exploration, the university developed a set of web-based learning environment support and teaching management method, formed a multi-network learning environment composed of blended learning, dual- classroom learning, project-based learning, collaborative learning, and self-learning.

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The course utilized multiple assessment methods, such as the informative assessment (learning progress, participation level, and milestone progress) and summative assessment. First of all, the learners must meet the required online learning time, homework time and self-test frequency, etc. Secondly, those who passed the online learning assessment were graded as follow: online homework (Design Score, DS) 10%, practical skills (Inter Score, IS) 20%, online exams (Web Score, WS) 20%, and final written exam (Final Score, FS) 50%. The grading method of this course is reasonable and effective, and has already gained wide spread recognition by the learners and society.

2.4. Procedures and Data Collection This study utilized the SQL Server 2008 Data Mining tool for the cluster analysis of student behaviors. The first step of data mining is data understanding. The online learning system database contained more than 40 data sheets. This research selected three types of data: basic characteristics of learners, behavior characteristics of learners, and learning efficiency of learners.

The second step of data mining was data preparation including data cleaning, data integration, data transformation, and data reduction. Data cleaning was mainly achieved thru the combination of SQL language and manual intervention. Data transformation mainly included tectonic attributes, data normalization, data discretization, and data reduction. This study implemented the maximum- minimum data normalization method, K-means data discretization method, and no loss reduction. The structure of the study included learning time span (i.e. the time span from the first time when the learner logged on to the last time when the learner logged out of the system), the total learning duration (i.e. the accumulation of the total time the learner spend in the network environment), learning frequency (i.e. the number of times the learner logged on the system), the average length of stay per study session (i.e. the average duration of each study session), repetition rate (i.e. the average number of times the learner reviewed each key points), discussion (i.e. the utilization of BBS for discussion, evaluated thru the combination of the number of threaded posts, the number of clicks on the thread, the number of replies, and the number of clicks on the replies), classroom notes (i.e. the online learning notes taken by the learner, formed by the quantity of online notes, frequency of updates, and the click number), the quantity of text message received (i.e. the number of texts the learner received during studying that encouraged them to learn), and the learning outcomes (i.e. the final grade, composed of online homework, practical skills, online tests, and the final written exam).

3. Results This research used the Microsoft Clustering algorithm from the Microsoft SQL Server Analysis Services, an iterative technique of segmentation algorithm. Microsoft Classification Viewer provides four different diagrams: “Classification Diagram” (Fig. 1), “Classification Profile” (Fig. 2), “Classification Features”, and “Classification Comparisons”. Due to the large size of the images and the large number of diagrams in this section, only some screen captures are displayed here.

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Figure1. The Classification Diagram tab of Clustering mining model

Based on the four diagrams, we can summarize the characteristics of the students. From table 1, male students can be clustered into two categories: high immersion type and low immersion type. Based on table 2, female students can be clustered into seven categories: high immersion- high achievement, high immersion-low achievement, moderately high immersion-active type, moderately high immersion-reflective type, moderate immersion, low immersion- continual type, and low immersion-continuous type.

Table 1. The Summary of Clustering for Male Students Category Cluster N u m b e r Learning Characteristics Learning of People Result High 3 206 Learners of this type have very high adhesion Good to the network learning platform, very high Immersion immersion to the network, high enthusiasm to Type study, high willingness to participate in activities and discussions, and a strong self-control 1 208 Learners of this type have low adhesion to the Poor Low network learning platform, low immersion Immersion to the network, low enthusiasm to study, low 5 202 participation, hardly join any group activities, Type and low self-control.

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Figure 2. The Classification Profiles tab of clustering mining model

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Table 2. The Summary of Clustering for Female Students Category Cluster Number Learning Characteristics Learning of Result People High 2 200 Learners of this type have very high adhesion to Good Immersion- the network learning platform, high immersion High to the network, high enthusiasm to study, high Achievement willingness to participate in activities and Type discussions, and strong self-control. High 9 172 Learners of this type have very high adhesion to Poor Immersion- the network learning platform, high immersion Low to the network, high enthusiasm to study, high Achievement willingness to participate in activities and Type discussions, and strong self-control. Moderately 7 196 Learners of this type have high adhesion to the Good High network learning platform, high immersion to Immersion- the network, have tendency to proactively be Active involved, learn through discussion and asking Type questions, enjoy communication through the internet, and have relatively strong self-control. Moderately 4 196 Learners of this type have high adhesion to the Moderate High network learning platform, high immersion Immersion- to the network, tend to be reflective when Reflective observing and dealing with information, good Type at learning through deep thinking, prefer individual study, low participation in network learning, hardly join in discussion and note taking activities Moderate 6 194 Learners of this type will adhere to the network Poor Immersion platform, will immerse in the network, willing Type to learn, the motivation for learning is mainly to complete the task, will participate in activities, have very few interaction, and moderate self- control. Low 8 178 Learners of this type have a comparatively low Poor Immersion- adhesion to the network platform, relatively Continual low immersion to the network, low enthusiasm Type for study, have low participation, rarely join in discussions and note taking, low self-control, prefer to learn in a very short period of time thru cramming, and like to learn in intermittent phase.

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Low 10 159 Learners of this type have a comparatively Poor Immersion- low adhesion to the network platform, low Continuous immersion to the network, low enthusiasm Type to study, low participation, rarely join in discussions and note taking, low self-control, and prefer step-by-step study. They have a linear study process, with a fixed and continuous study time.

4. Discussion and Conclusion The findings from this research show immersion level has a strong influence on student learning. Based on the above findings, the researcher suggested online instructors to provide expansive knowledge or outside resources in terms of contents for the male high immersion learners, female high immersion-high achievement and moderately high immersion-active types to enrich their learning content and to broaden their learning horizon. In addition, instructors should design highly challengeable activities for these students, guide them to become leaders, and actively communicate with them.

In terms of learning content and learning assignments, for male low immersion types and female low immersion types, it is recommended that the knowledge systematically sent to students should be easy learning tasks, which is not hard and utilizes illustrative texts and fun learning resources, and use the task-driven method to encourage them to complete their study tasks. In terms of regulation, there must be stronger supervision and guidance, such as sending text messages through the system, E-mail, professor messages, and other notification to remind students of their current progress. For the interactive aspect, this group requires specialized attention; the professor should actively interact with them, and design an incentive system to motivate them to participate in discussions. This way, these low immersion students can gain a strong sense of acceptance to improve their immersion level, and finally achieving better learning results. As for the continuous learners, the professor must provide well-structured learning resources, a well-developed learning process, and must not implement too many connections which will aggravate these students’ learning burden. For those continual students, it is best to strength the pluralistic evaluation, especially informative assessment.

Females who are high immersion-low achievement type suffer from bad study strategies; although they have high learning immersion and study hard, but their results are not as good as expected. To help these students, they must be guided and trained with a better learning strategy, such as mind mapping, memory skills, etc.

For the females who are moderately high immersion-reflective type, the instructor can use an incentive system or small group activities to promote their online participation, allowing them to experience the fun and benefits of collaboration, and improve their team work skills.

Female learners who are moderate immersion type may have good grades, but their online learning immersion is only moderate, with moderate self-consciousness. Their motive for learning is mainly to complete the assigned task. Therefore to target this type of student,

96 EITT 2013, Williamsburg, VA, USA, November, 2013 The Cluster Analysis of Learners’ Behavior Characteristics in the Network Environment instructors can design the learning materials that are of interest while possessing certain challenges to the student.

References Berman, S., & Tinker, R. (2000).The world’s the limit in the virtual high school. In Pea, R. D. (Intro.), Technology and Learning (pp.192-196). San Francisco: Jossey-Bass. Brusilovsky, P. (2000). Adaptive hypermedia: from intelligent tutoring systems to Web-based education. In Intelligent Tutoring Systems, LNCS 1839, edited by G. Gauthier, C. Frasson, and K. Van Lehn, pp.1–7. Berlin:Springer. Brusilovsky, P. (2001). Adaptive hypermedia. User Model and User-Adapted Interaction, 11, 87– 110. Brusilovsky, P. & Nijhawan, H. (2002). A framework for adaptive e-learning based on distributed re-usable learning activities. In Proceedings of World Conference on E-Learning, E-Learn 2002: Montreal, Canada, edited by M. Driscoll and T. C. Reeves, pp.154–161. Chesapeake, VA: Association for the Advancement of Computing in Education. Burstein, J. (2003).The E-rater scoring engine: automated essay scoring with natural language processing. In Automated Essay Scoring: A Cross-Disciplinary Perspective, edited by M. D. Shermis and J. C. Burstein, pp.133–122.Mahwah, NJ: Lawrence Erlbaum Associates. Burleson, W. & Picard, R.W. (2004). Affective agents: sustaining motivation to learn through failure and a state of stuck. In Proc. of the Intelligent Tutoring Systems 7th Int. Conf. (ITS 2004):Workshop on Social and Emotional Intelligence in Learning Environments. August 30- September 4, Maceio-Alagoas, Brazil. Conchas, G. (2006).The Color of Success: Race and High Achieving Urban Youth. New York: Teachers College Press. Conati, C. (2002). Probabilistic assessment of user’s emotions in educational games. Applied Artificial Intelligence, 16(7–8), 555–575. Craig, S. D., Graesser, A. C., Sullins, J., & Gholson, B. (2004). Affect and learning: an exploratory look into the role of affect in learning with auto tutor. Learning. Media and Technology, 29(3), 241–250. Cristea, A. I. & Garzotto, F. (2004). Designing patterns for adaptive or adaptable educational hypermedia: A taxonomy, Morgantown, WV: Association for the Advancement of Computing in Education. Retrieved from http://wwwis.win.tue.nl/~acristea/HTMP/Minerva/papers/ Garzotto-Cristea-symposium-patterns-2give.doc Cristea, A.I. (2005). Authoring of adaptive hypermedia; adaptive hypermedia and learning environments. In Advances in Web-Based Education: Personalized Learning Environment, edited by S.Y.Chen and G. D. Magoulas. Hershey: IDEA. Retrieved from: http://wwwis.win. tue.nl/~acristea/Chen/AHChenBook Chapt-camera Ready2.doc Boyd, D. (2004). The characteristics of successful online students. New Horizons in Adult Education, 18(2),31-40. Spector, J.M, Merrill, M.D., Merrienboer, J., & Driscoll, M.D. (2007). Handbooks of Research on Educational Communication and Technology (3rd. Ed). American. 2007: 241. Hung, J.L & Zhang, K. (2008). Revealing on1ine 1earning behaviors and activity patterns and making predictions with data mining techniques in online teaching. MERLOT Journal of online Learning and Teaching, 4(4).

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Kay, J. (2006). Challenges and future of learner modeling. Personal Communication, 6. Kinshuk & Lin, T. (2004). Cognitive profiling towards formal adaptive technologies in Web-based learning communities. Int. J. WWW-Based Communities, 1(1), 103–108. Chen, N.S. & Lin, K.M. (2002). Analysis of learning behavior and learning performance in WBI. Information Management, 8(2),121-133. Mambretti , C. (1999). Internet technology for schools. Jefferson, NC: McFarland. Pelgrum, W. J., & Anderson, R. E. (2001). ICT and the emerging paradigm for life-long learning: An IEA educational assessment of infrastructure, gals, and practices in twenty-six countries. Amsterdam: IEA. Salanova, M., Bakker, A. B., & Llorens, S. (2006). Flow at work: evidence for an upward spiral of personal and organizational resources. J. Happiness Studies, (7), 1–22. Shapiro, A. M. & Niederhauser, D. (2004). Learning from hypertext: research issues and findings. In Handbook of Research on Educational Communications and Technology, 2nd ed., edited by D. H. Jonassen, pp. 605–620. Mahwah, NJ: Lawrence Erlbaum Associates. Shih, P., Munoz, D., & Sánchez, F. (2006).The effect of previous experience with information and communication technologies on performance in a Web-based learning program. Comput. Hum. Behav, 22(6), 962–970.

98 EITT 2013, Williamsburg, VA, USA, November, 2013 Wang, S. R. & Wang, S. Y. (2013). Adopting E-Books in Curricular. Proceedings of International Conference of Educational Innovation through Technology, 99-104.

Adopting E-Booksin Curricular

Sirui Wang, Shuyan Wang The University of Southern Mississippi Email: [email protected]; [email protected]

Abstract: The purpose of this article is to explore the possibility of promoting e-books as instructional delivery method in curricular, provide evidences of the successful integration of e-books in teaching and learning process, and discuss the possible future of integrating e-books into education as a method for instruction delivery.

Keywords: electronic books; e-books; digital learning; instruction delivery

1. Introduction Researches have shown that instructors have difficulties to change their reading habits from paper to electronic screens in the process of adopting e-books in education (Wilson, 2003). However, there are at least fifteen states in US have already changed their laws or policies on the state level to extend textbook formats from paper-based to computer and technology devices (Levin, 2011). The purpose of this article is provide a comprehensive understanding of e-books and explore the possibility and challenges of promoting e-books as instructional delivery method in curricular in the future.

2. Awareness of E-Books in Education Although e-books still have not been completely accepted by instructors as a method to delivery their instructions, researchers have confirmed the great potential of e-books in education. The State Educational Technology Directors Association (SETDA) in the report of National Educational Technology Trends 2012 has stated that involving e-books in higher education has the advantages of (a) delivering content digitally, which addresses the “diversity of students, geographic locations, underserved areas, the dropout rate and the achievement gap” (Alliance for Excellent Education , 2012, p.11), (b) providing access to digital content through multiple methods that include digital textbooks, audio and video resources, apps, and interactive online content, (c) personalizing learning experiences based on learning styles, interests, abilities, and adaptive software, and (d) providing multiple learning platforms for delivering content and curriculum (Duffey & Fox, 2012).

With its digital format, e-books provide instructors flexibilities of delivering instructions, and make learning customized depending on learners’ diverse background and learning ability. It is necessary for instructors to understand the digital features of e-books and find the appropriate way to deliver their instructions through this digital format.

3. Features of E-Books E-books, also known as digital books, electronic books, or E-book, have a variety in terms of its definition and format. In this article, it refers to e-books. It can be easily considered as the content of printed books reproduced digitally, either in PDF, text, or other Web-compatible formats

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(Lamothe, 2011; Tripathi & Jeevan, 2007).With its demonstrated digital format, e-books have been qualified with several highlighted features to benefit instructors and students.

3.1. Flexibility in Accessing Instructional Materials Compared with the traditional printed books, the text-to-speech function of e-books allows readers to listen to the text that helps increase learning opportunities for students who have disabilities in reading due to deafness or blindness (Cavanaugh, 2008). In Lynch’s study of promises of e-books in 2013, he found that e-books allow the adjustment of text font size and style that benefit readers who are disabled in vision. As assistive tools, the reading option of e-storybook enhances readers’ comprehension (Doty, Popplewell, & Byers, 2001); while the word pronunciation tools in e-books assist readers’ phonologically (Olson & Wise, 1992).

In a word, using e-books to delivery instruction allows a flexible access to instructional materials for teaching and learning, provides a flexible learning platform for students, and promises instructors diverse options of introducing instructional materials and activities into classroom.

3.2. Adaptability to Different Instructional Standards Cavanaugh (2005) stated that, the digital format of e-books allows teachers to easily modify their teaching materials to adapt to different needs and standards. For instance, it is very common that traditional textbooks require teachers to analyze and decide what parts are proper for their school district, because they developed to support multiple state standards; but with the help of e-textbooks, teachers can easily customize their textbooks without worrying about the unmatched standards outside of their states (Mardis, Everhart, Smith, Newsum, & Baker, 2010).

3.3. Less Weight and Low Cost Compared with traditional paper-based books, e-books have the advantages in light weight and low cost. E-books provide not only more learning opportunities for learners that deserve learning but also relief for learners who are burdened physically (Petracco, 2001). Currently, in K-12 and higher education settings, students carry a heavy load of printed textbooks that is heavy in weight as well as in cost. The technology of e-books makes carrying a large collection of books in its “light and compact portable form” possible (Lynch, 2013).

3.4. Interactivity in Instruction Recent researches shown e-books provided more opportunities for teacher-student, student- student, and student-content interaction than the traditional textbooks. Mardis, Everhart, Smith, Newsum, & Baker (2010) found that teachers could deliver instructional materials in a more interactive way through the digital format of e-books and customize the teaching and learning processes that motivate students more easily than traditional books. Larson (2010) also found that e-books “may support students’ comprehension and strengthen both aesthetic and efferent reader response” (p.15).

In a summary, all these features possessed by e-books in its digital format “represent potentially important determinants of user willingness” in higher education (Lai & Chang, 2011, p.559).

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4. Examples of Integrating E-Books into Education According to Embong, Noor, Ali, Bakar, and Amin (2012), digital technology of e-books make instructional materials and activities rich; somehow, the use of e-books is “rapidly gaining ground in education” during the advancement of technology and even “slowly replacing the conventional textbooks” (p.581).

The first widely adoption of e-books in educational setting was in the project Gutenberg founded by the University of Illinois in 1971, which provided free access to thousands of books online that made educators and learners aware of digital books and helped learning become rapidly digitalized (Kissinger, 2011). With an access to over 33,000 free e-books, the project Gutenberg made educators and technologists consider the involvement of e-books into learning as “a realistic, potentiality effective medium” (Embong, Noor, Ali, Bakar, & Amin, 2012, p.20).

One of the most successful digital content programs in K-12 education is the e-textbook program in Georgia from 2010-2011. Setting Thomasville High School as the testing-site, Georgia shares two goals for promoting e-textbook programs: (1) to move away from traditional textbooks to its digital content, and (2) to help increase student achievement by engaging students and differentiating instruction in grades 8 to 12(http://tinyurl.com/thomasvilledigital) (eTextbook, 2012). After facilitating the program in a complete school year, the percentage of 9th and 10th grade students with proficient or advanced 21st century skills levels has increased by “12 percent in one school year based on standardized assessments” (Duffey& Fox, 2012, ¶6), which has proved to be the apparent effects of e-textbook in improving students mastery of technological skills.

The e-book project at Clearwater High School with Amazon Kindle in 2010 is another example that successfully replaced print textbooks with e-books (Embong, at el, 2012). Amazon Kindle provided e-book readers to all 2,100 students and 100 teachers with all subjects that were taught in school loaded. This allowed students and instructors at Clearwater High School who used the electronic devices realize that what they did with printed textbooks such as book marking pages, making notes, as well as searching for word definition and highlighting texts the same process as with the e-books. The population and dedicated designed materials of this e-book project made the results a successful example of reinforcement of e-books in education.

5. Challenges of E-Books as an Instruction Delivery Method As stated above, with the desired features of e-books, implementing e-books in education will make content delivery digitalized, provide multiple methods to access instructional materials, customize teaching and learning experiences, and support multiple learning platforms for instruction delivery and content delivery (Duffey & Fox, 2012). It is also important to discuss the limitations and challenges of integrating e-books in education.

Although with the development of technology, e-book readers have the features of “convenience, compatibility, and media richness (Lai& Chang, 2011, p.559), ” people would think that teachers would promote significantly the acceptance of e-books in education. However, in Wilson’s research of e-books in academic environment, 50% teachers investigated denied the usage of e-books in their teaching and learning because of the complexity of e-book

EITT 2013, Williamsburg, VA, USA, November, 2013 101 Proceedings of International Conference of Educational Innovation through Technology readers (Wilson, 2003). Besides the complexity of e-book readers, the cost of devices and less technological support from school district also limit the integration of e-books into teaching and learning. It would be hard for instructors to deliver instruction through e-books without the support from their schools or department. Only when instructors have a proficiency of e-books and obtain the in-time support from school district, can the integration of e-books become a popular and common delivery method for education.

6. Conclusions As discussed above, there are many advantages of integrating e-books into curricular although there are limitations. With e-books, students will be able to collaborate with peers and interact with teachers and peers easily in the traditional classroom and hybrid learning programs. Instructors can extend the instructional materials by adding external links to the e-books and share among students; students can provide their feedbacks and reflections on learning materials instantly when they reading through e-books by adding shared notes. Therefore, e-books have a very bright future in education.

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References Alliance for Excellent Education. (2012).The digital learning imperative: How technology and teaching meet today’s education (challenges). Retrieved from http://all4ed.org/files/ DigitalLearningImperative.pdf. Cavanaugh, T. (2005). The digital reader: Using ebooks in k-12 education. Eugene, OR: International Society for Technology in Education (ITSE). Cavanaugh, T., & Cavanaugh, C. (2008). eBook libraries (the whole list). Retrieved from http:// drscavanaugh.org/ebooks/libraries/ebook_libraries_list.htm Doty, D. E., Popplewell, S. R., & Byers, G. O. (2001). Interactive CD-ROM storybooks and young readers’ reading comprehension. Journal of Research on Computing in Education, 33, 374- 384. Duffey, D. & Fox, C. (2012). National Educational Technology Trends 2012: State Leadership Empowers Educators, Transforms Teaching and Learning. Washington, DC: State Educational Technology Directors Association (SETDA). Embong, A.M., Noor, A.M., Ali, R.M.M., Bakar, Z.A., & Amin, A.R.M. (2012). Teachers’ perceptions on the use of e-books as textbooks in the classroom. World Academy of Science, Engineering and Technology, 70, 580-586. eTextbook (2012). Thomasville city schools website. Retrieved from http://tinyurl.com/ thomasvilledigital Kissinger, J. S. (January, 2011). A Collective Case Study of Mobile E-book Learning Experiences. (Doctoral Dissertation). UNF Theses and Dissertations. paper127. http://digitalcommons.unf. edu/etd/127 Lai, J.Y., & Chang, C.Y. (October, 2011). User attitudes toward dedicated e-book readers for reading: The effects of convenience, compatibility and media richness. Online Information Review, 35(4), 558-580. Lamothe, A.R. (2011). Factors influencing the usage of an electronic book collection: Size of the e-book collection, student population, and faculty population. College & Research Libraries, 74(1), 39-59. Larson, L.C. (2010). Reader response meets new literacies: empowering readers in online learning communities. The Reading Teacher, 62(8), 638–648Levin, D.A. (September, 2011). Digital Content: Making Learning Relevant. Principal Leadership, 12(1), 32-36. Lynch, C.A. (2013). EBooks in 2013. E-content Supplement to June 2013. ALA. p.12-16. Mardis, M., Everhart, N., Smith, D., Newsum, J., & Baker, S. (July,2010). From paper to pixel: digital textbooks and florida’s schools. A white paper. The Florida State University PALM Center. Retrieved from http://www.eric.ed.gov/PDFS/ED522907.pdf Olson, R. K., & Wise, B. (1992). Reading on the computer with orthographic and speech feedback: An overview of the Colorado Remediation Project. Reading and Writing: An Interdisciplinary Journal, 4, 107-144. Petracco, P. (2001). Weighing in on backpacks. School Leader, Info Link. Retrieved from http:// www.njsba.org/members_only/publications/school_leader/May-June-2001/ info_link.htm

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Tripathi M. &Jeevan, V.K.J. (2007). E-book Subscription in a Distance Education Institution: A Case of Indira Gandhi National Open University, India, 104-114. Wilson, R. (2003). Ebook Readers in higher education. Educational Technology & Society, 6 (4), 8-17, Retrieved from http://ifets.ieee.org/periodical/6_4/3.pdf

104 EITT 2013, Williamsburg, VA, USA, November, 2013 Hung, J., Hsu, Y., & Rice, K. (2013). Evaluating K-12 online program - An data mining approach. Proceedings of International Conference of Educational Innovation through Technology, 105-114.

Evaluating K-12 Online Program - an Data Mining Approach

Jui-Long Hung, Yu-Chang Hsu, Kerry Rice Boise State University Email: {andyhung, hsu, krice}@boisestate.edu

Abstract: This study investigated an innovative approach of program evaluation through analyses of student learning logs, demographic data, and end-of-course evaluation surveys in an online K–12 supplemental program. The results support the development of a program evaluation model for decision making on teaching and learning at the K–12 level. A case study was conducted with a total of 7,539 students. This study demonstrated how data mining can be incorporated into program evaluation in order to generate in-depth information for decision making. In addition, it explored potential EDM applications at the K-12 level that have already been broadly adopted in higher education institutions.

Keywords: educational data mining, program evaluation, K–12 virtual school, pattern discovery, predictive modeling

1. Introduction Traditionally, the majority of online instructors and institutional administrators rely on web- based course evaluation surveys to evaluate online courses (Hoffman, 2003). The data and information are then used to help inform online program effectiveness and generate information for program-level decision-making. While it enjoys wide use, the survey method only provides learners’ self-report data, not their actual learning behaviors

Several studies have found self-reported data were not consistent with actual learning behaviors (Hung & Crooks, 2009; Picciano, 2002). This inconsistency can potentially compound the already problematic lack of direct observation opportunities. Online program administrators need more effective tools to provide customized learning experiences, to track students’ online learning activities for overseeing courses (Delavari, Phon-amnuaisuk, &Beikzadeh, 2008), to depict students’ general learning characteristics (Wu & Leung, 2002), to identify struggling students (Ueno, 2006), to study trends across courses and/or years (Hung & Crooks, 2009), and to implement institutional strategies (Becker, Ghedini, & Terra, 2000). Each of these needs can be addressed by mining educational data. Nowadays, various educational data are stored in database systems. This is especially true for online programs, wherein student learning behaviors are recorded and stored in Leaning Management Systems (LMS). Program administrators can take advantage of emerging knowledge and skills by extracting and interpreting that data.The purpose of this study is to propose a program evaluation framework using Educational data mining.

2. Program Evaluation Program evaluation is the means by which a program assures itself, its administration, accrediting organizations, and students that it is achieving the goals delineated in its mission statement (Nichols & Nichols, 2000). Evaluation can be done by a variety of means. The most common form of evaluation is through surveying students regarding courses/faculty/programs (e.g.,Cheng, 2001;

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Hoffman, 2003;Spirduso& Reeve, 2011).However, making causal inferences based on a one-time assessment is risky (Astin& Lee, 2003). Nevertheless, perceptional survey data cannot accurately reflect real learning behaviors (Hung & Crooks, 2009; Picciano, 2002). Although various scholars (e.g., Grammatikopoulous, 2012; Vogt &Slish, 2011) have proposed systematic frameworks (e.g., interviews and observation) in order to obtain objective knowledge via multiple means, these methods are difficult to implement in a fully online program.

3. Educational Data Mining Data mining (DM) is a series of data analysis techniques applied to extract hidden knowledge from server log data (Roiger&Geatz, 2003) by performing two major tasks: pattern discovery and predictive modeling (Panov, Soldatova, &Dzeroski, 2009). Educational data mining (EDM) is a field which adopts data mining algorithms to solve educational issues (Romero & Ventura, 2010). Romero & Ventura(2010) reviewed 306 EDM articles from 1993 to 2009and proposed desired EDM objectives based on the roles of users. For the purpose of this study, which is designed to inform administrators, the list is limited to objectives for administrators: • Enhance the decision processes in higher learning institutions • Streamline efficiency in the decision making process • Achieve specific objectives • Suggest certain courses that might be valuable for each class of learners • Find the most course effective way of improving retention and grades • Select the most qualified applicants for graduation • Help to admit students who will do well in higher education settings Based on the theory of bounded rationality, decision-making is a fully rational process of finding an optimal choice given the information available (Elster, 1983). An ideal program evaluation framework should provide multiple facets of information to decision makers. Therefore, integrating more than one data source and analytic method is essential for an effective program evaluation.

4. Program Evaluation Framework Figure 1 shows the framework of the proposed program evaluation method. The core strategy of this framework is data triangulation (Jick, 1979) which combines multiple data sources (learning logs, course evaluation survey, and demographic data) and multiple methods (pattern discovery and predictive modeling) to generate accurate, in-depth results. Using this framework, the authors conducted a program evaluation case study to evaluate how the proposed program evaluation framework can support administrators’ decision making.

5. Method 5.1. Data Source In this case study, data were collected from a statewide K–12 online institution that serves over 16,000 students in a northwestern state in the U.S. The institution provides fully online courses to K–12 students. Courses were designed by subject-matter curriculum designers and subject-matter teachers to standardize course materials. Teachers were required to complete an online orientation prior to teaching courses for the institution. Teachers received the same or similar training for online teaching provided by the institution. Site coordinators are located at each district in the state and regional principals oversee teacher evaluation. The following data were collected for the academic year of 2009-2010 (3,604 students enrolled in fall 2009 and 3,935 students in Spring 2010): 1) LMS

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activity logs; 2) student demographic data; and 3) course evaluation survey data. All data tables were stored in the database and inter-connected with unique identifiers (e.g., course ID).

Figure 1. Program evaluation framework

5.1.1. LMS activity logs The LMS activity logs were collected from the Blackboard activity accumulator (Blackboard Inc., 2010) for the fall 2009 and spring 2010academic terms. The following records were removed in data preprocessing: irrelevant fields (e.g., group ID), irrelevant records (e.g., login failure), and data stored in wrong or mismatched fields (about 11.8% of overall activity logs). After data preprocessing, a total of 23,854,527 activity logs were collected from 7,539 students in 883 courses. These students took 1 to 18 courses in the 2009–2010 academic years.

5.2. Variables Table 1 lists variables collected from Blackboard, the student demographic database, and the course evaluation survey. Some variables were transformed with calculations in order to generate more meaningful variables for analysis. For example, student’s birth year was transformed to age. The summary of all learning activities was aggregated to a new variable called “frequency of clicks” that represents each student’s total frequency of clicks in the Blackboard LMS. If students took

EITT 2013, Williamsburg, VA, USA, November, 2013 107 Proceedings of International Conference of Educational Innovation through Technology more than one course during the analysis period, variables of learning activities (e.g., frequency of total clicks and frequency of course access), performance (e.g., final grade), and survey (e.g., course satisfaction and instructor satisfaction) were averaged.

Table 1. Variables for data mining Variables Descriptions Category stuID Student’s ID Student Demographic Variable Age Student’s age Student Demographic Variable City Student’s residential city Student Demographic Variable District Student’s school district Student Demographic Variable Grade_Avg Average course grade Student Performance Variable Click_Avg Average frequency of clicks/course Student Engagement Variable Content_Access_Avg Average frequency of course content accessed/ Student Engagement Variable course Course_Access_Avg Average frequency of course accessed/course Student Engagement Variable Page_Access_Avg Average frequency of page accessed/course Student Engagement Variable DB_Entry_Avg Average number of discussion board entries/ Student Engagement Variable course Tab_Access_Avg Average frequency of tab accessed/course Student Engagement Variable Login_Avg Average frequency of logins/course Student Engagement Variable Module_Avg Average frequency of module accessed/course Student Engagement Variable Gender Gender Student Demographic Variable HSGradYear High school graduation year Student Demographic Variable School Student’s school Student Demographic Variable No_Course Number of course taken Student Demographic Variable No_Fail Number of course failed Student Performance Variable No_Pass Number of course passed Student Performance Variable Pass rate Average individual student pass rate for all Student Performance Variable courses in academic year 2009-2010 (>= 0 and <=1) cSatisfaction_Avg Average course satisfaction including 8 questions Student Perception Variable related to course content and 5 questions related to course structure iSatisfaction_Avg Average instructor satisfaction including 11 Student Perception Variable questions related to instructor.

5.3. Analytic Tools SAS Enterprise Miner 6.1 (SAS Institute Inc., USA) was employed to perform the following data mining tasks in this study: 1) student clustering which describes shared characteristics of students who passed or failed their course; 2) perception and performance predictions which identify key predictors of course satisfaction, instruction satisfaction, and final grade. Because one of the major target audiences of this article is K–12 administrators, the authors utilized methods like decision tree and K-means clustering, which can produce results more intuitive for non-data miners.

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6. Results 6.1. Student Clustering K-means algorithm (Hartigan&Wongm, 1979; Budayan, 2008) was applied to group students based on their shared characteristics (Internal Standardization = Range; Maximum Number of Clusters = 6).Total clusters were limited to avoid trivially small or exclusive groups, the identification of which was outside the purposes of this case study. A pass rate equal to “1” means a student passed all courses during the period of analysis. A pass rate equal to “0” means a student failed all courses during the period of analysis. A pass rate between “0” and “1” means a student passed some, but not all, courses during the period of analysis. In clustering analysis, pass rate was set up as the standard for classification and six clusters were generated.

Table 2 includes the results of clustering analysis in academic year 2009-2010. Table 2.Results of clustering analysis Variables CL1 CL2 CL3 CL4 CL5 CL6 Number of Students 316 320 594 601 2311 3397 Pass rate =0 0 0 594 601 0 0 Pass rate (>0 and <1) 316 320 0 0 0 0 Pass rate =1 0 0 0 0 2311 3397 GenderF 0 320 0 601 0 3397 GenderM 316 0 594 0 2311 0 Age 16.91 17.06 16.69 16.82 16.6 16.59 Grade_Avg 50.11 52.82 22.44 20.85 81.75 85.4 Click_Avg 583.15 549.09 440.17 416.4 892.49 881.69 Content_Access_Avg 112.96 112.2 93.78 89.43 180.34 177.96 Course_Access_Avg 170.26 172.29 133.94 141.52 281.5 284.22 DB_Entry_Avg 4.08 5.28 2.78 4.22 8.28 9.57 Login_Avg 29.4 24.35 23.58 19.18 47.92 46.42 Module_Access_Avg 156.18 145.02 112.7 102.38 249.16 240.79 Page_Access_Avg 99.61 89.39 71.97 62.46 145.43 142.42 Tab_Access_Avg 41.92 37.82 29.98 26.03 62.04 60.72 No_Fail 1.23 1.33 1.43 1.39 0 0 No_Pass 1.52 1.7 0 0 1.59 1.64 No_course 2.76 3.03 1.43 1.39 1.59 1.64

Findings below were summarized from the clustering analysis. 1). Students with higher engagement levels usually had higher performance. 2). Younger students (CLs 5 & 6) who lived in larger cities were more successful than those in smaller cities (CLs 3 & 4) and older students (CLs 1 & 2). 3). All-failed students who were also low-engaged consisted of approximately 15.9% on average per course. 4). All-passed students who were also high-engaged consisted of approximately 75.7% students on average per course. 5). Based on Cluster 1 and 2, on average, older students (age > 16.91) tended to take more than two courses with pass rates ranging from 54.09-56.11%.

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6). On average, high-engaged students demonstrated engagement levels twice that of low- engaged students. 7). Frequencies of reading behaviors (such as content access and page access) were much higher than discussion behaviors (p<0.001). 8). Female students were more active than male students in online discussions (with higher DB_Entryavg frequency). 9). Female students had higher pass rates than male students.

6.2 Average Clicks per Course in Different Subject Areas Table 3 shows students’ average frequencies of total clicks and performances per course in different subject areas. Total clicks were equal to the summarized frequency of overall learning activities. The results show that Math and Science had the highest number of total clicks per course and of total clicks per student per course. However, for those who took Math and/or Science courses, their average final grades (56.70 and 64.41 accordingly) were lower than the overall final grade average (71.11). This indicates students participated actively in courses of these two subject areas, but they failed to achieve expected outcomes (70 or higher). Possible reasons for this outcome could be related to course design and/or best practice in teaching strategies for Math and Science courses. On the other hand, English courses received a lower number of clicks combined with less than expected outcomes. Encouraging motivation and engagement in these courses could have a profound effect on future outcomes. Students in Foreign Language and Health not only participated in learning activities actively, but also obtained the highest grades, on average, in each of these two subject areas.

Table 3. Average frequencies of total clicks and performance in different subject areas Subject Areas Total Clicks Total Clicks/student No of Students Final Grade Drivers Ed 4,808.00 227.97 21.09 78.40 Electives 5,353.63 247.69 21.61 76.59 English 4,807.79 239.98 20.03 62.09 Foreign Language 7,824.63 439.40 17.81 76.54 Health 6,641.80 269.99 24.60 83.58 Math 7,898.35 444.05 17.79 56.70 Science 9,015.16 603.53 14.94 64.41 Social Studies 4,740.92 235.97 20.09 70.58 Average 6,386.29 323.43 19.75 71.11

6.3. Predictive Analysis CRT Decision Tree analysis (Breiman, Friedman, Olshen, & Stone,1984) was applied to construct predictive models combining course related data and survey results (Splitting Criterion: Gini; Leaf Size: 60; Maximum Depth: 10; Assessment Measure: Average Squared Error). These settings allow for a larger sequence of sub-trees in order to enrich the study’s findings. Decision Trees classifies instances by sorting them down the tree from the root to the leaf nodes. In the tree structures, leaf nodes represent classifications, and branches represent conjunctions of features that lead to different target values. The following three variables were adopted as dependent variables in the Decision Tree analysis: 1) Average course grade;2) average course satisfaction; and 3) average instructor satisfaction.

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• Average course grade is each student’s final course grade (range: 0-100). If a student took more than one course, average course grade is the average of multiple courses. • Average course satisfaction was generated by averaging the scores from eight survey questions related to course content and the five survey questions related to course structure (range: 1–7). If a student took more than one course, average course satisfaction is the average of satisfaction scores from multiple courses. • Average instructor satisfaction was generated by averaging the scores from 11 survey questions related to the instructor satisfaction (range: 1–7). If a student took more than one course, average instructor satisfaction is the average of satisfaction scores from multiple courses.

6.3.1. Final grade prediction All variables in Table 1 were imported for final grade prediction. Average course grade was used as the dependent variable and the remainders were treated as independent variables. Because the tree results contained too much information, blank nodes were used to represent the results excluded from the data interpretation. Figure 3 shows the decision tree for final grade prediction. In academic year 2009-2010, 75.7% of students passed all courses, 15.9% of students failed all courses, and 8.4% passed some but not all of their courses. The left branch of the decision tree represents students who passed all courses. The results indicate a positive correlation between engagement level and performance (higher engaged => higher performance). The right branch of the decision tree represents students who had failed in one or more courses. The results imply a negative correlation between engagement level and performance (lower engaged => lower performance).

More results of predictive analyses will be presented in the conference, including performance prediction with external variables and course/instruction satisfaction prediction.

7. Discussion This study is a first attempt at program evaluation combining multiple data sources. The goal of this project was to propose a new program evaluation framework in order to generate sufficient information for program-level decision-making. The advantages of this framework are data triangulation and data interpretation. Overall, using multiple forms of data allows for a more meaningful analysis of actual student behaviors, and the identification of potential relationships with demographic data, satisfaction data, and student outcomes. The result is a much richer and deeper analysis of student performance and teaching, as well as of effective course design, than could ever be accomplished with survey data or behavior mining alone.

7.1. Demographic and Performance Based on results revealed by the program evaluation framework, some indicators can be applied to identify students more likely to be successful and those more likely to be at-risk. In this study, a student who possessed more of the characteristics listed below was more likely to be at risk of failure: ● Male ● Older than 18 years ● Took more than two courses per semester ● Took entry-level courses in Math, Science, or English ● Lived in a smaller city

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Figure 2. Final grade prediction (complete chart: http://goo.gl/NIfWu)

These indicators can be applied to develop an early warning system (Macfadyen& Dawson, 2010), so administrators and teachers can have a list of successful and at-risk students before each semester starts.

7.2. Engagement and Performance Based on data mining analysis, higher-engaged students usually had higher performance. This finding is also supported by previous studies (e.g., Hung & Crooks, 2008; Hung & Zhang, 2009). However, the conclusion may be limited to courses which were well designed and implemented. Lim & Morris (2009), when studying post-secondary students, found junior and senior students had significantly higher survey mean scores in perceived learning, learning application, and learning involvement than freshman and sophomore students. Assuming higher perceived learning, learning application, and learning involvement equates to high motivation, the authors could not explain why older students had significantly higher engagement than young students. Our study, by combining analysis of engagement and performance through data mining with survey responses, revealed why students had different levels of engagement and performance. For example, the majority of responses from the students enrolled in courses categorized as high engagement and high performance were, “The course was not available in my school.” Meanwhile, the majority of responses from students in courses that were categorized as low engagement and low performance were, “I was making up a class I had failed.” The level of engagement in our study may have been influenced by motivation. In addition, Lim & Morris (2009) found older students had a better chance to be successful in online learning at the higher education level. However, our study found older students were more likely to be at-risk students in K-12 online education. Students older than 18 tended to be low engaged and lower performing in their courses.

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References Astin, A. W. & Lee, J. J. (2003). How risky are one-shot cross-sectional assessments of undergraduate students? Research in Higher Education, 44(6), 657–672. Becker, K., Ghedini, C., & Terra, E. (2000). Using KDD to analyze the impact of curriculum revisions in a Brazilianuniversity. Proceedings of Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, 4057, 412–419. Blackboard Inc. (2010). Blackboard database schema. Retrieved from http://library.blackboard. com/ref/fea8bb86-1720-4b14-bb81-542d973b5338/ Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and regression trees. Wadworth International Group. Cheng, D. X. (2001). Assessing student collegiate experience: where do we begin? Assessment and Evaluation in Higher Education, 26(6), 525–38. Delavari, N., Phon-amnuaisuk, S., &Beikzadeh, M. (2008). Data mining application in higher learning institutions. Informatics in Education, 7(1), 31–54. Eiszler, C.F. (2002). College students’ evaluations of teaching and grade inflation. Research in Higher Education, 43(4), 483–501. Elster, J. (1983). Sour grapes: Studies in the subversion of rationality. Cambridge, UK: Cambridge University Press. Grammatikopoulous, V. (2012). Integrating program theory and systems-based procedures in program evaluation: A dynamic approach to evaluate educational programs. Educational Research and Evaluation, 18(1), 53–64. Hartigan, J.A.,&Wong, M.A. (1979), Algorithm AS136: A k-means clustering algorithm, Applied Statistics, 28, 100–108. Hermans, C. M., Haytko, D. L., & Mott-Stenerson, B. (2009). Student satisfaction in web-enhanced learning environments. Journal of Instructional Pedagogies, 1(1), 1–19. Hoffman, K. M. (2003). Online course evaluation and reporting in higher education. New Directions for Teaching and Learning, 96, 25–29. Hung, J. L., & Crooks, S. (2009). Examining online learning patterns with Data Mining techniques in peer-moderated and teacher-moderated course. Journal of Educational Computing Research, 40(2), 183–210. Hung, J. L.,& Zhang, K. (2008). Revealing online learning behaviors and activity patterns and making predictions with data mining techniques in online teaching. MERLOT Journal of Online Learning and Teaching, 4(4), 426–437. Jick, T. (1979). Mixing qualitative and qualitative methods: Triangulation in action. Administrative Science Quarterly, 24, 602–611. Ladebo, O. J. (2003). Relationship between Agricultural trainees’ performance and satisfaction with academic program. Journal of International Agricultural and Extension Education, 11(1), 55–60. Lim, D.H.,& Kim, H.J. (2003). Motivation and learner characteristics affecting online learning and learning application. Journal of Educational Technology Systems, 31(4), 423–439. Lim, D. H., & Morris, M. L. (2009). Learner and instructional factors influencing learning outcomes within a blended learning environment. Educational Technology & Society, 12 (4), 282–293. Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an early warning system for educators: a proof of concept. Computers and Education, 54, 588–599.

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Nasser, F.,&Hagtvet, K. A. (2006). Multilevel analysis of the effects of student and instructor course characteristics on student ratings. Research in Higher Education, 47(5), 559–90. Nichols, J. O. & Nichols, K. W. (2000). The departmental guide and record book for student outcomes assessment and institutional effectiveness, 3rd edition. New York: Agathon Press. Panov, P., Soldatova, L., & Dzeroski, S. (2009). Towards an ontology of data mining investigations. Lecture Notes in Artificial Intelligence, 5808, 257–271. Picciano, A. G. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal of Asynchronous Learning Networks, 6(1), pp. 21–40. Roiger, R. J., & Geatz, M.W. (2003). Data mining: a tutorial-based primer. Boston, MA: Addison Wesley. Romero, C., & Ventura, S. (2010). Educational data mining: A review of the state of the art. IEEE Transactions on Systems Man and Cybernetics Part C: Applications and Reviews, 40(6), 601– 618. Spirduso, W. & Reeve, T. G. (2011). The national academy of Kinesiology 2010 review and evaluation of doctoral programs in Kinesiology, Quest, 63(4), 411–440. Ueno, M. (2006). Online outlier detection of learners’ irregular learning processes. In C. Romero & S. Ventura, (Eds.), Data Mining in E-learning (pp. 261–278). Billerica, MA: Wit Press. Vogt, F. D. & Slish, D. (2011). A model for programmatic evaluation by student assessment. Journal of Science Education and Technology, 20, 796–802. Wu, K.W. & Leung, C. H. (2002). Evaluating learning behavior of web-based training (WBT) using web log. Proceedings of International Conference on Computers in Education. NewZealand, 736–737.

114 EITT 2013, Williamsburg, VA, USA, November, 2013 Chiang. T., Yang, S., Liu, V., & Lin, C. (2013). A mobile augmented reality system enhanced inquiry-based strategies to improving students’ learning achievement in natural science learning. Proceedings of International Conference of Educational Innovation through Technology, 115-120.

A Mobile Augmented Reality System Enhanced Inquiry-based Strategies to Improving Students’ Learning Achievement in Natural Science Learning

Tosti H.C. Chiang, Stephen J.H. Yang, Vivi C.H. Liu, Cynthia Y.C. Lin

National Central University Email: [email protected]; [email protected]; [email protected]; [email protected]

Abstract: This study exams the influence that inquiry-based learning strategies supplemented by a location- based mobile augmented reality (AR) system have on students’ learning achievement. Inquiry-based learning strategies were employed for teaching, and the teaching activities were divided into five steps: ask, investigate, create, share, and reflect. The test subjects were fourth grade students approximately between 9 and 10 years of age from an elementary school in Northern Taiwan. A total of 57 students from two classes taught by the same teacher were selected. The test material was a fourth grade natural science unit on aquatic animals and plants. The test results show a significant difference in the learning effectiveness achieved using the new learning method involving inquiry-based learning strategies supplemented by a mobile AR system.

Keywords: augmented reality, mobile learning, inquiry-based learning, natural science

1. Introduction In recent years, computer-assisted and web-based learning systems have been widely developed (Yeh, Chen, Hung, & Hwang, 2010). These learning systems typically incorporate new learning strategies with an appropriate learning environment, such as computer learning supplemented by scaffolding learning strategies, and real-life learning situations supplemented by active learning and action learning strategies. These strategies are widely employed in the classroom. Numerous studies show that computer-assisted and web-based learning systems effectively increase learners’ learning motivation. Recently, researchers have combined handheld devices with sensor technology to implement more effective learning methods. Chu, Hwang, Huang, and Wu (2008) developed a learning system that enables learners to learn about the characteristics and life cycle of plants on campus using mobile communication and sensor technologies. Learning has evolved from traditional methods to new strategies that combine digital technology with real environments (Yang, Chen, 2008). Because of location-based learning and experiential learning, sensing technology has been extended and applied to outdoor learning, and these learning methods are suitable for real-life environments (Chu, Hwang, Tsai, & Tseng, 2010; Yang, 2006).

The previously mentioned mobile learning devices emphasize the adoption of digital learning aids in real-life scenarios. Thus, regarding supplementary mobile learning aids, the interaction between digital learning aids and the actual environment must be emphasized to enable learners to effectively manage and incorporate personal knowledge (Yang, Okamoto & Tseng, 2008). For example, learners can select a virtual learning object from the actual environment using a mobile learning aid, allowing them to obtain a first-hand understanding of the learning environment and, subsequently, increasing their learning motivation and experience. This type of technology

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 115 Proceedings of International Conference of Educational Innovation through Technology is achievable through the application of augmented reality (AR), which enables human senses (e.g., sight, sound, and touch) to be combined with virtual objects and facilitates real environment interaction for users to achieve an authentic perception of the environment (Azuma, 1997). In addition, AR can provide differing levels of immersion and interaction to benefit learning activities. A comprehensive range of studies have documented the application of AR in learning.

Thus, this research raises the following research question which is significant differences in learners’ learning achievement using the new learning method of inquiry-based learning supplemented with mobile AR?

2. Literature Review 2.1 Inquiry-Based Learning Inquiry-based learning is a learning activity that involves the teacher encouraging students to proactively hypothesize, explore, validate, categorize, explain, and discuss everyday situations or problems encountered. Through hypothesizing, exploring, and observing, learners develop advanced social interaction skills and a higher level of thinking. Inquiry-based learning enables learners to not only develop a deeper level of thinking when encountering learning situations but also to learn how to implement the process of learning (NRC,2000). Lim (2004) contended that during the process of conducting learning tasks, online inquiry-based learning allows learners to develop confidence regarding participating in activities, cultivate teamwork abilities, and feel greater responsibility in controlling their learning progress. Colburn (2000) defined inquiry-based learning as a method that comprises many open, student-centered, and hands-on approaches, including structured inquiry, guided inquiry, open inquiry, and the learning cycle. These approaches enable students to identify connections on various levels and to integrate and collate information. The instructor then provides the students with relevant concepts, and after this knowledge is assimilated, students are able to apply it in other contexts. Inquiry-based learning is also applied in the social sciences. Lakkala, Lallimo, and Hakkarainen (2005) combined history classes with inquiry-based theory for implementation in 12 elementary and junior high schools. Shih, et al (2010) integrated inquiry based theory with mobile devices to assist students in understanding the culture associated with temples.

2.2 Augmented Reality AR is a technology that allows users to combine real-life sensory experience with digital environment perceptions. Although AR and virtual reality (VR) are similar hardware technologies, their fundamental difference is that VR attempts to replace the real world, whereas AR enhances one’s perception of reality (Azuma, 1997). According to Azuma, Baillot, Behringer, Feiner, Julier, & MacIntyre (2001), the three characteristics of AR are (a) real and virtual objects incorporated into reality; (b) collaboration between real and virtual objects, and (c) real-time interaction between real and virtual objects.

Educators and researchers anticipate applying emerging technologies, such as AR and multiple- user VR, to teaching and learning activities (Dalgarno & Lee, 2010; Dunleavy, Dede, & Mitchell, 2009). The sensory experience and interaction and guiding functions of these technologies can improve learners’ learning satisfaction and enable them to structure their knowledge and complete learning tasks. Furthermore, a number of researchers propose that mobile AR devices have unique

116 EITT 2013, Williamsburg, VA, USA, November, 2013 A Mobile Augmented Reality System Enhanced Inquiry-based Strategies to Improving Students’ Learning Achievement in Natural Science Learning applications in education, such as improving the success rate of physical interaction-related learning tasks and supporting memory-related learning activities (Chien, Chen, & Jeng, 2010; Dunleavy, Dede, & Mitchell, 2009).

3. Learning strategies for experimental group The research approach used in this study was inquiry-based learning strategies supplemented with mobile location based AR. The strategies adopted by Bruce and Bishop (2002) were employed for the experimental design, and the design criteria of the inquiry-based learning model were divided into the following five steps (Fig 1): (a) Ask: The instructor first defines the learning objects and allows learners to search for them to cultivate their proactivity. The purpose of this step is to enable learners to search for the learning objects, which are then continuously redefined throughout the cycle of inquiry- based learning. (b) Investigate: In this step, learners are naturally guided to continuously investigate the learning content using their curiosity. Learners can reference the learning aids to understand various aspects of the learning content. When the content is understood, learners can redefine the learning object or simplify the object by dividing it into smaller components. (c) Create: After the completion of learning object investigation, the learners form connections among the learning content to create an internalized new knowledge. (d) Sharing: After the first three steps are performed, learners share their learning experiences and explore the entire learning process. (e) Reflect: Learners can rethink the initially defined learning objects, the direction of inquiry and confirm the accuracy of the conclusion.

Figure 1. Learning activity

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4. Experiment Design The participants of this experiment were fourth grade students from an elementary school in Northern Taiwan. A total of 57 students were included in this study, and they ranged between 9 and 10 years of age. These students were from two classes, one class was set as the experimental group, and the other class was set as the control group. The same instructor was responsible for both classes.

The experiment material used in this study was a fourth grade natural science unit on aquatic animals and plants, which was divided into four sections, specifically, Section 1: Water habitats; Section 2: different types of aquatic plants; Section 3: different types of aquatic animals; and Section 4: the secret of aquatic plants. Each section contains learning themes, for example, water habitats comprised the two themes of natural habitats and manmade habitats; natural habitats include lakes, rivers, marshes, coastal intertidal zones, and lake intertidal zones; manmade habitats include ponds, dams, and irrigation ponds. Water plants comprised the following four themes: emergent plants, submerged plants, floating-leaf plants, and floating plants.

In this study, the measuring tools were a pre-test, a post-test for measuring the learning achievement of the group regarding the natural science course. The pre-test aimed to ensure that the two groups of students had an equivalent basic prior knowledge of the natural science course content. It consisted of thirty multiple-choice items with a perfect score of 100 for evaluating the students’ prior knowledge of aquatic plants. The post-test contained thirty multiple-choice items for assessing the students’ knowledge of identifying and differentiating the plants on the school campus.

5. Result Before the experiment, the two groups took a pre-test to ensure that they had equal abilities in this subject before the learning activity. The mean and standard deviation of the pre-test were 46.46 and 13.220 for the experimental group, and 44.97and 15.546 for the control group. The t-test result showed that these two groups did not differ significantly (t = 0.391, p > .05); that is, the two groups of students had statistically equivalent abilities before learning the subject unit.

After participating in the learning activity, the two groups of students took a post-test. The t-test result shows that the average learning achievement of the experimental group is significantly better than that of the control group (t= 2.046, p< .05), as shown in Table 1.

From the above results, learning achievement of a mobile augmented reality system with inquiry-based strategies is better than traditional learning in natural science learning.

Table 1. t-test results of learning achievement between two groups Variable Group N Mean S.D. Std. error t Post-test Experimental group 28 80.14 8.763 1.656 2.046* Control group 29 73.93 13.703 2.545 *p<.05, **p<.01, ***p<.001

118 EITT 2013, Williamsburg, VA, USA, November, 2013 A Mobile Augmented Reality System Enhanced Inquiry-based Strategies to Improving Students’ Learning Achievement in Natural Science Learning

6. Discussion and conclusion The learning activity of the experimental group involved a fourth grade natural science unit on aquatic plants. The instructor first defined the learning object as water hyacinths, then guided learners to use mobile AR to determine the location of the learning object. After the learners had reached the location of the water hyacinths, information related to the learning object was presented by the handheld device. Then, the instructor used the questions displayed on the handheld device to guide the learners to conduct observations of the environment. Subsequently, the learners observed the characteristics of water hyacinths within the time stipulated by the instructor. During the observation process, the learners could use the camera function of the handheld device to take photographs of the water hyacinths and share their observation results with their peers. The learners could also use the footnote function to note their perceptions and share their findings with their peers to verify their understanding. After the observations were complete, the instructor employed the learning progress system to provide information related to water hyacinths for the learners. During this process, the instructor reiterated the main concepts of water hyacinths and encouraged the learners to examine each other’s findings and held conduct discussions regarding the learning content. Through sharing, the learners could determine whether method adjustments were required to understand the material and whether their understanding was similar to that of their peers. This also enabled the instructor to determine whether the learners were experiencing difficulties during the learning process. After interacting with their peers, the learners conducted in- depth reflections on the newly learned information. Through the process of reflection, knowledge was further comprehended and memorized, which enhances learning effectiveness.

This study attempted to establish a new learning method by supplementing inquiry-based learning strategies with mobile AR. Comparing the experimental group and control group, a significant difference in learning achievement was observed. This study infers that during the processes of sharing and reflecting, the learners assimilated the findings of their peers, enhancing their learning achievements.

The results of this study show that inquiry-based learning strategies supplemented with mobile AR technology are beneficial for conducting outdoor observations, which can effectively enhance learners’ learning motivation and increase their knowledge of aquatic plants. Future studies should further investigate enhancing the aspects of the ARCS model of motivation (i.e., Satisfaction) in the design of learning activities to facilitate the development of additional scenario-based learning modules.

References Azuma, R. T. (1997). A Survey of augmented reality. In Presence: Teleoperators and Virtual Environments, 6, 355-385. Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S., & MacIntyre, B. (2001). Recent advances in augmented reality. IEEE Computer Graphics and Applications, 21(6), 34–47. Bruce, B. C. & Bishop, A. P. (2002). Using the web to support inquiry-based literacy development. Journal of Adolescent & Adult Literacy, 45(8), 209-221. Chu, H. C., Hwang, G. J., Huang, S. X., &Wu, T. T. (2008). A knowledge engineering approach to developing e-libraries for mobile learning. The Electronic Library, 26(3), 303–317. Chu, H. C., Hwang, G. J., & Tsai, C. C. (2010). A knowledge engineering approach to developing mindtools for context-aware ubiquitous learning. Computers & Education, 54(1), 289-297.

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Chien, C., Chen, C., & Jeng, T. (2010). An interactive augmented reality system for learning anatomy structure. Computer, I. IAENG. Colburn, A. (2000). An inquiry primer. Science Scope, 23, 139−140. Dalgarno, B. & Lee, M. J.W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32. Dunleavy, M., Dede, C., & Mitchell, R. (2009). Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. Journal of Science Education and Technology, 18(1), 7–22. Lakkala, M., Lallimo, J., & Hakkarainen, K. (2005). Teachers’ pedagogical designs for technology- supported collective inquiry: A national case study. Computers & Education, 45(3), 337-356. Lim, B. R. (2004). Challenges and issues in designing inquiry on the Web. British Journal of Educational Technology, 35(5), 627- 643. National Research Council. (2000). Inquiry and national science education standards. Washington, DC: National academic Press. Price, B. (2001). Enquiry-based Learning: an introductory guide. Nursing Standard, 15(5), 45-52. Shih, J. L., Chuang, C. W., & Hwang, G. J. (2010). An Inquiry-based Mobile Learning Approach to Enhancing Social Science Learning Effectiveness. Journal of Educational Technology & Society, 13(4), 50-62. Yang, S. J. H., (2006). Context aware ubiquitous learning environments for peer-to-peer collaborative learning. Educational Technology & Society, 9(1), 188-201. Yang, S.J.H., Chen, I.Y.L. (2008). A social network-based system for supporting interactive collaboration in knowledge sharing over peer-to-peer network. International Journal of Human-Computer Studies, 66(1). 36-50 Yang, S. J. H., Okamoto, T., & Tseng, S. S. (2008). A matter of context-aware ubiquitous learning. Journal of Educational Technology & Society, 11(2), 1-2. Yeh, Y. F., Chen, M. C., Hung, P. H., & Hwang, G. J. (2010). Optimal self-explanation prompt design in dynamic multi-representational learning environments. Computers & Education, 54(4), 1089-1100.

Acknowledgement This work is supported by National Science Council, Taiwan under grants NSC101-2511-S- 008-001-, NSC99-2511-S-008-006-MY3, and the Research Center for Science & Technology for Learning of the University System of Taiwan.

120 EITT 2013, Williamsburg, VA, USA, November, 2013 Wang, Z., Yang, L., & Li, H. (2013). Design and development of educational game based on RETAIN model. Proceedings of International Conference of Educational Innovation through Technology, 121-128.

Design and Development of Educational Game Based on RETAIN Model

Zhijun Wang Tianjin Normal University Email: [email protected]

Lingling Yang Tianjin Normal University Email:[email protected]

Hong Li Tianjin University of Traditional Chinese Medicine Email: [email protected]

Abstract: Recently, The development of game industry is very fast. Educators begin to change the view on the game in the conflict between “Intercept” and “guide” for young people addicted to the game. They hope the game with such a large attraction for young people having educational nature. So, educational games emerged around us. The study of educational games has been made some achievements in other countries, while Chinese educational game is just started, and lack of a workable educational game design model and design theory. This thesis brings in the RETAIN model, which is worked out by two scholars of the University of Florida, USA. The article make a restructuring and refinement to every element of the RETAIN model for educational game design and development, and obtain 12 points about educational game design. Besides educational game design and development process be put forward based on the RETAIN model points, the educational game design strategy and instructional system design and software design processes. And focusing on the 10-12 year-old primary students, developed an educational game instance about knowledge of safety education, called “Dangerous Fantasy”.

Keywords: educational game; RETAIN model; refined analysis; case design

1. Development of Educational Games in China In recent years, the game industry has developed rapidly in China, how to make the game to play an educational role becomes the concern of educators. According to a survey report: Most Chinese teenagers of all ages have played online games. 74.8% of pupils who played online games; 81.2% of junior high school students who played online games; 77.9% of high school students who played online games while college students was 73.7%. All of the surveyed Chinese youths played online games percentage was 79.3%. All young people who had played online games spend 5.35 averages per week play games, while play online games weekly average number of 1.82 times (Cultural Market Development Report of China, 2007).

Visible online games great influence on young people, the combination of online games and education also contains a huge educational and business opportunities. In the United States, Canada, Britain, South Korea, Japan and other countries have formed a certain game norms and

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 121 Proceedings of International Conference of Educational Innovation through Technology system, and hence the quality of educational games is relatively high. Such as the U.S. Game2Train company has been focusing on the development of games based learning software, has developed a series of digital learning games, widely used in education and training, and its products are divided into Internet / Intranet, videogame tutorials, and enhanced classroom three categories. Canada Inlight Entertainment game development company is a specialized company developing educational games for children, they put people familiar with the Disney star who “invited” into the game, such as Winnie the Pooh, Mickey Mouse, etc., so that they become the protagonist of the game, with kids learn while playing.

In China, however, due to lack of cooperation of educators and game developers, educators lack of knowledge of game design, and game developers lack of knowledge of teaching theory, resulting in educational games can’t satisfy learners. There are many problems of educational games in China. For example, educational games design theories rich, but not theoretical research into the system and poor operability; educational games for its design objects, the majority of youth-oriented, so many professional game development company attaches importance to the development of image and sound, in order to attract young people, but they ignore the game’s instructional design. One of the most prominent is that education and game combined with a stiff, unable to achieve the natural integration of education and games. We learn from RETAIN model, hope we can get the method to solve the above problems of Chinese educational games.

2. The RETAIN Model RETAIN model (Gunter & Kenny, 2008) provides a theoretical guidance for the design of educational game. RETAIN model consists of six parts: Relevance, Embedding, Transfer, Adaptation, Immersion and Naturalization. These six words’ first letters make up RETAIN model’s name. The model is based on the principles of instructional design and game design, appropriate use of Keller’s ARCS model, Gagné’s Nine Events and Scaffolding Principles of Bruner.

3. Restructuring and Refinement to Every Element of RETAIN Model 3.1. Relevance 3.1.1. Appropriate situational creation. The situational of educational game refers to learning environment for learners, but it’s different from the traditional learning environment. Educational game’s learning environment is presented through the story, characters and scenes design. Unreal story should provide learners with a real experience of the situation; learners can feel in the game with their real life, emotions, movements, skills, values, ethical standards that is to give learners with real-world similar experience. Story context settings need to consider the preferences and style of the learners, in order to arouse the learners’ attention. Younger learners like the cartoons, color pictures, interesting stories, while older learners like being able to stimulate their thinking about the problem.

3.1.2. Correlation between learning units. Learning content of educational games can’t be too easy or too difficult, should be an easy to difficult process, and has some relevance and proper use of “Advance Organizer”. Ausubel suggests that to achieve meaningful learning can have two different ways: reception learning and discovery learning. Educational game’s meaningful learning through discovery learning to achieve. In the specific design, the contents of the educational games should be carefully designed, there must be the guide of help or assistance should refer to the

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correlation between the various units of the game and between the various stages of the game. In the design of educational game should be appropriate to give the learners some help, provide advance organizers to play a guiding role.

3.2. Embedding 3.2.1. Story contains learning content. Embedding requires learning content of the educational game should be carried by story, refusing to learning contents add to the game blunt. Efforts to make the learners’ attention and emotions fully invested in the educational games. Fully taking into account the characteristics of “relevant”, select the appropriate contexts and themes, designed to meet the learners’ cognitive characteristics of characters and scenes should be considered while designing. At the same time, reasonable embedding can stimulate learners’ interest in learning. So that students think educational game as game rather than as educational software.

3.2.1. Decomposition of learning goals. We should have the overall learning goals, as well as the detailed sub-goals at all levels. Learning is much more natural capacity to integrate into the game process can be more operational with target decomposition. The formulation of learning goals should be a low to high, the initial target to take into account the learner’s initial level of difficulty can’t be too large. In the process of decomposition of goals should be considered to develop learners’ confidence and sense of achievement, in order to stimulate and maintain learner motivation.

It can be said, “Relevance” and “Embedding” are complementary. In the design of educational game, we need to consider these two characteristics, designed according to the relevant elements of the educational game.

3.3. Transfer and Adaptation Because “Adaptation” is a follow-on concept to “Transfer”, we analyzed these two elements together.

3.3.1. Similar content. After learners learned knowledge or skills through educational game, educational game design needs some similar content presented to the learner, this presentation is to achieve through the stage of the game the difficulty of upgrading. On one hand, this approach allows the learners to consolidate the already learned knowledge or skills; the other hand, this approach can develop the knowledge of learners have learned. Therefore, you need to gradually increase the difficulty of the challenge, not for the baffled learners, but in order to expand their cognitive structure.

3.3.2. New content. Learners can’t only stay in their existing cognitive structure, they need new content. New content for the learners is not entirely unfamiliar, can draw on the learning styles or ways of thinking that learners have learned. Piaget’s Cognitive development theory suggests that the assimilation of individuals outside information into the existing cognitive structure of the process, but this information with the existing cognitive structure is not very consistent, and then the individual is necessary to change the cognitive structure, shall comply with this process. Similar content in educational game requiring learners’ assimilation process, the new content in educational game need learners conform. In addition, Ausubel suggests promoting meaningful

EITT 2013, Williamsburg, VA, USA, November, 2013 123 Proceedings of International Conference of Educational Innovation through Technology learning to occur and to maintain the most effective strategy is the use of advance organizer on the new content is directed guidance. Advance organizer will not only help to establish a meaningful learning, but also help learners to recognize learned the contents of the mind which part of the original cognitive structure have substantive contact. In the design of educational game, new content should be appropriate to reduce the difficulty of the educational games, and to provide learners with the task guidance or help. That is: advance organizers, to ensure that the learner is able to smoothly the learning of new content.

3.3.3. Duplicate content. Duplicate content in educational game, including two meanings: First learning the contents of the repetitive learning or repeat the operation of the educational game, its main purpose is to consolidate the learners have learned the knowledge so that students the operation is more flexible; second is to provide learners with the opportunity to re-try the game, its main purpose is to encourage independent learning, and constantly found. Specific educational game design each game stage appropriate content to repeat the need to provide learners with the chance to start for a problem or hurdle, especially for new content, in particular, need try again opportunities.

“New content”, “similar content” and “duplicate content” relationship between the three should be shown below (Figure 1), is a cyclic iterative process. “Transfer” and “Adaptation” to the two elements to achieve the learners in the learning process “balance - imbalance - a new balance” state can continue to expand, and improve the learners’ existing cognitive structure, to achieve meaningful learning.

Figure 1. “New content”, “similar content” and “duplicate content” relationship

3.4. Immersion Immersion is based on (Csikszentrnihalyi, 1975) flow experience. And flow experience is used in game design widely. So we introduce flow experience and flow theory, hoping to further improve the RETAIN model.

Flow theory is an important foundation of the game design theory (Csikszentrnihalyi, 1975), they found in the “creation”: “when people engaged in their favorite work experience a special physical and mental experience, it often makes people sleepless nights, without paying, threw themselves into it, and enjoy amazing burst of creativity.” Later research (Jegers, 2007) has shown that people often get the game immersion experience in playing computer games; one important

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reason for this is really a player bored. The degree of immersion is the key to the success of the measure of a game design. Educational game also needs flow theory, play the advantages of educational games so that students can throw themselves in learning, and to maximize learning efficiency and learning depth. Flow experience includes nine elements (Novak, 2000): clear goals, unambiguous and immediate feedback, skills that just match challenges, t merging of action and awareness, concentration and focus, a sense of potential control, a loss of self consciousness, an altered sense of time, an auto telic experience. The first three elements is a prerequisite for flow experience, the middle three elements is characteristics of flow experience, the last three elements is results of flow experience.

3.4.1. Clear goals. The clear goals are the meaning of “engaged in an activity, every step has a clear and specific target for the learners who are very clear to know how to do next.” This requires the design of educational game should provide learners with clear goals; task-driven approach can be straightforward to achieve this goal. On one hand, learners know teaching goals clearly. On the other hand, learners know the things what should be done next.

3.4.2. Unambiguous and immediate feedback. Unambiguous and immediate feedback means learners clearly know how the progress of activities, each step can get immediate feedback. Learners to make a timely and direct evaluation of their own learning goals completed, in order to know if learners have achieved the goals. Therefore, in the design of educational game, we need design timely feedback.

3.4.3. Skills that just match challenges. Skills that just match challenges mean learners need certain skills to deal with the challenges and to solve the problems when they face with particular challenges. The relationship of Challenge and skill is shown below (Figure 2).

Figure 2. Different experiences of the players in the game (Sui, 2010)

Longitudinal axis is challenge and horizontal axis is players’ abilities. The middle curve represents the player gains experience; while the gray is the area which players can get flow experience. It can be seen from the figure: when the challenge is too difficult, but players’ abilities is poor, players will anxiety; when the challenge is easy but abilities better, can’t produce the flow experience, players will have a tired feeling. Therefore, only when challenges and skills phase equilibrium in order to achieve the state of immersion. In educational game, the skills of the learners into two categories: The first category is related to the operation of educational

EITT 2013, Williamsburg, VA, USA, November, 2013 125 Proceedings of International Conference of Educational Innovation through Technology games skills, such as a mouse use, the understanding of the rules of the game; the second is the ability to apply knowledge to solve problems. The first category skills can be improved through repeated simple exercises, while the second category is the active construction process of the learners; learners eventually need to learn skills. Learners have to face the challenges, the same divided into two categories, one is the challenge of the game operation, and the other learning challenges. In educational game, first category challenges should not too complicated, so that the challenges of educational games focused on the learning content. In addition, Vygotsky believes that teaching must meet the age characteristics of children in child development. Therefore, the users’ characteristics of educational games should be analysis, in order to develop a suitable design for users.

3.5. Naturalization Naturalization is to be achieved through the design of educational game: the habitual use of knowledge, or even to achieve the ideal state does not require conscious control. Currently, naturalization very difficult to achieve, but the habitual use of knowledge is easier to achieve.

3.5.1. Repeat motivation. We must first set the repeat operation in the education gameto achieve habitual use of knowledge, “practice makes perfect” is precisely this reason. Repeat can not only deepen learners’ understanding and use of knowledge, but also increase their sense of accomplishment of the educational games. According to Keller’s ARCS model, the sense of accomplishment to be able to stimulate and maintain learner motivation.

3.5.2. Applied to new scenarios. After the content has been studied repeatedly to achieve the “Naturalization” state, learners’ more mental resources can be used to obtain new content. The one hand, the working memory to accept, hold, in the process of processing information has a certain capacity limits, if the information of the output exceeds this capacity, information processing will be affected to some degree, can’t even be processed. On the other hand, “note” studies have shown that people carrying out the controlled processing in the same room can only be effectively carried out a mental activity, a number of tasks only time-sharing. It is difficult to process a variety of information because limited resources of working memory capacity and attention (Jinbo, 2009, p.6-7). Based on cognitive load theory, if the learners are able to intellectual understanding reaches a naturalized state, will not have to redistribution of the more cognitive resources, it can be more working memory and attention allocated to the new learning content.

We can be found that RETAIN model elements are not mutually independent. There is a close link between them, especially the relationship between the main points of the elements (Figure 3). Guidance based on in-depth analysis of RETAIN model, the educational game design and development process should follow the general rules and processes of instructional system design, software design and game design. Therefore, the educational game design and development process are: prophase analysis, educational game’s goals analysis, details design of educational game, educational game development, evaluation and modification of educational game, educational game’s promotion and application. Not mutually independent in all of the above development between the parts, they constitute an organic educational game design and development system, shown in Figure 4.

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Relevance Appropriate situational creation Correlation between learning units

Embedding Story contains learning content Decomposition of learning goals

Transfer and Adaptation Similar content New content Duplicate content

Immersion Clear goals Unambiguous and immediate Unambiguous and feedback 馈 immediate feedback

Naturalization Repeat motivation Applied to new scenarios

Figure 3. Relationship between the main points of the RETAIN model elements

Prophase analysis

Educational game’s goals analysis

Details design of educational game Genre choice Story design Rules design Modify Game Elements design Checkpoints and task design Others

Educational game development

Evaluation and modification of educational game

Educational game’s promotion and application Figure 4. Educational game’s design and development system

5. Development of Educational Game Case Based on RETAIN Model Name: Dangerous Fantasy Learning content: the daily safety knowledge Learners: 10-year-old to 12-year-old primary school students Learning goals: to know and be able to use the knowledge of traffic safety, electrical safety knowledge, fire safety knowledge, knowledge of social security and natural disasters, safety knowledge that can avoid the daily life in a variety of man-made and sophisticated non-human, to ensure their own and others health and safety. Genre: AVG-RPG Tools: Flash, also used RPG Maker and Photoshop.

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6. Conclusion China in the field of educational game development is still in its infancy, actionable educational game design model and design theory is still relatively lacking. Through in-depth analysis RETAIN model, hope to explore an effective operational program.

References Csikszentmihalyi, M. (1975). Play and Intrinsic Rewards. Journal of Humanistic Psychology, 15(3). Cultural Market Development Report. (2007). Online Game and contemporary adolescent development: Situation and Countermeasures (a). Retrieved from: http://www.ccm.gov.cn/ show_zt.php?aid=4596&tid=399 Gunter, G. A., Kenny, R. F. & Vick, R. H. (2008). Taking educational games seriously: using the RETAIN model to design endogenous fantasy into standalone educational games. Educational Technology Research and Development, ( 5). Jegers, K. (2007). Pervasive Game Flow: Understanding player enjoyment in pervasive gaming. Computers in Entertainment, (1). Lee, J. B. (2009). Cognitive load assessment and change projections: A case study of e-learning. Wuhan: Wuhan University Press, 6-7. Novak, T.P. & Hoffman, D.L. (1999) Measuring the customer experience in online rnvironment: a structural modeling approach. Marketing Science, 19(1). Sui, Z. H. (2010). Dynamic design of difficulty based on the flow theory of educational games. Xi’an: Shaanxi Normal University.

128 EITT 2013, Williamsburg, VA, USA, November, 2013 Hou, J. ,Zhang, K., & Qi, Y. (2013). Model design and effects research of tutor-directed online teaching. Proceedings of International Conference of Educational Innovation through Technology, 129-140.

Model Design and Effects Research of Tutor-directed Online Teaching

Jianjun Hou, Kuiyuan Zhang, Yanli Qi Peking University Email: [email protected], [email protected], [email protected]

Abstract: Effective teachers’ training has already become the important way to promote their professional development. It’s also the inevitable requirement of the national educational reform. For so many years there have been some disadvantages in traditional teachers’ training model in China, such as one-fold training model, theories deviating from practices, monotonous learning experience, poor training effects, and formalist training. Using the successful experiences of Chinese and foreign online teaching for reference, School of Distance Learning, PKU put forward tutor-directed online teaching model in combination with Chinese online teaching practices, which both ensure the true occurrence of online learning process and improve the efficiency and effectiveness of online learning results. This paper first introduces the theoretical and practical background of this model, and then elaborates the architecture of tutor-directed online teaching model from the role, teaching and management, these three aspects. Finally, it takes teachers’ training project of School of Distance Learning PKU as an example to investigate practical effects of the model.

Keywords: Online Teaching, Teaching Model, Tutor-directed, Teacher education

1. Foreword Effective teachers’ training has already become the important way to promote the professional development of teachers, and it’s also the inevitable requirement of current education reform for teachers’ staff construction. For many years China mainly use the traditional in-service teachers’ training model, that is, experts delivering lectures, which mainly based on passing on knowledge. Its advantages lie in that teachers can systematically master the theoretical knowledge and current trends in a short period of time. However it also has disadvantages such as one-fold training model, theories deviating from practices, monotonous learning experience, poor training effects, and formalist training and so on. Therefore, the reform and innovation of the ways and means of teachers’ training has become one of the heated focuses in researching this field.

The Chinese government attaches great importance to and vigorously promotes the reform of the professional development model for the teachers. As a key organization which carries out teachers’ training projects in basic education of China, School of Distance Learning, Peking University has formed a unique participatory teachers’ training model with the support of network after years of practice and search. It not only provides a feasible way to optimize the means of teachers’ training and promote teaches’ professional development, but also provides a reference to improve the ways of online education and to enhance the effects of online teaching and learning.

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2. Research Background 2.1. Characteristics of Chinese Adult Learners Online education takes autonomous learning as its main learning style. But it is not optimistic of the autonomous learning situation among Chinese adult learners. They generally lack good independent study habits and self-taught ability (Zhao Hong, Chen Li, 2012). Shi Yongsheng (2012) found that 68.1% of the adult learners don’t have systematical full-time higher education and are poor in self-taught abilities. Wang Dayong (2007) found adult learners showed lower self-taught abilities in learning motivation, self-efficacy, goal setting, learning strategies, and learning skills etc. in his investigation. Xing Xiaochun (2004) found most adult learners showed uneven development in learning motivation, learning plans, learning methods, use of resources, and learning self-evaluation etc. and there was still a gap for them to match requirements of online learning.

Learning characteristics of adult learners are closely related with Chinese traditional education. In online education environment, the autonomous learning abilities of online learners refers to consciously planning, controlling, regulating and evaluating learners’ own learning process during the course of interaction with teachers, peers and learning resources so as to complete learning tasks, and achieve learning objectives (Zhang Shan Shi, 2010). Robert Lyall (2000) thought that online autonomous learning is more suitable for mature learners who have intrinsic learning motivation and more self-disciplined learning abilities. In traditional education, most of the learners have not received specialized training about self-taught abilities, so they have difficulties in online self- taught environment.

2.2. From Participatory Teaching to Tutor-directed Teaching Participatory teaching is widely used in face-to-face training. It focuses on equal participation of team members and dynamical construction of knowledge and abilities. The core concept of participatory teaching is reflected in two aspects: (a) all members equally participate in learning process. There are no traditional teachers or learners, and all are equal participants; (b) learning process is a dynamic process of construction. Teachers may not know more than learners, but they can achieve teaching purposes by combining learners’ resources, experiences and knowledge. Despite of the obvious advantages of participatory teaching, there are still some problems in teaching practice, such as less effectiveness in arouse and maintain learners’ motivation, time-consuming and inefficient in teaching knowledge. Therefore, we try to fuse advantages of participatory teaching and explore new online teaching model.

Leaders and experts of School of Distance Learning PKU proposed the Tutor-directed online teaching concept considering both the process and outcome. Hou et al. point out that we should design and develop online teaching model according to two basic cognitions, which are, from the process aspect we should ensure online learning really happens (Huang et al., 2007) and from the result aspects we should enhance its efficiency and effectiveness. To ensure the realization of this learning idea, conditions need to be created in five aspects, taking real questions as learning situation, learning interest as motivation, learning activities as explicit behavior, analytical thinking as internal behavior, and guide and feedback as external support. Absorbing the advantages of participatory teaching model, tutor-directed online teaching model draws in the concept of Tutor- directed to form a service system constructed by three subsystems including the role, teaching and

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management. Through this system, teachers help learners arrange learning programs, participate in learning activities, actively think over questions, self-control, overcome their learning difficulties, and resolve negative emotions. Thus the goal which combines the process and results is achieved in online education.

3. Tutor-directed Online Teaching Model 3.1. Concept Since 2006, Peking University has introduced the concept of tutor-directed into teachers’ online training. Tutor-directed online teaching model takes network as medium, learning resources as content, teachers’ lead and learning activities as clue, and interpersonal communication as main interaction. Its core objective is to ensure the real occurrence of learning. Specifically speaking, this model focuses on two questions, how to guide learners to take full advantage of diversified learning resources and how to lead them to participate in the interactive process actively.

In order to realize the concept of “tutor-directed”, this model shows the following characteristics in terms of organizational form: (a) Online classes are all small sized (learners≤20); (b) Courses are generally arranged by week. Under teachers’ lead, learners complete specified learning tasks in prescribed period of time; (c) Learners learn mainly through various interactive learning activities, which is full of online discussion and communication between teachers and learners or among learners themselves.; (d) Online teachers not only participate in the design of online courses but also participate in the whole learners’ learning process; (e) Teachers control the whole process. They can discover the learners who are unable to keep up with learning progress and take appropriate measures.

3.2. Role System The first step of the tutor-directed online teaching model is to create a management team of online teaching with distinct administrative levels and explicit labor divisions. School of Distance Learning PKU has established an online teaching management team, in which members distribute throughout the country. It is mainly composed by two roles, teaching supervisors and tutors. In the mean time, for some large scaled training, we selectively add the role of coaches, whose main responsibilities are to assist teaching supervisors to manage tutors.

Specific organizational structure showed as below:  Teaching supervisors: chief in charge of teaching management of a particular subject or a certain area, mainly responsible for the formation of a teaching management team, lead, organization, supervision and evaluation of the work of the entire teaching management team;  Coaches: ��in charge of assisting�� teaching supervisors�� to�� manage tutors ��in ��large-scale training;  Tutors: directly contacting with online learners, providing guide, support and teaching services;  Online learners: participating the online learning and enjoying services from the entire teaching and management team.

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Teaching

supervisor Management system

（Coach ĊĊ Coach） Teaching

Tutor ĊĊ Tutor ĊĊ Tutor System

Learner ĊĊ Learner ĊĊLearner ĊĊ Learner

Figure 1. Role System of Tutor-directed Online Teaching Model

3.3. Teaching System The teaching system of tutor-directed online teaching model defines the interactive relationship between online tutors and learners. The notion of tutor-directed emphasizes on teachers’ provision for learners with full guide, support and services. For this purpose, our School of Distance Learning specially establishes a teaching system of tutor-directed online teaching model. This system is specificallydivided into two branches, task clue and relationship clue.

Release teaching announcement Announce course Progress and tasks checking Monitor learning progress Summary of learners¶�data information Provide learning directions Evaluation of learners Contact class members Provide learning feedback Summation of generative Provide school guidance Collect learners¶�data resources Collect generative resources Teaching Teaching Summary and preparation implementation evaluation

Create a good Incentives and Emotional communication atmosphere solicitude exchange

Figure 2. Teaching System of Tutor-directed Online Teaching Model

In task clues, online tutors provide learners with effective guidance, support and services through task-based teaching programs and operations so as to ensure the effective occurrence of learning behavior. Specifically speaking through notification, guidance, feedbacks, monitoring, evaluation and other operations, online tutors can lead learners to participate actively in teaching activities, attend positively group communication, link extensively their own experiences, think deeply about the practical issues, and steadily improve cognitive abilities.

(1) Teaching preparation. In this phase, online tutors establish a virtual classroom according to learners’ name list. They mainly complete tasks such as grouping learners, notification, issuing electronic resources etc. The specific tasksin this stage include the following:  Announce course information: tutors inform learners of the course information, including course schedule, teaching website URL, and learners’ account and so on.  Contact class members: tutors are responsible for contacting class learners who are in their charge, to establish the relationship between teachers and learners, verify that every learner has been aware of their own learning tasks and can log in time on the teaching platform to participate in learning.  Provide school guidance: tutors provide directions for learners, especially those with less online learning experiences, including how to use teaching platform, how to

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carry out exchanges and cooperation, how to participate in various types of learning activities etc.

(2) Teaching implementation. In this phase, online tutors provide learners with humanistic lead, support and services in accordance with detailed requirements of job tasks. Specific tasks in this stage include the following:  Release teaching announcement: during the teaching process, online tutors need to release regular and temporary teaching announcements to inform learners of related information, such as periodical schedules, progress of learning task etc.  M��onitor learning progress: ��online ��tutors�� ensure learners�� consistent with�� the overall progress by operations such as reminding, urging, evaluating, opening or closing teaching system module etc.  Provide learning directions: through communication and exchanges, online tutors lead learners participate in learning activities, attract learners to actively attend discussion and communication,�� inspire ��their active ��think��ing,�� and ��guide�� them ��to complete ��their�� homework. Mentioning of specifispecificpecifi c work,��online online tutors tutors�� can can ��take take ��many many strategies strategies �� suchsuch asas �� providprovid-- ing a scaffold, giving questions, and introducing cases and so on.  Provide learning feedback: online tutors respond to interactive behaviors of learners while teaching,�� including�� answering questions about�� learning ��and�� technology, r��eplying�� to�� learners in order to promote their further thinking, and checking homework and providing comments etc.  Collect learners’ data: online tutors track and record key nodes of learners in their learning process. Data sources include objective data recorded automatically by computer system as well as subjective scoring by tutors according to learners’ performance in discussion and homework completion.  Collect generative resources: the most vivid and detailed teaching resources are learners’ active speech and homework while they participate in online learning. Online tutors select the excellent contents and questions, process and perfect them, and then make the above into typical cases to update teaching designs.

(3) Summary and evaluation. In this stage, online tutors need summarize all the work in the entire teaching cycle, and make a scientific evaluation based on learners’ data. Specific tasksin this stage include the following:  Progress and tasks checking: online tutors inspect the whole teaching platform and work records to check the completion of every teaching task, and timely report problems or take measures to remedy.  Summary of learners’ data: online tutors gather learners’ data at every learning stage to provide basis for learners’ evaluation.  Evaluation of learners: online tutors make summative evaluation for each learner or each study group according to the summary of learners’ data  Summation of generative resources: online tutors classify, integrate, and report generate resources collected at every different learning stage.

In relational clues, through relational teaching programs and operation online tutors create a good atmosphere to enhance learning enthusiasm and learning effects for class members. Specifically speaking, tutors through the entire teaching cycle carry out greetings, caring, motivation

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and emotional communication behaviors to promote communication and collaboration, eliminate negative emotions, and enhance the sense of belonging of learners. The above specifically includes the following three tasks:  Create a good communication atmosphere: in virtual interactive space online tutors animate the class through�� their words ��or posts��, play down sense of strangeness and distance between team members, and promote positive statements of learners.  Incentives and solicitude: tutors inspire, encourage and mobilize learners’ enthusiasm and motivation, exert and maintain their potential learning motivation to the furthest extent so as to better participate in the entire learning process.  Emotional�� exchanges: i��n�� the process of communicating�� with team members, ��tutors ��express their feelings through words and posts, enhance mutual good impressions, and elevate team identities and individual belongingness.

3.4. Management system Management system of tutor-directed online teaching model defines interactive relationship between leaders (teaching supervisors and coaches) and online tutors of teaching management teams. The yearly training scale in School of Distance Learning, PKU adds up to more than hundreds of thousands. In order to effectively manage such a team to ensure teaching qualities, teaching management team must correspond in scale and coverage. The system is likewise divided into two branches, task clue and relationships clue.

Tasks release Work scheduling Establish contacts Progress monitoring Work inspection Teacher recruitment Work contents Check information Guide and error Data summary Role assignment Operating procedures Check-up system correction Work summary Explicit positions Examination standards Procedural evaluation Personnel evaluation Team Pre-service Teaching Teaching Summation and formation training preparations implementation assessment

Create a good Incentives and Exchange of Emotional communicative atmosphere solicitude experiences expressions

Figure 3. Management System of Tutor-directed Online Teaching Model

In task clues, leaders of online teaching management team lead online tutors to work by task- based managing programs and operations. Specifically speaking, leaders carry out behaviors such as targeted notifications, organization, guidance, monitoring, error correction and so on in the whole managing cycle to ensure online tutors implement managing procedures in accordance with work schedule, provide teaching services in accordance with work standards, and carry out communication and cooperation as needed.

(1) Team formation. In this stage, distance education and training institutions designate specific person who recruits staff and is responsible for management and operation of the entire team. Specific tasksin this stage include the following:  Teacher recruitment:recruitment: teaching supervisorsupervisor (leader) is appointed directly by training inin--

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stitutions. In accordance with the competency models, teaching supervisor selects and employs coaches and tutors.  Role assignassignment:ment:ment: teaching supervisorsupervisor determinesdetermines the teaching role committedcommitted by em-employed teachers according to their educational level, work experience, work abilities and so on.  Explicit positions: teaching supervisor groups coaches and tutors according to learners’ scale, geographic regions, disciplines etc.

(2) Pre-service training. In this stage, distance education and training institutions guide in roles related personnel to learn schedule, work contents, operating procedures and standards through online training platform. Specific contentsin this stage include the following aspects:  Work scheduling: teaching staff should form a common view of the time arrangement of each teaching ��and ��management activities ��during the training ��to facilitate ��mutual coordina��- tion and cooperation.  Work contents: coaches and tutors must have a clear understanding of daily management and teaching contents.  O��perating procedures: ��for ��members who are lack of work experiences,�� we ��provide operating procedures for reference in each management and teaching task to guide team members to work.  Examination standards: in order to guarantee work qualities of coaches and tutors, a set of perfect examination standards is made to check, supervise and evaluate their work.

(3) Teaching preparations. In this stage, each team leader contacts team members and lead them to complete the preparatory work before class opening. The specific tasksin this stage include the following:  Establish�� contacts��: teaching superviso��r�� or coach�� contacts�� online tutors one by one��, establishes their relationship of leading and being led, and confirms that every tutors have known their respective teams with specific duties and can work on time for duty.  Check ��information:�� teaching superv��iso��r�� or coach ��le��a��d�� tutors�� to�� check�� learners��’ information one by one, issue them class notification, and make sure that every learner can start learning on time.  Check-up system: teaching supervisor or coach lead tutors to check the setting of teaching platform term by term to ensure the normal operation of teaching platform after training begins.

(4) Teaching implementation. In this phase, online tutors under the guide of team leader provide learners with such services as directing, answering questions, supervision and evaluation etc. The specific tasksin this stage include the following:  Tasks release: in order to ensure teaching qualities, team leader need guide online tutors with more detailed directions. Issues about what to do, how to do, and to what extent are described in the form of task announcement.  Progress monitoring: each work in tutor-directed online teaching is all linked with one another and orderly connected. Team leaders need to get work completion status of tutors through a variety of channels, and to take specific measures to compensate for delays.  Guide and error correction: capabilities of tutors are uneven, which cannot guarantee them to strictly complete all work required as standards. Coaches must correct errors and

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improve low qualified work through various channels.  Procedural evaluation: team leaders need timely summarize and evaluate teams’ work status and tutors' performance, according which their ability levels and efforts can be evaluated, and which is also the basis for their payment of remuneration and subsequent employment.

(5) Summation and assessment. In this stage, tutors submit various summary materials to the team leader. Teaching supervisor or coaches make data statistics of the overall teaching implementation, collect materials, write a work summary, and examine and evaluate tutors. The specific tasksin this stage include the following:  Work inspection: team leader need inspect tasks completion of learners one by one in each class to timely feedback to tutors to remedy the existing problems through announcement, e-mail or phone etc.  Data s��ummary: team leader need��s to�� calculate ��learners’ phrase scores and total score��,�� collect plagiarism data, distinguish different levels of learners, and pack the data above.  Work summary: team leader needs to write a summary about the implementation of the overall teaching and will feed back to the higher-ups a variety of data, problems and experiences occurring in the whole teaching circulation.  Personnel evaluation: team leader needs to comprehensively summarize and evaluate daily performance and submitted materials of tutors. They will fill in Comprehensive Evaluation Table for Tutors, draw up their reference wages and submit to superiors as the basis of the performance appraisal and future hiring.

In relational clues, main tasks of leaders in online teaching and management team are to create a good working atmosphere and enhance the work enthusiasm of team members. Specifically, leader in the entire management cycle need carry out greetings, caring, motivation, emotional communication etc. to promote communication and collaboration, eliminate negative emotions and improve senses of team belonging, which is specified including the following four tasks:  Create a good communicative atmosphere: leader animates atmosphere by words, plays down senses of strangeness and distance among team members, and promotes positive statements of tutors.  Incentives and solicitude: leader inspires, encourages and mobilizes the enthusiasm and motivation of tutors, makes their potentials exert and maintain to the furthest extent so as to better participate in their work and achieve their objectives.  Exchange of experiences: while in communication, leader shares his work experiences, feelings, ideas and other work-related information to subordinates, which strengthen work abilities of team members and improve mutual favorable impressions.  Emotional expressions: leader expresses his feelings through language and words while communicating with team members, which can enhance mutual good impressions and learners’ sense of team identities.

4. Implementation and Effects of Tutor-directed Online Teaching Model Tutor-directed online teaching model will be continuously developed and improved along with the carrying out of teachers’ training projects in School of Distance Learning PKU. Since it was founded in our school in 2006, tutor-directed online teaching model is successively inspected and practiced in projects of educational technology and skill training for primary and secondary

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school teachers and national training programs for primary and secondary school teachers. The cumulative participators in the former training project add up to more than 630 thousand while the latter more than 340 thousand.

4.1. The Overall Evaluation of Tutor-Directed Online Teaching Model From Learners At the end of every training project, School of Distance Learning will collect learners’ evaluations on teaching in form of questionnaires and interviews. Altogether 900 thousand learners have been trained since six years ago. In each time of the training, learners’ satisfaction rate maintains at more than 95%, participation rate more than 98%, passing rate more than 92%, and excellent rate remains at more than 50%. Overall training situation of the National Training Plan in 2012 is shown as below:

Figure 4. Training situation of the National Training Plan in School of Distance Learning, PKU in 2012

4.2. Analysis of the Advantages and Disadvantages of the Tutor-Directed Online Teaching Model Through interviews, we further analyze learners’ evaluation results. Learners generally approve practices in this model at five aspects which are teachers’ guide, interactive feedback, exchange and cooperation, evaluation and humanistic concern. In the meanwhile, they also question the compact of the teaching activities and the task load.

(1) Tutors’ lead. Learners think that teachers’ lead helps them learn as planned, keep up with the class and participate actively, which is explained as followed:

Tutors assign learning tasks in stages and help learners to make phrase plans to ensure their learning progress. Tutors monitor learners’ learning progress at the end of every phrase. Thus they can not only give learners certain freedom in every phrase, but also ensure learners will not be left behind on the whole and will not accumulate a large number of tasks at the end of the semester. The above can make up for learners’ defects of lack of self-control. At the same time, tutors summarize and announce learning results at different stages, which helps the learners know their own learning conditions, to cultivate their competitive spirits and upward mobility.

“I am very busy with daily work so I cannot attend to one thing without neglecting the other if I arrange learning myself. Reminders and guidance of teachers make it more orderly of e-learning, which helps me save a lot of time and efforts.

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(2) Interactive feedbacks. Learners think that interaction and feedbacks between teachers and learners is useful to reduce learning disabilities and deepen thinking training, which is embodied in the following:

Tutors make heuristic feedbacks on learners’ speech. They use techniques such as rhetorical questions, hints and induction etc. to guide learners to systematically and comprehensively think over cases or problems, which can develop learners' critical thinking and enhance the breadth and depth of their thinking; tutors give timely feedbacks to learners’ general questions, which can resolve operational and technical problems in learning process and reduce learning obstacles.

“I’m really quite unfit at the beginning. I simply said a few words when participated in the online discussion before and there was no effect. Now I had to communicate with my tutor repeatedly and I must think over it.”

(3) Exchange and cooperation. Learners think that exchanges and cooperation will help draw on collective wisdom, absorb all useful ideas, and cultivate cooperative spirit, which is specifically embodied in:

Online tutors weaken the status of academic authorities of textbooks and teachers in the teaching process. They encourage learners to express their different points of views and expand their thinking collision so that they can test and practice theories with experiences in daily work. Online tutors guide learners to carry out cooperative learning behaviors such as grouping, labor divisions, topics selection, exchange, problems solving etc. They can strengthen their cooperative senses and learning skills while completing their tasks together.

“In this form of training, I become more outspoken than in conventional teaching seminar. We can post our viewpoints on the forum for learners to discuss and debate. There is no problem even if the language is sharp or strike home. It is very beneficial for us and others to get improved.”

(4) Procedural evaluation. Learners think that procedural evaluation contributes to the cognitive transformation of learning. Both the results and the process are important. This is accounted for:

Online tutors lead learners to learn and accept procedural evaluation, weaken their attention to academic scores, avoid opportunistic thinking, and focus on learning with more dedicated and positive attitude. Thus learners will do solid work, advance gradually and entrench themselves at every step.

“I am a teacher myself. It is quite one-sided at primary and secondary schools to evaluate learners only on final exams. Opportunistic learners cannot gain good scores here. Only can stead completion of each of the learning activities do.”

(5) Humanistic concern. Learners think that the humanistic care is the stabilizer of learning motivation, which is embodied in:

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Tutors accompany learners through the entire learning process to solve their psychological confusion on learning aspects, defuse negative emotions in the learning process, and motivate learners to study hard. In virtual learning environment full of humane caring, learners seem to return to their "student age". In their learning process, learners are supported by online tutors and accompanied by other learners. Humane warmness reduces learners’ solitude and loneliness to some extent.

“It was very hard for me to stay on while online learning, and even to adhere for half an hour. Now I often discuss with others while learning. Once you enter this learning environment, will you sit down and the time is also not so tough as before.”

(6) Study rhythm and assignments. Recognizing the advantages at the same time, learners also express dissatisfactions with learning rhythm and assignments. Learners think that tutor-directed online teaching model is more compact in learning rhythm and larger in assignments. For learners busy with daily routines, this model will increase learners’ burden.

The writer believes that in order to ensure the effectiveness of teaching, learners must spend correspondent time and effort. The reason why learners feel less pressure in traditional training may be that they unilaterally pursue academic scores and concern only about what affects academic achievements and overlook the importance of the learning process. From the ethical point of view, tutor-directed online teaching model ensures the true occurrence of online learning in the process and enhances its efficiency and effectiveness from the results. This starting point is not wrong. To eliminate discontent moods of learners, we need lead them to establish a correct learning concept. Of course, in subsequent teaching process, we will continue to optimize teaching and management system and mildly alleviate learners’ burden. For example, we can enhance the relevance between learning and work. Work issues related to teaching contents will be introduced into teaching so as to save learners’ time and efforts.

5. Summary In this paper, the writer studied online teaching issues on Chinese teachers’ training. In current situation, Chinese adults are generally lack of good self-taught habits and abilities. The writer believes the teaching method which completely relies on learners’ self-taught cannot meet the needs of Chinese online teaching. To solve the problem, School of Distance Learning PKU introduces the concept of participatory training and completes the shift from concerns about resources to concerns about activities. Through further practices, tutor-directed online teaching model is presented.

Tutor-directed online teaching model starts from the origin of learning and is considered and designed from two aspects, the process and the outcome. That is, the real occurrence of online learning will be ensured from the process, and its efficiency and effectiveness will be strengthened from the outcome. After accumulation and development for several years, this pattern has established roles, teaching and management system. It has provided considerate teaching services for hundreds of thousands of primary and secondary school teachers across the country and is generally approved by learners. This model has been generally accepted especially in five aspects, teachers’ guidance, interactive feedbacks, exchange and cooperation, evaluation and humanistic

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concern. In the mean time, learners also question the compact of the teaching activities and the task load. School of Distance Learning PKU will continue to improve this model through practice and exploration to contribute their wisdom and strength for the national strategy of revitalizing China through science and education and the purpose of constructing a learning society.

References Guo, W. G. (2009). From a network training course to a “virtual” teachers’ training college - educational technology and capacity building program in Peking University (primary) design and implementation of network training curriculum. China Educational Technology, (6), 24- 28. Huang, R. H., Zhang, Z. H., Chen, G., & Xu, Z. (2007). Online learning: did the learning really happen? – comparative study on Chinese and British online learning in cross-cultural context. Open Education Research, (6), 12-24. Lyal, R. (2000). Influences on the orientations to learning of distance education learners in Australia. Open Learning, 15, 107-121. Shi, Y.S. (2012). Cultivation of autonomous learning abilities for distance learners. China Adult Education, (1), 112-115. Wang, D. Y. (2007). Study on self-learning abilities of distance learners. Distance Education in China, (5), 31-36. Xing, X. C. (2004). Investigation and analysis of autonomous study status of experimental learners in distance open education. Journal of Shandong Radio and TV University, (3), 8-9. Zhao, H. & Chen, L. (2012). Cultivating method study on autonomous learning abilities for distance learners. E-education Research, 33, 56-63. Zhang, S. S. (2010). Fostering ways and content analysis of autonomous learning abilities of distance learners. Distance Education in China, (10), 41-44.

140 EITT 2013, Williamsburg, VA, USA, November, 2013 Huang, J., Huang, M., & Qin, C. (2013).Foster reflective thinking and active learning through electronic portfolios at public speaking course to English as foreign language students. Proceedings of International Conference of Educational Innovation through Technology, 141-146.

Foster Reflective Thinking and Active Learning through Electronic Portfolios at Public Speaking Course to English as Foreign Language Students

Ju Huang, Min Huang, Chaoxian Qin Southwest University Email: [email protected]; [email protected]; [email protected]

Abstract: This paper aimed to explore an exploratory qualitative investigation of an incorporating blended learning with e-portfolio as an alternative authentic assessment tool in public speaking course. E-portfolio has gained recognition in documenting students’ learning. A large amount of literature illustrates the advantages of e-portfolios across disciplines. While in China, such alternative assessment practices are less explored so far in English as foreign language education. Using the data included e-portfolios, in-depth interviews and researchers’ field notes, the researchers examine the impacts of the initiative on Chinese college student through case studies. It helps to gain an understanding of how participants’ reflective thinking and active learning was shaped by their engagements with e-portfolio throughout and after the public speaking course. In addition, the study also aims to identify the benefits and challenges of using a e-portfolio as a tool for learning and assessment. Findings of the study indicate that participants are appreciative of e-portfolio and it fostered participants’ reflecting thinking by peer-assessment, supported collaboration and promoted. Suggestions on effective implementation of e-portfolio in public speaking course are provided.

Keywords: e-portfolio, public speaking course in China, reflective thinking, active learning

1. Introduction With the internationalization and globalization, the ability to speak a foreign language has become an important skill in workplaces worldwide. The ability of public speaking is regarded as the higher level of English proficiency in China. Lucas (2013) said English public speaking could help cultivating a special set of talents for Chinese college students in this globalized world. With the widespread of two national speech contests in China, namely, 21st Century Cup National English Speaking Competition and CCTV Cup Speaking Competition, many universities offered the English public speaking course for college students. And in some Chinese middle schools, English public speaking course is designed as an optional one for advanced students. Although the practice of English public speaking is flourishing in China, this subject has received little scholarly attention (Lucas, 2013)

In the educational programs, the use of electronic portfolios (e-portfolios) as authentic student assessment tools has become popular in recent years in many countries around the world. Lots of research has done to testify that the e-portfolio can demonstrate the development process of students and has positive impact on students’ understanding of their own learning (Wang, 2007; Granberg, 2010; Chien, 2013). However, studies conducted in China are less explored so far in English language teaching and learning (Li, 2011).

In this study, the researchers are interested in exploring the possible impact of e-portfolio on Chinese college students’ active learning and reflective thinking in public speaking course to add

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 141 Proceedings of International Conference of Educational Innovation through Technology to the understanding of their combined impact on college students in China. Thus, this research was designed to achieve the following goals: a) To develop an in-depth understanding of the benefits and challenges of using e-portfolio for Chinese college students in the public speaking course. b) To understand how the e-portfolio shaped students’ reflective thinking and active learning, and promote their publishing and speaking skills.

2. Literature Review 2.1. Defining e-portfolios Barrett (2007) defines e-portfolio as follows: “An electronic portfolio uses technologies as the container, allowing students or teachers to collect and organize portfolio artifacts in many media types (audio, video, graphics, text)” (p. 438). In the context of education, this definition implies that a portfolio can be used as a platform to capture and document students’ learning as well as their progress and direction in future life that can be used as a reference and a source of learning. With the aid of Internet and its technology, portfolios can be created and managed more efficiently (in the form of e-portfolios) in public speaking course, where video clips of speeches, pictures and other documents can be better managed, organized, documented and presented. The flexibility of using multimedia provides the portfolios developer with multiple tools to present her/his artifacts and reflections.

E-portfolios are often related to a constructivist approach to knowledge and learning (Butler, 2006). The use of such e-portfolios focuses on the students’ learning process and knowledge production. Their progress can be documented, described and reflected on through an e-portfolio process. Klenowski (2000) believes e-portfolios are one of the most effective approaches in understanding the value of an educational model of assessment that can guide independent learning, self-evaluation, reflective practice, organization, meta-cognition and the role of teacher–learners partnership.

2.2. E-portfolio, Reflective Thinking and Active Learning Although the use of e-portfolios for educational assessment purposes is relatively a new experience in Chinese educational context, many scholars summarized the benefits of using e-portfolio in education. Studies have shown that the development of portfolios “involve[s] an intentional, guided approach to reflection and learning” (Herteis & Simmons, 2010, p.9). Dewey (1933, p. 43) defined the term reflection as “an active, persistent, and careful consideration of any belief or supposed form of knowledge in light of the grounds supporting it and future conclusions to which it tend”. Schön (1983, 1987) extended the definition to combine reflection with action. He described the occurrence of reflection in two time frames: “reflection-on-action” and “reflection- in-action”. E-portfolios can make the students’ watching their own performance possible. Students can make a basic judgment of their work and through the comparison between the excellent public speaker and their own performance; they can achieve clearer understanding of their psychological and mental process of speaking and come to find their problems and ways in public speaking performance.

142 EITT 2013, Williamsburg, VA, USA, November, 2013 Foster Reflective Thinking and Active Learning through Electronic Portfolios at Public Speaking Course to English as Foreign Language Students

The use of e-portfolios would encourage students to engage in active learning by providing various ways for expressing their entire learning experiences (Cameron,, 1999). Cameron (1999) writes about Kolb’s four stages of active learning, and it includes a stage for observation and reflection (p.13-14). There should be a component of active learning that asks students to think about their learning process, in the same way it is used with respect to the portfolio: students thinking through the decisions and choices they made in an effort to reach a deeper level of understanding (personal communication with Jill Jones, September 19, 2013). Barnhizer (2006) writes that when we learn through action (rather than passive reading or listening), we are working toward the formation of a self-identity; the things we do make us who we are (15). Active learning forces the learner to become the very activity they are trying to understand. A student feeling more like a public speaker or judge of public speaking contest while delivering speeches in from of video camera and commenting their peers’ video rather than when reading about public speech skills; Therefore, with the aid of reflections, e-portfolios may become an episode of active learning.

3. Methodology 3.1. The Participants and Settings The research setting was a course of public speaking in Southwest University (SWU) China, which was a practice-oriented course and established in 2008. The goals of the program are to develop college students’ communicative competence and English public speaking skills, to broaden students’ horizons for a society of increasing diversity in today’s globalized world. It featured in fostering students’ critical thinking, reflective thinking and cracking speaking. Topics include introductory speech, informative speech and persuasive speech, as well as techniques of speech delivery. The course divided the students into 5-6 persons groups and arranged weekly group works and extra-curriculum workshops to practice their public speaking skills and promote pee assessments. Since 2012, each member of groups developed an e-portfolio with 3 videos of introductory speech, informative speech and persuasive speech, peer and self-evaluation forms, weekly reflections and other related documents. The e-portfolio is an alternative assessment tool rather than pen and pensile test in the course.

A convenience sample method is applied on voluntarily basis in this study. The participants were four members (2 males, 2 females) in the course who joined in the program in the years of 2011 and 2012. They majored in different disciplines and took English as a foreign language. They come from different departments and take on various majors. Pseudonyms were used to protect the participants’ identity. The Public speaking course site http://swups.swu.edu.cn has been used as the online platform to create the participants’ e-portfolios since 2012. Only the participants of the program had the authority to add, edit, and upload materials.

3.2. Data Collection and Analysis A qualitative case study is the methodological framework of this study (Merriam, 1998). This study aimed at investigating the role of e-portfolio in fostering the Chinese college students’ reflective thinking and active learning in English public speaking course. The data were collection through (1) collecting content shared in e-portfolios. (2) In-depth interviews after the course. (3) Field notes of researchers. The interviews were conducted … after. Each interview ranged from 20 to 30 minutes and were conducted in Chinese, audiotaped and transcribed. During these interviews students were asked to describe their understanding of developing videos and e-portfolios, their

EITT 2013, Williamsburg, VA, USA, November, 2013 143 Proceedings of International Conference of Educational Innovation through Technology experiences in working with them, what impact on their understanding of their performance, as well as their practices and intention to continue to use and develop e-portfolios.. The interviews were recorded and transcribed.

4. Findings 4.1. Active Learners Based on analysis of interviews, we summarized that the process of implementing e-portfolios resulted in three areas: students’ ability to effectively use portfolios, students’ understanding of active learning and reflecting thinking, and students’ ability to assess public speaking skills.

The interview data indicates that students in the public speaking course can actively learn from their e-portfolios because of the direct demonstration of the process of public speaking.

Extract One Whenever I make English public speech, I don’t know where to put my hands. I found from the video that they were always swaying in the air, which made me feel uncomfortable. And I asked for the help from my teacher. She told me that I could just put my hand close to my leg naturally or just put my hands on the desk in front of me. After several practices, I found my own way to put my hands. I felt so happy.

The interviews identified that the students in the public speaking course can actively apply some learning strategies, even some emotional factors through video, which is one of components in their e-portfolio.

Extract Two The members in my group always get together and discuss our performance in our videos. We always point out our partners’ problems in speaking. Frankly speaking, I did not accustom to it and felt unhappy because I felt criticized and lost my face. Later, they noticed my unhappiness and point out my problems indirectly. I found I could accept their ideas and their ideas are so meaningful to me.

Participants identify that e-portfolios actually involve them in active learning, comparing and reflection (reflection notes from participants 1 and participant 2). Specifically, according to one of participants, his learning and achievement are crucially strengthened by self-reflection and feedbacks from the course instructor.

4.2. Reflective Learners One of the themes that participants mentioned during the interviews was that they believed the e-portfolio might have played in the development of their professional development as reflective teachers. Findings in this study indicate that creating and maintaining e-portfolios are advantageous as they provide the participants the opportunity to consciously monitor and assess their own current knowledge continuously and consistently. It is in line with Kabilan & Khan’s (2012) finding. All the four participants said that the feedback and suggestions given by the course instructor deepen and enrich their learning. Two of them keep the habit of writing weekly journals till now. Extracts one is representative of the comments they offered.

144 EITT 2013, Williamsburg, VA, USA, November, 2013 Foster Reflective Thinking and Active Learning through Electronic Portfolios at Public Speaking Course to English as Foreign Language Students

Extract three I really liked it [the e-portfolio] and develop the habit of writing reflections. I believe that my experience in the course changed me a lot. I usually spend two or three hours writing reflections after school in the first year. My teaching focuses on active learning and aims to be student centered. So I think it [e-portfolio] is useful to help me to understand what active learning means. I may utilize technology as a platform to document and assess my students’ learning.

4.3. Limitations The participants’ development and growth as an individual, as well as a confident English public speakers, are obvious in their e-portfolios and can be traced considerably. However, some participants of this study complained about the huge time and effort needed to maintain their e-portfolios and reflections, quite similarly to Kilbane & Milman (2005) study. Therefore, careful measures in determining workload and time constraint are imperative.

In respect of students’ reflective thinking, even though participants in this study have indicated that e-portfolios have contributed to it, more research is needed, particularly in concretely measuring the reflective thinking and active learning gained by the participants. For example, participants have pointed out that they have developed the habit of writing reflection and communication in English; but the question is, ‘To what extent and how much the reflections contribute to their public speaking skills and reflective writing? In addition, it is hard to actually measure the reflective thinking gained or benefitted. All the above imply that using e-portfolios as a learning and assessment tool is still in an infancy stage.

5. Conclusion The results of this study suggest e-portfolio is not only regarded a tool to assess students’ learning in a new way that they have never experienced before, but were perceived as making a positive contribution to develop their reflective thinking and active learning by Chinese students. Instructor may give clear expectations on numbers of reflection posts each week and encourage variety forms of e-portfolios so that the students will have an idea of their engagement in their e-portfolios. Steps should be taken to ensure that developing e-portfolio is process-oriented rather than only a product. Further research will be explored in the aspect of creating learning community of students by sharing and interacting with e-portfolios.

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Institute research report. Business-Education Research Center of Peking University. (2009). Industrial and Commercial Bank of China research report. Wu, F. (2010). Corporate e-learning ten development theme. Modern distance education research. 105(3), p. 58-63. Allen, M., Translated by Wu, F. (2009). The next generation of enterprise University. Beijing: World Publishing Corporation.

146 EITT 2013, Williamsburg, VA, USA, November, 2013 Li, J., & Xu, H. (2013). The effect of online games on adolescents’ physical, mental health and academic performance. Proceedings of International Conference of Educational Innovation through Technology, 147-150.

The Effect of Online Games on Adolescents’ Physical, Mental Health, and Academic Performance

Jian-Sheng Li, Huan Xu Nanjing Normal University, Email: [email protected], [email protected]

Abstract: The purpose of this study was to investigate the effect of online games on the adolescents’ physical and mental health and academic performance. A sample of 197 Chinese adolescents participated in the study. Through the questionnaire, data were collected and the conclusions are as follows: (1) Length of playing online games is positively correlated with adolescent physical health. (2) Puzzle games play a certain role in promoting adolescents’ mental health. (3) Length of playing online games, the frequency of playing online games, and the duration of playing games have negative correlated with adolescent physical health and academic performances.

Keywords: online games, adolescent, physical and mental health, academic performance

1. Introduction With the rapid development of the Internet technologies, online games came into people’s life quickly and have been prevailing. A report delivered by China Internet Network Information Center (CNNIC) has showed that the number of the Internet users of adolescents reached 232 million, which accounted for 45.3% of all Internet users and 64.4% of all adolescents in the end of December, 2011. Playing online games has turned into a new way of recreation of adolescents. Furthermore, many adolescents are addicted to the games. Most of the previous studies focused on this, such as depression and Internet addiction in adolescents (Ha, 2007), gamer experiences and addiction (Hsu, Wen & Wu, 2009), problematic Internet use and addiction (Lin & Wei, 2009), excessive computer usage in adolescents, problematic Internet use (Liu & Chen, 2007), alienation of gamers(Zhang,2009). Online games can also lead to learning and physical health problems of adolescents. After the investigation of 1090 primary and middle school students, students who are addicted to online game seriously did poorly in study and feel more stressful (Liu,2007). And, online games addiction seriously endangers the health of adolescents, such as vision loss, muscle soreness, insomnia, headache, decreased appetite weight loss and so on (Tian,2009). Online games may cause some students the deviation of value and the wrongness outlook on life (Li, 2008).

However, playing online games has a positive effect on adolescents. Games are seductive, deploying rich visual and spatial aesthetics that draw players into fantasy worlds that seem very real in their own terms, exciting awe and pleasure (Poole, 2000). As Bouras et al. (2004) suggested, gaming is becoming a new form of interactive content, worthy of exploration for learning purposes. Game motivates students using entertainment, and this is a part of the natural learning process in human development (Betz, 1995). Interactive learning environments allow learners to construct understandings by interacting with information, tools, and materials as well as by collaborating with other learners within the games(Dickey,2007).Therefore, online games can partly promote the study of information technology course (Ren,2012). A study on the cooperation mechanism

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 147 Proceedings of International Conference of Educational Innovation through Technology in ‘World of Warcraft’ found that wisdom of players can be show and the development of the awareness of citizen in the virtual world(Shi,2012). Another study has also found that designing a game-based learning course in networking can promote high school female students’ interest in science(Lin & Liu ,2011).

In all, the effects of playing online games on adolescents are in many ways. This study aimed to discover the effects of the online games on adolescents’ physical- mental health and academic ability. For this purpose, players’ behavior, effect factors and adolescent health were divided.

2. Method 2.1. Sample In this paper, the adolescents are those who are aged 13 years old but less than 20 years old. The participants are recruited from high school students and junior college students in Jiangsu province, china. 364 adolescents whose age ranges from 13 to 20 were take part in this research and complicated the questionnaires. In the end, 170 copies of which are valid.

2.2. Questionnaire Based on the above researches, the questionnaire has 22 items which derived from theoretical notions: mental health, physical health and learning performance. These notions are composed of different factors. 200 junior college students from Nanjing Normal University completed the questionnaire’s pre-test. Based on the test results, the questionnaire has been modified again and the data are processed by SPSS 18.0.

3. Results 3.1. The Effect of Online Games to Teenager’s Physical Health Physical health is tested from drink and smoke, eye dry, exercise shoulder pain, insomnia, headaches, anorexia. It can be concluded from table1 that length of playing online games is negatively related with insomnia (r=-0.262, p=0.000); Duration of playing games is negatively related to the drink (r=-0.230, p=0.003), positively related to sore shoulders (r=0.191, p=0.010), insomnia (r=0.230, p=0.002), nausea anorexia (r =0.179, p=0.016); Playing dance class (r=0.172, P=0.028) and legendary journey (r=0.305, p=0.000) is positively related to insomnia and nausea anorexia, but playing poker nearly has no effect; The frequency of playing games is positively correlated with drinking (r=0.151, p=0.045 ).

3.2. The Effect of Online Games to Teenager’s Psychological Health Mental health is tested from positive life, independence, Confuse reality and virtual, Thinking ability to respond, Teamwork, Sense of accomplishment, Make friends, loneliness. It can be concluded from table2 that length of playing online games is positively related to confuse reality and virtual(r=0.212, p=0.002) and loneliness(r=0.241, p=0.001); Duration of playing games is negatively related to confuse reality and virtual(r=-0.292, p=0.000) and positively correlated with sense of accomplishment (r=0.218, p=0.003); Playing dance class (r=-0.239, p=0.001), legendary journey (r=-0.194, p=0.010) and fantasy westward journey (r=-0.196, p=0.009) is negatively related to confuse reality and virtual; Playing legendary journey (r=-0.304, p=0.000) and fantasy westward journey (r=0.156, p=0.043) is positively correlated with Sense of accomplishment; The frequency of playing games is positively correlated with drinking (r=0.243, p=0.000).

148 EITT 2013, Williamsburg, VA, USA, November, 2013 The Effect of Online Games on Adolescents’ Physical, Mental Health, and Academic Performance

3.3. The Effect of Online Games to Teenager’s Academic Performance Academic performance is tested from indulging in the game, interesting comparison, skipping class, academic decline, attention, memory loss, poor study habits, and dislike school. It can be concluded from table3 that duration of playing games is positively related with indulging in the games (r=0.216, p= 0.001) and skipping class (r=0,174, p=0.011); Frequency of playing games is negatively correlated with indulging in the games (r=-0.168, p=0.015), interesting comparison (r=- 0.245, p=0.20), skipping class (r=0.163, p=0.020) and academic decline (r=-0.307, p=0.000).

Therefore, based on the above results, it can be concluded that online games affect the adolescents’ mental health and academic performance, and the effect is negative. There is no direct impact between online games and adolescents’ physical health, but online games can cause adolescents’ insomnia. There is a negative impact between length of playing online games and psychological health and academic performance. Frequency of online games has no significant impact on teenager’s psychological health, but has negative effects on their academic performance; the time of online games adolescents play every time have negative impact on adolescents’ physical and mental health and academic performance; the type of online games have some positive impact on teenager, for example, the poker game of chess can improve adolescents’ thinking ability to respond, but have a negative impact on their physical health.

4. Discussion From this investigation, the conclusion can be known: playing online games is associated with adolescents’ physical and mental health and academic performance to some degree. Games have become one part of adolescents’ life. Therefore, it is important to know games’ influence and scopes on adolescents. This paper provides case support on how to deal with the relationship between online game and physical and mental health of adolescents and academic performance. On the other hand, the sample size of this study and the sample range is limited, so it should be cautiously dealt before the conclusion is widely recognized.

References Betz, J. A. (1995). Computer games: Increase learning in an interactive multidisciplinary environment. Journal of Educational Technology Systems, 24(2), 195-205. Bouras, C., Igglesis, V., Kapoulas, V., Misedakis, I., Dziabenko, O., Koubek, A., & Sfiri, A. (2004). Game-based learning using web technologies. Dickey, M. D. (2007). Game design and learning: A conjectural analysis of how massively multiple online role-playing games (MMORPGs) foster intrinsic motivation. Educational Technology Research and Development, 55(3), 253–273. Ha, J. H., Kim, S.Y., Bae, S. C., Bae, S., Kim, H., Sim, M., & Lyoo, I. K.(2007). Depression and Internet addiction in adolescents. Psychopathology, 40, 424–430. Tian, J. (2009). Prevention and Control of Teenagers’ Internet Addiction. Life World, 256, 32-37. Liu, J. Y. & Chen, S. H. (2007). Investigation and Analysis of the behavior of the minor student network game. Education Research Monthly, 24, 37-41. Lin, M. T. & Liu, C. M. (2011). Developing a game-based learning environment by using ubi- media technologies. Liu, M. & Wei, P. (2009). Cognitive and psychological predictors of the negative outcomes associated with playing MMOGs (massively multiplayer online games). Computers in Human

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Behavior, 25(6), 1306–1311. Li, M. (2008). A survey on how plying online games influences college students and the countermeasures (D). The Netherland: Northeast Normal University. Poole, S. (2000). Trigger happy, videogames and the entertainment revolution. New York: Arcade Publishing. Hsu, S. H., Wen, M. H., & Wu, M. C. (2009). Exploring user experiences as predictors of MMORPG addiction, Computers & Education. Zhang, Y. L. (2009). Gamification and alienation: an empirical study of the computer game affecting college students take college students of eight universities in Nanjing as cases. The Netherland: Nan Jing University. Zhang, Y. X., Li, J. S., & Li, Y. (2013). Study on the game player achievement goals in educational games influence on academic emotions.Journal of Distance Education, (8), 105-111. Shi, Y. G. (2012). The fair exercise in virtual world. Youth Studies, (01), 429-431. Ren, S. P. (2012). The study of online games’ influence on information technology course in middle school. The Netherland: Yanbian University.

150 EITT 2013, Williamsburg, VA, USA, November, 2013 Li, S., Han, Y & Liu, S. (2013).Physiological evaluation of the players’ emotions in different educational games. proceedings of International Conference of Educational Innovation through Technology, 151-158.

Physiological Evaluation of the Players’ Emotions in Different Educational Games

Jian-Sheng Li, Yun-Xia Han, Shan Liu Nanjing Normal University Email: [email protected], [email protected], [email protected]

Abstract: The player’s personality in games has been studied in recently. This study explored whether the game types could affect learner’s learning emotions in educational games or not and inferred which kind of game has the potential in education. As a sample, 40 players were recruited to evaluate three electronic games on training players’ abilities to use the games. In this paper, the players’ heart rate variability (HRV) was recorded through Biofeedback instrument to explore learner’s emotions. After evaluating the games’ scores by the related scales, three different kinds of games (“Ballance”, “Rescue” and “Gates of Logic.”) are chosen as test materials. The experiment results show three games all arouse the players’ an overall positive emotions. The increasing HF and the unchanging LF/HF show the different types’ games can arouse the different degrees of pleasure.

Keywords: game types, emotions, educational games

1. Introduction Recently, the player’s personality, game types and learning effect have been studied. Pillay’s findings suggest that playing recreational computer games may influence children’s performance on subsequent computer-based educational tasks (Kim et al, 2010). Game type would be related to children’s gender-based peer preference: boys’ preference for same-sex peers would be especially pronounced in a more competitive /physical game, and girls’ preference for same-sex peers would be especially higher in a less competitive /physical game (Boyatzis et al, 1999). Ruben Puentedura (2012) figure out that Narrative-Based game are very useful in an educational environment, which includes Role-playing games, Massively multiplayer online game, alternate reality games, they are better suited to different players. Action games could not be directly used in education, but simulation games is particularly rich category for education, which may map on the educational contents. On the other hand, the play’s personality is also the important factor in game-based learning. Especially, the player’s emotion is one of most relevant dimensions for game assessment (Berta, 2013). Emotions can affect attention, creation, and the formation of memory channels. Emotional status and learning are strongly correlated (LeDoux, 1994). The players’ emotional state will evolve according to the events of the game (Chanel, 2011). However, the emotional reactions are not introduced by the designers on purpose (Weinstein, 2010; Zhou & Zhang, 2010). Therefore, it is necessary to consider players’ emotion in assessing the learning effect and what types of educational games can influence students’ emotions (Chanel, 2006).

Emotion assessment is also a rapidly growing research field, especially in the human-computer field. In emotion assessments, spontaneous and less controllable reactions can be more reliable. Physiological signals can be captured by the peripheral nervous system and those coming from the central nervous system (Chanel , 2006).Based on the research results above, this study aims to

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 151 Proceedings of International Conference of Educational Innovation through Technology explore the different games and players’ emotional states. In this research, the players’ emotions are obtained by recording physiological signals, which can be analyzed and then estimated which kind of game has the potential in learning.

1.1. Game Types As the Internet becomes popular, the newer games are emerging. Many studies have focused on different aspect about kinds of games but there has not been much consensus on game types. However it’s possible to use some popular classifications for defining different games (Lee, 2006). For example, Lindsay Grace divided games into six categories (Grace, 2005). Wang (2010) divide electronic games into eight types: Linguistic (L), Musical (M), Logical (R), Visual (V), Kinesthetic (P), Social (S), Introspective (I), and Watchable (W).In this article, based on the Wang’s electronic classification above, we chose different electronic games as experiment materials.

1.2. Emotions People’s moods heavily influence their ways of communicating and acting (Wan, 2010) and Emotions can affect attention, meaning creation, and the formation of memory channels. Hence, emotional status and learning are strongly correlated (LeDoux, 1994).

A lot of prior researches explored in recognizing emotions with computers, such as recognizing emotion from speech, facial expressions or other. Measuring emotion from brain activity is a relatively new method, although some valuable conclusions have been published (Wan, 2010). As it is important to recognize the learners’ emotional states, people (Chen & Lee, 2011; Emmanuel, Pierre, & Claude, 2007; Kiyhoshi & Tomoya, 2006; Mohamed & Mahmoud, 2007) have attempted to use artificial intelligence techniques to build appropriate human emotion-recognition models. Thus, the following four methods have been used to recognize learner emotions:(1) voice (prosody) analysis (Kopecek, 2000); (2)observable behavior such as user actions in a system interface (Vicente & Pain, 2002); (3) facial expression analysis (Wehrle & Kaiser, 2000); and, (4) analysis of physiological signs (Picard, Healey, & Vyzas, 2001). Specially, in recent years, emotion-recognition technologies based on human physiological signals have been developed for practical application (Chen & Lee, 2011; Emmanuel et al., 2007; Kiyhoshi & Tomoya, 2006; Mohamed&Mahmoud, 2007), for example, Chen and Lee (2011) integrated sensors, signal processing, wireless communication and machine-learning technologies to construct an embedded human-emotion-recognition system.

On the emotional learning, previous research had typically used dichotomous conceptions of emotions (i.e. positive affect vs. negative affect) and a few kinds of discrete achievement emotions. But some researchers also used the Classification of positive emotions, neutral emotion and negative emotion (Lei, 2009). The methods for assessing learner’s emotional states are usually post hoc subjective emotion assessments by learner’s self reporting on a set of questions (Schutte, Malouff, & Bhullar, 2009). These methods are often not sensitive to changes in emotion. However, the heart rate variability (HRV) patterns are directly responsive to changes in emotional states, then the heart rate variability (HRV) was used as the emotion index in some researches (Latham, 2006; McCraty, Atkinson, Tiller, Rein, &Watkins,1995; Tiller, McCraty & Atkinson,1996). In this paper, based on the methods above, player’s heart rate variability is recorded by Biofeedback instrument (Spirit-16) to reflect participants’ emotional

152 EITT 2013, Williamsburg, VA, USA, November, 2013 Physiological Evaluation of the Players’ Emotions in Different Educational Games states. That is to say, use HRV physiological signals to identify player’s emotion reaction in educational games.

2. Research Goals This study will explore how different types of games affect participates’ emotion in game- based learning environment, and then infer which kind of game has the potential in the education. Therefore, in this paper, the research hypotheses are as followings: The players have experienced the positive or negative emotions in different educational games and the degree of the emotions is different when the players faced different educational games.

3. Methodology 3.1. Materials Our research chose electronic games according to “Grading and Classification of Electronic Games in Educational Perspective” (Wang, 2010). This evaluation system divides electronic games into eight types: Linguistic (L), Musical (M), Logical (R), Visual (V), Kinesthetic (P), Social (S), Introspective (I), and Watchable (W). Thirty-six graduate students from Nanjing Normal University who are interested in playing educational games were chosen randomly to evaluate six electronic educational games that trained each of the eight types of players’ abilities. The researchers averaged their evaluation scores and compared this to the corresponding rating scale that we determined as classifications of electronic games in educational perspective. The result presents that “Ballance” (game1) is a “visual” electronic game, “Rescue”(game2) is an “introspective” electronic game, and “Gates of Logic”(game3) is a “watchable” electronic game.

3.2. Participants Steinberg’s research (2005) shows that there are significant differences in cognitive skills and affective experiences between different ages. Therefore, the study recruited 100 undergraduates from Nanjing Normal University, Hehai University, and Nanjing Xiaozhuang College for ensure that they are in the same age group. They completed the “Basic Information Questionnaire” before the experiment which asked basic information such as gender, age, experience, and preference for the games. The mean age was 20.34 years (SD =2.29). Forty (19 female and 21 male) participants were selected who did not play the three games before and they all had a similar preference for the games. Thus, we could exclude the interference of the players’ experience and preferences.

3.3. Measures Research has shown that heart rate variability (HRV) patterns, also known as heart rhythms, are directly responsive to changes in emotional states (McCraty, Atkinson, Tiller, Rein &Watkins, 1995; Tiller, McCraty, & Atkinson, 1996). HRV is often used as a noninvasive test of integrated neurocardiac function, because it can help distinguish sympathetic from parasympathetic regulation of the sinoatrial node. They divided the power spectrum into three major frequency ranges (low frequency [LF], medium frequency [MF], and high frequency [HF]. The integral of the power spectrum within each region was calculated. The LF region (0.01 to 0.08 Hz) is primarily considered a measure of sympathetic activity with a minor parasympathetic component. In contrast, the HF region (0.15 to 0.5 Hz) is associated with respiratory sinus arrhythmia and is almost exclusively due to parasympathetic activity. The LF/HF ratio has been used as a measure of sympathovagal balance. The two emotional states produced different effects on sympathovagal balance. Anger resulted in

EITT 2013, Williamsburg, VA, USA, November, 2013 153 Proceedings of International Conference of Educational Innovation through Technology a significant increase in LF power (p ~0.01) with no change in HF power. In contrast, appreciation produced an increase in LF and HF power. The LF/HF ratio was significantly increased during anger and remained unchanged during appreciation (McCraty, Atkinson, Tiller, Rein, &Watkins, 1995).

Also, research referred that the low-frequency zone of the power spectral density represents a change in sympathetic activity; according to analytical results, it also represents a negative emotional state. The medium-frequency zone of the power spectral density indicates the changes in parasympathetic nervous activity or in a peaceful emotional state. The green part is the high- frequency zone of the power spectral density, representing parasympathetic nervous activity changes, or a positive emotional state (Chen et al, 2011). Therefore, in our research, HF and LF/ HF are chosen as participants’ emotional states.

3.4. Procedure Before performing the formal test, the experiment and the three games are introduced to each participant in a Biofeedback laboratory. Then the participants are given several minutes for being familiar with the experiment process. For every participant, there are three steps to be complied: keeping calm and relax for at least 1 min and 30 s, playing the game for 15 min in one of the three experimental games, and then having a break rest for three min. The first step was used to return the physiological signals to a baseline level, to record a baseline activity, and to provide a rest period for the participants. The second step was kept the participants to play the games without interference. Each game is about 15 minutes in length. Then, the participants played three games at three minutes intervals between every two games, The biofeedback instrument recorded their heart rate variability (HRV) while the participants playing the games, at the same time, the mark of the beginning and end of every game are signed in order for post-processing data.

4. Results Biofeedback instrument (Spirit-16)can record people’s biofeedback quickly, including electroencephalogram (EEG), blood volume pulse (BVP), and heart rate variability (HRV), which can be used to measure human emotions and so on. Biofeedback measure and record HRV raw data with its instrument, at the same time, the system has an easy-to-use software program with a heart rhythm monitor and an emotion-recognition algorithm for identifying emotional states. Figure 1 shows the heart rate power spectral density analysis for identifying human emotion (McCraty et al., 1995)

Figure 1. Players’ emotional expression changes in high-frequency power and in LF/HF ratios

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According to the test, we can get the data of LF, HF and LF/HF for all participations, after filtering thirty persons’ data, the average of these data are presented in the following Figure1. Just as the McCraty’s study, the positive emotion generated with an increase in HF power. The LF/ HF ratio was significantly increased during anger and remained unchanged during appreciation. Therefore, results show that three games all caused the player’s an overall positive emotions with an increase in total mean HF and remaining unchanged on LF/HF in the Figure 1.It was still seen that different types of games caused the players’ different emotions. The introspective type electronic game (game2) caused the players the highest positive emotion, and the watchable type game (game3) caused the lowest.

5. Conclusion and Discussion 5.1. Conclusion Just as the Figure 1 above, we can see the data of HF measured and calculated for the three games all increased to varying degrees. In the Figure1, the purple part indicates the HF’s average data while one is in calm state. The red part indicates the average data of “balance” game which is a “visual” electronic game, and the yellow part indicates the average data of “rescue” game which is an “introspective” electronic game and the blue part indicates the average data of “Gates of Logic” electronic game which is a “watchable” electronic game, respectively.

Rollin McCraty (1995) verified that anger resulted in no change in HF power; in contrast, appreciation produced an increase in HF power. We can conclude that all three games can arouse positive emotion. Moreover, the yellow part is higher than the red part, and blue part is lowest among three, we can conclude that the participates are most happy when they are playing the “rescue” game than the others, and the “balance” game is second, the blue part is higher than the purple part, but the two value have a little difference, we can assume that the “Gates of Logic” electronic game arouse less happily experience than the other. We can see the data of LF/HF measured and calculated for the three game all increased to varying degrees from the Figure 3 above, but compared to the date of calm state, the increase of anther three part is very small, which can be seen have no change. Rollin McCraty(1995) verified that the LF/HF ratio was significantly increased during anger and remained unchanged during appreciation. We can also conclude that all three games can arouse positive emotion. Because the red part is higher than the yellow part, we can also conclude that the participate is most happy when they are playing the “rescue” game than the others, and the “balance” game is second, this result are same as the conclusion draw by HF. The blue part is lowest among three, compared with baseline, we should think it has no change, and it should arouse most happy experience, this result are not same as the conclusion draw by HF. The reason may be the participant began to get bored with playing after they have finished two games, which need to be further confirmed. All in all, different types of games do arouse students’ positive emotions in varying degrees. And the “introspective” element has more chance to arouse positive emotion than the “visual” element, the effect of “watchable” element on positive emotion need to be further research.

5.2. Discussion and future work This paper proposes an approach based on emotion recognition to emotional state of players in three different types of games. Seen from the conclusion above, all three different games all arouse positive emotion which this conclusion consistent with previous findings. However, in our results,

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The Conclusions for “Gates of Logic” electronic game from the HF and LF/HF are different. The reason can be explained as follows. Firstly, the participants may be begun to get bored with playing after they have finished two games. Both physiological and self-report analyses have lead to the conclusion that playing at the same level of difficulty several times elicits boredom (Chanel et al, 2008). Although we do not know the difficulty between these three games, we cannot rule out this reason, when one played the third game after finished two, the participant’s emotional state has begun to be influenced by their own mental state, but without much relationship with games. Secondly, the competence of the player has increased, although the game are different, his operation skills and speed would achieve a higher level, which potentially giving rise to boredom (Chanel et al, 2011). It may also make an unexpected emotional state change. In addition to the conclusion above about the third game need to be further study, we should explore what is the main reason affect people’s emotion, when one person plays different games. Although different patterns of emotional responses have been found in psycho physiological studies for different type games, Stemmler argues that they are also might due to context deviation specificity(Stemmler et al, 2001), so we should acknowledge what played a decisive role in human emotions, the game type or game content, or the other. At the same time, the learner’s own conditions should be taken into consideration, such as motivations and learning styles. Different gaming motivations and learning styles can affect learner’s engagement and learning outcomes (Lee et al, 2009; Kong et al, 2012). As for the methods of measurement, there are many in psycho physiological field. We should use more than one method to assess emotional state for every participant, in order to draw a more accurate conclusion.

References Bellotti, F., Kapralos, B., Lee, K., Moreno-Ger, P., & Berta, R. (2013). Assessment in and of serious games: an overview. Advances in Human-Computer Interaction, (1). Boyatzis, C. J., Mallis, M., & Leon, I. (1999). Effects of game type on children’s gender-based peer preferences: A naturalistic observational study. Sex Roles, 40(1-2), 93-105. Chanel, G., Kronegg, J., Grandjean, D., & Pun, T. (2006). Emotion assessment: Arousal evaluation using EEG’s and peripheral physiological signals. In Multimedia Content Representation, Classification and Security(pp. 530-537). Springer Berlin Heidelberg. Chanel, G., Rebetez, C., Bétrancourt, M., & Pun, T. (2008, October). Boredom, engagement and anxiety as indicators for adaptation to difficulty in games. In Proceedings of the 12th international conference on Entertainment and media in the ubiquitous era (pp. 13-17). ACM. Chanel, G., Rebetez, C., Bétrancourt, M., & Pun, T. (2011). Emotion assessment from physiological signals for adaptation of game difficulty. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 41(6), 1052-1063. Chen, C. M., & Lee, T. H. (2011). Emotion recognition and communication for reducing second- language speaking anxiety in a web-based one-to-one synchronous learning environment. British Journal of Educational Technology, 42(3), 417-440. Chen, C. M., & Wang, H. P. (2011). Using emotion recognition technology to assess the effects of different multimedia materials on learning emotion and performance. Library & Information Science Research, 33(3), 244-255. Emmanuel, B., Pierre, C., & Claude, F. (2007, July). Towards advanced learner modeling: Discussions on quasi real-time adaptation with physiological data. Paper presented at the

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Seventh IEEE International Conference on Advanced Learning Technologies ( I C A L T ) , Niigata, Japan. Grace, L. (2005). Game Type and Game Genre. Retrieved February, 22, 2009. Kim, J. W., Han, D. H., Park, D. B., Min, K. J., Na, C., Won, S. K., & Park, G. N. (2010). The relationships between online game player biogenetic traits, playing time, and the genre of the game being played. Psychiatry investigation, 7(1), 17-23. Kiyhoshi, N., & Tomoya, K. (2006, August). A multi-modal emotion-diagnosis system to support e-learning. Paper presented at the First International Conference on Innovative Computing, Information and Control (ICICIC), Beijing, China. Kong, J. S. L., Kwok, R. C. W., & Fang, Y. (2012). The effects of peer intrinsic and extrinsic motivation on MMOG game-based collaborative learning. Information & Management, 49(1), 1-9. Kopecek, I. (2000). Emotions and prosody in dialogues: An algebraic approach based on user modelling. In ISCA Tutorial and Research Workshop (ITRW) on Speech and Emotion. Latham, C. (2006). Heart rate variability as an index of regulated emotional responding. Review of General Psychology, 10, 229–240. LeDoux, J. E. (1994). Emotion, memory and the brain. Scientific American,270(6), 50-57. Lee, J. H. M., Lee, F. L., & Lau, T. S. (2006). Folklore-based learning on the web--pedagogy, case study, and evaluation. Journal of Educational Computing Research, 34(1), 1-27. Li Lei, Guo Cheng.(2009). Reaeach on adolescent academic emotions. Journal for Guizhou Educational College, 25(4), 12-15. McCraty, R., Atkinson, M., Tiller, W. A., Rein, G., & Watkins, A. D. (1995). The effects of emotions on short-term power spectrum analysis of heart rate variability. The American journal of cardiology, 76(14), 1089-1093. Mohamed, B. A., & Mahmou, N. (2007). EMASPEL (emotional multi-agents system for peer to peer e-learning). Paper presented at the Seventh IEEE International Conference on Advanced Learning Technologies (ICALT), Niigata, Japan. Picard, R. W., Vyzas, E., & Healey, J. (2001). Toward machine emotional intelligence: Analysis of affective physiological state. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 23(10), 1175-1191. Schutte, N. S., Malouff, J. M., & Bhullar, N. (2009). Assessing emotional intelligence. The Springer Series on Human Exceptionality, (2), 119–134. Steinberg, L. (2005). Cognitive and affective development in adolescence. Trends in cognitive sciences, 9(2), 69-74. Stemmler, G., Heldmann, M., Pauls, C. A., & Scherer, T. (2001). Constraints for emotion specificity in fear and anger: The context counts.Psychophysiology, 38(2), 275-291. Tiller, W. A., McCraty, R., & Atkinson, M. (1996). Cardiac coherence: A new, noninvasive measure of autonomic nervous system order. Alternative Therapies in Health and Medicine, 2(1), 52-65. Vicente, A., & Pain, H. (2002, January). Informing the detection of the students’ motivational state: an empirical study. In Intelligent Tutoring Systems (pp. 933-943). Springer Berlin Heidelberg. Wang, W. (2010). Grading and classification of electronic games in educational perspective. Beijing, China: Science Press. Wan, J., Hu, B., & Li, X. (2010). EEG: A Way to Explore Learner’s Affect in Pervasive Learning Systems. In Advances in Grid and Pervasive Computing (pp. 109-119). Springer Berlin

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Heidelberg. Wehrle, T., & Kaiser, S. (2000). Emotion and facial expression. In A. Paiva (Ed.), Affect in interactions: Towards a new generation of interfaces (pp. 49–63). Heidelberg, Germany: Springer. Weinstein, A. M. (2010). Computer and video game addiction-a comparison between game users and non-game users. The American Fournal of Drug and Alcohol Abuse, 36(5), 268-276. Zhou, Y., & Zhang, C. (2010). The factors of computer game addiction and the development of educational games. E-Education Research, (7), 44-47. Zhang, Q., & Lee, M. (2009). Analysis of positive and negative emotions in natural scene using brain activity and GIST. Neurocomputing, 72(4), 1302-1306.

Acknowledgement This study was supported by the national social science fund, China. (13BRK026).

158 EITT 2013, Williamsburg, VA, USA, November, 2013 Li, Q. & Zheng, Q. (2013). Empirical research on the interaction between learners’ interactive centrality and quality in the forum on MOOCs. Proceedings of International Conference of Educational Innovation through Technology, 159-168.

Empirical Research on the Interaction between Learners’ Interactive Centrality and Quality in the Forum on MOOCs

Qiujie Li, Qinhua Zheng Beijing Normal University Email: [email protected]; [email protected]

Abstract: In Connectivism learning, interaction between learners can help them to form their personal knowledge network. This makes interaction in learning more important than before. In the MOOCs environment, due to the features of massive and rich interactive media and numerous learners, it supposes to achieve the realization of Connectivism learning. So, to study the relationship between the quantity and quality of interaction on MOOCs can help the teachers to know how to improve students’ interaction and how to improve their learning performance. Unlike current studies discussing quantity and quality of interaction separately, this research focuses on the interaction between learners’ interactive centrality which describes interactive quantity, and learners’ interactive quality in the forum on MOOCs. Social network analysis, content analysis and regression analysis will be used to collection and analyze the data from a course on Coursera. Significant correlation between the interactive centrality and quality of interaction was found and thecondition necessary for the relationship between them is discussed in this research.

Keywords: interactive centrality, interactive quality, learning on MOOCs

1. Research Background Connectivism proposes that learning is the optimization of personal knowledge network, emphasizing network formation. The formation of the network consists of two elements: nodes and connections (Siemens, 2005). The main way of the formation of nodes and the establishment of connection is interaction. Diversification of means make interaction not only the key of re- integration in teaching and learning, but also the social communication, information aggregation, content creation and collaborative innovation in the learners’ social network in online education. In the MOOCs environment, due to the features of massive and rich interactive media and numerous learners, it supports to achieve the realization of Connectivism learning. (Cabiria, 2012; Siemens, 2012) In order to promote the development of MOOCs, it’s necessary to study the interaction issues. In the interview of the teachers in Coursera, teachers showed special interests in the relationship between interaction and curriculum learning performance, which help us to form the proposition.

Essentially, interaction can be interpreted in two perspectives: quantity and quality. The quantity can be interpreted as the centrality of learners in their social networks formed by interaction. For the quality, Gunawardena, Lowe and Anderson (1997) proposed the interaction analysis model which can be used to analyze interactive content and obtain the depth of learners’ interaction. With the development of MOOCs, it is important to know whether quantity and quality of interaction forms cross-impact, that is, whether the current location of the learner in the network/ interaction level of learners will directly affect the level of his interactions/ position in the interactive network subsequently.

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Therefore, this study will take learners on a Coursera course as the research object. Since forum is an important way to interact on the Coursera platform, so the study will analyze the data of interaction from the forum.

2. Research Question and Hypothesis The research question of this study is about the interaction between learners’ interactive centrality and quality in the forum on MOOCs, which includes hypothesis that, for the learners in MOOCs, 1) the increase of the centrality of interaction will bring the improvement of the quality of interaction; 2) the improvement of quality of interaction will bring the increase of the centrality in interaction.

3. Research Design 3.1. Subjects and Data Sources Learners of one course from Coursera are the subjects. The course started from 13/5/2013 and ends in 10/6/2013, lasting for 5 weeks. The topic of the course is about the skills that help to write a developed, effective paragraph. Such skills include how to use verbs and subjects, how to use clauses and phrases and so on. Since we want to explore the interaction between learners’ interactive centrality and quality in the forum, we needed a group of subjects that posts every week during the study. We selected those who took part in all the forums’ learning activities in the five weeks, the continuous participants.

3.2. Research Methods In this study, we explore the research question by analyzing the selected learners’ posting performance in the course forum. Data will be collected on weekly basis. Table 1 shows variables, data collection and data analysis methods of these variables. Most of the students successfully completed the instructor’s online course and gave positive feedback on their experience. In order to have more of its students benefit from the online course, USTB will continue to offer the course and produce research on the results of the live global classroom. Table 1. Variables and research methods Variable Indicator Data collection Data analysis methods methods interactive centrality (S) In-degree /Out-degree social network analysis interactive quality (R) mean of interaction content analysis social knowledge construction level relationship between S and R correlation analysis

(1) Social Network Analysis: This study uses social network analysis to obtain the degree of the individual’s interactive centrality. Obtained indicators include individual learners’ weekly in-degree and out-degree in the social network build through the interaction. For an individual learner, in-degree reflects the number of persons responding to the posts of the subject and out-

160 EITT 2013, Williamsburg, VA, USA, November, 2013 Empirical Research on the Interaction between Learners’ Interactive Centrality and Quality in the Forum on MOOCs degree reflects the number of persons who have gotten the respond from the subject. In-degree and out-degree can be used to describe the position of a learner in social network and how wide their interaction is.

(2) Content Analysis: In this study, we analyze the leaners’ posts through the interaction analysis model and calculate learners’ mean of interactive depth as the indicator. There were two researchers who code 60% of the posts from the continuous participants. The software for coding English text was used for the left 40%, using the result of coding from the researchers.

4. Findings 4.1. The Amount of Participants and Posts in the Forum Data about the amount of participants and posts in the course forum comes from two groups, all people who have ever posted (the whole group) and the ones who kept posting during the five weeks (the continuous participants).

(1) Data about the whole group Both the amount of posts and the amount of participants have shown a gradual downward trend. According to Figure 1 and Figure 2, participants involving in the discussion of the first week are of the largest number, which is 4000 and they also gave largest number of post in the five weeks, which is 9906. On the other hand, in the fifth week, the number of students who took part in the forum reaches the lowest, which is 791. And they posted 2090 times, which is also of the smallest number. From the first week to the fifth week, posting declined 78.90%and participants declined 80.23%. The decrease is very large. For every week, the mean of posts of the participants is relatively stable. The maximum comes from the last week, which is 2.64 per participant. The minimum comes from the third week, which is 2.13 per participant. The data above indicates that the downward trend of the performance of posting is obvious and posting behavior is not very stable. There is a great loss of participants and posts. Since the number of posts per participants is relatively stable, the decline of posting mainly comes from the decline of participants in the course forum.

(2) Data about the continuous participants By comparing the list of participants in the five weeks, there are 162 continuous participants who kept posting every week during the five weeks. Figure 3 shows the amount of posts of this group of participants. Participants posted most in the first week, posting 1746 times. And they posted least in the fourth week and the number of posts is 1073, a decline of 38.5% comparing to the amount of the first week. For the five weeks, posting number decreased first and then increased; however, the number of posts is relatively stable. The average of posting per participant every week ranges from 6.6 times to 10.8 times. Data above shows that, comparing to the whole group, the decline of posting of continuous participants is small and the posting behavior of the continuous participants is relatively stable. Meanwhile, although the mean of posting fluctuates, compared to the whole, the levels are still much higher. This stable posting behavior of the group helps us to study the relationship between the interactive centrality of the participants and the content of the posting of the participants.

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Figure 1. Number of posts of the whole group

Figure 2. Numbers of participants of the whole group

4.2. The Relationship between the Interactive Centrality of the Social Network of the Participants and the Level of the Content of the Interaction (1) Descriptive Statistics Among all the five weeks, the maximum of the out-degree of all the continuous participants ranges from 55 to 101 and the maximum the in-degree ranges from 36 to 108. Both of them maintain a high level. In addition, according to the minimum of the five weeks, there are some participants in some weeks only initiated topics and didn’t rely to others posts, leading their out- degree to be 0. And some participants in some weeks posted and received no reply, leading their

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Figure 3. the number of posts of the continuous participants in-degree to be 0. The average of out-degree of all the continuous participants ranges from 4.07 to 6.94 and the average of in-degree ranges from 3.20 to 5.25. In every week, the average of the out-degree is always larger than the in-degree. It means that, for the group, there are more responds they gave to others than the responds they received. Data is show in table 2.

Table 2. Descriptive Statistics of out-degree and in-degree maximum of maximum of Average of the Average of the Statistic out-degree / in-degree / out-degree in-degree Weeks minimum of out- minimum of in- degree degree week 1 78/0 75/0 6.94 5.25 week 2 72/0 66/0 6.15 5.07 week 3 81/0 51/0 4.88 3.91 week 4 55/0 36/0 4.07 3.20 week 5 101/0 108/0 4.44 3.69

The content analysis framework of Gunawardena, Lowe and Anderson is used to evaluate the level of every post of continuous participants in the five weeks. And the average of the levels of every participant is calculated as their final level of interaction in each of the five weeks. Finally, we have got the level of 6856 posts and the average level of every participant in each of the five weeks.

Although the level of the content analysis framework ranges from 1 to 5 (1 is the lowest level and 5 is the highest level), in this research, the highest level only reaches 3(see in table 3). Most of posts are in the level of 1 or 2. According to table 3, the average of the interaction level for all the participants of the five weeks ranges from 1.11 to 1.25.

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Table 3.Descriptive Statistics of interaction level Statistic maximum value of minimum value of Average of the Weeks the interaction level the interaction level interaction level week 1 2 1 1.11 week 2 2 1 1.19 week 3 2 1 1.22 week 4 3 1 1.24 week 5 2.5 1 1.25

(2) Correlation analysis of the interactive centrality of the social network of the participants and the level of the content of the interaction We explored the relationship between the interactive centrality of the social network of the participants and the level of the content of the interaction in three ways and the three ways and the findings are as followed: 1) The first one is to explore the relationship between the point centrality and the levels of content of interaction of the participants in the same week. Here are the findings. First, according to table 3, in week 1, there is a significant positive correlation between the in-degree and the level of interaction, and the index correlation of index is 0.235. Second, there is a significant positive correlation between the out-degree and the level of interaction andthe index correlation is 0.203. Third, according to table 3, in other weeks, there is no significant correlation between the interactive centrality and the level of interaction.

2) Next exploration focus on the relationship between the point centrality of one week and the level of interaction of the participants in the following weeks. For example, we have explored the whether there is a significant correlation between the point centrality of the first week and the level of interaction in week 2, week 3, week 4 and week 5. Data from table 3 shows that, there is no significant correlation between the first variable in one week and the second variable in following weeks.

3) The third one is to explore the correlation between the level of interaction in one week and the point centrality of the following weeks. Data from table 3 shows that, there is only a significant positive correlation between the second indicator of the first week and the in- degree/out-degree in week 2, week 3, week 4 and week 5.The correlation index of the level of interaction of first week and the in-degree/out degree of the second week is 0.186/0.215. However, in other weeks, there is no significant correlation between the level of interaction in week 2, week 3, week 4 and the in-degree/out-degree of their following weeks.

According to the findings above, for the first week, there is significant positive correlation between the interactive centrality and the level of interaction in the same week. There is also a significant positive correlation between the levels of interaction in the first week and the interactive centrality of week 2, week 3, week 4 and week 5. Table 4.Correlation analysis of the interactive centrality and the level of interaction

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Level of Level of Level of Level of Level of interaction interaction interaction interaction interaction in week 1 in week 2 in week 3 in week 4 in week 5 week1 Pearson .235** .079 .002 .057 -.002 Correlation in- degree Sig (2 .003 .319 .982 .474 .982 tailed) N 162 162 162 162 162 Pearson .203** .104 .022 .030 -.008 week1 Correlation out-degree Sig (2 .009 .186 .780 .707 .919 tailed) N 162 162 162 162 162 week2 in- Pearson .186* .120 .100 .107 .083 Correlation degreee Sig (2 .018 .128 .203 .177 .293 tailed) N 162 162 162 162 162 Pearson .215** .135 .132 .090 .094 wee2 out- Correlation degree Sig (2 .006 .087 .094 .255 .234 tailed) N 162 162 162 162 162 week3 Pearson .206** .116 .146 .083 .134 Correlation in-degree Sig (2 .009 .143 .064 .291 .089 tailed) N 162 162 162 162 162 Pearson .276** .149 .117 .098 .085 week3 Correlation out- Sig (2 .000 .059 .139 .216 .283 tailed) degree N 162 162 162 162 162 week4 in- Pearson .185* .050 .081 .072 .058 Correlation degree Sig (2 .018 .532 .305 .364 .460 tailed) N 162 162 162 162 162

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Pearson .223** .138 .110 .044 .091 week4 out- Correlation degree Sig (2 .004 .081 .165 .575 .248 tailed) N 162 162 162 162 162 week5 in- Pearson .188* .042 .068 .012 .033 Correlation degree Sig (2 .016 .599 .390 .878 .676 tailed) N 162 162 162 162 162 week5 Pearson .192* .139 .092 .050 .011 Correlation out-degree Sig (2 .015 .077 .246 .525 .888 tailed) N 162 162 162 162 162

5. Conclusion and Discussion 5.1. When the amount of participants in the interaction is large enough, for individual learners, the wider of social network, the better quality of interaction, which is based on the social network. According to the findings in correlation analysis, the in-degree/out-degree has a significant positive correlation with the level of interaction in the first week. It can be concluded that the wider social network can increase the possibility of higher level of interaction.

What interests us is that significant correlation only appears in the first week and there is no significant correlation in other weeks. A possible reason is the decline of interaction caused by the loss of participants. According to the content analysis framework, interaction gets deeper and deeper step by step. Interaction of higher level is based on the several interaction of lower level. So, a great number of interactions are necessaryfor higher interactions. In other weeks, although the amount of continuous’ posts decreased little, the amount of the whole group’s posts decreased a lot. (There is a decline of 78.90% from the first week to the fifth week) Because of the decline of total posts, the possibility of higher interaction also decreases.

So, it is possible to increase the quality of interaction by encouraging learners to building their social network. But the teacher should ensure that there is enough interaction to get interaction of high level. If there is enough interaction in the forum, the learners who have wider social network are more likely to make interaction of higher level.

5.2. Participants who make interaction of higher level at the beginning of the class are more likely to build wider social network in the following interaction. According to the correlation analysis, there is a positive correlation between the level of interaction in week 1 and the in-degree of week 2, week 3, week 4 and week 5. There is also a positive correlation between the level of interaction in week 1 and the out-degree of other weeks.

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It can be concluded that the better quality of the interaction of a participants in the first week, the wilder of social network they can build in the following interaction.

Like the first conclusion, the significant correlation appears only in week 1. In other weeks, there is no significant correlation. One of the possible reasons is that the number of participants is much larger than other weeks. This makes the intersection between week 1 and other weeks are much larger than the intersection among other weeks. For example, number of participants who posted both in week 1 and week 2 is 1693 and the number of participants who posted both in week 3 and week 4 is only 682.The small intersection limits the influence from the interaction before on the interaction later, for a stable social network hasn’t been built up and is very difficult to be built up.

To get a step further and illustrate the point more clearly, we select 15 threads which involve the most respondents from the third week and analyze the number of interaction between the originator of the thread and the responders in the first and second week. The findings are in table 5. According to table 4, participant A, C, M who posted first in the threads had a little communication with their responders. For others posters, there was no relationship between the first poster and the responders before week 3. So for these participants, the interaction of the third week has no relationship with the first and second week. For the reason, it is hard to use the interaction before to help the interaction later.

Table 5.Relationship building across different weeks Poster Number of Number of The total number of respondents participants in the pre-interaction thread A 32 11 2 B 30 11 0 C 23 9 3 D 17 12 0 E 16 8 0 F 14 6 0 G 14 11 0 H 13 9 0 I 13 10 0 J 12 8 0 K 12 8 0 L 11 4 0 M 11 8 1 N 11 6 0 O 11 4 0

It is hard to build up a influence in interaction and maintain the influence. It is possible due to the loss of participants. And lack of functions help to save the relationship among learners in

EITT 2013, Williamsburg, VA, USA, November, 2013 167 Proceedings of International Conference of Educational Innovation through Technology a forum is another possible reason. Here are some examples of such function. In Facebook, we can keep our relationship with someone we have communicated by add him or her to our friend list. In some platform, learning group can be made and there is different forum for each of the group. However, in forum of Coursera, there is no such function. If such function is available, the influence of early interaction may be greater.

5.3. In the five weeks, there building of social network in one week has no relationship with the interaction level of other weeks. According to the correlation analysis, there is no significant correlation between the in-degree/ out degree and the level of interaction in the following weeks, which means that the influence of social network have little influence on the quality of new interaction. However, since the social network of the participants is relative instable, it is possible that there will be a significant influence if there is a more stable social network. So further research is needed to explore whether the instability of social network limit the influence of social network on new interaction.

References Cabiria, J. (2012). Connectivist learning environments: massive open online courses. In WORLDCOMP’12, The 2012 World Congress in Computer Science, Computer Engineering and Applied Computing. Gunawardena, C. N., Lowe, C. A., & Anderson, T. (1997). Analysis of a global online debate and the development of an interaction analysis model for examining social construction of knowledge in computer conferencing. Journal of educational computing research, 17(4), 397- 431. Siemens, G. (2005). Connectivism: a learning theory for the digital Age. Retrieved from: http:// www.elearnspace.org.Articles/connectivism.htm. Siemens, G. (n.d.). Massive Open Online Courses: Innovation in Education? Open Educational Resources: Innovation, Research and Practice, 5.

168 EITT 2013, Williamsburg, VA, USA, November, 2013 Li, T., Wu, F., & Cao, S. (2013). Personalized design of online learning environments to facilitate self-directed learning. Proceedings of International Conference of Educational Innovation through Technology, 169-174.

Personalized Design of Online Learning Environments to Facilitate Self-Directed Learning

Tongtong Li, Fati Wu Beijing Normal University Email: [email protected], [email protected]

Shihua Cao Hangzhou Normal University Email: [email protected]

Abstract:Self-Directed Learning ability plays an important role in successful online learning. Each learner has different self-direction level: low, moderate, approximate, and high. In this paper, we discussed how to design online learning environments especially learning activities and resources in order to facilitate each student’s self-direction advance to higher level. First, from the concept of learner-centered, we stated that self-directed learning theory is suitable for directing online learning environments design; then, we propose a personalized design framework based on Grow’sStaged Self-Directed Learning Modeland give some design rules and typical examples.

Keywords: online learning environments, distance education, self-directed learning, personalized design

1. Introduction Distance education is implemented through online learning environments, so the design of online learning environments will deeply impact on students’ learning performance. How to design effective and personalized online learning environments has become research focus in the field of distance education.

In the past few years, most designs were under the guidance of traditional class teaching theory, treating online learners as containers who receive information passively, while ignoring their adult learning characteristics. Based on the concept of learner-centered, the design of online learning environments should under the guidance of learning theory suited for adult learners.

Self-Directed Learning is perceived as backbone of adult education theory, which can be seen as the most promising one to direct online learning environments design. So we try to discuss online learning environments design based on this theory, especially explore how to design to facilitate each online learner’s self-directed learning abilities development.

2. Self-Directed Learning Self-Directed Learning is a process that students direct their own learning (Cormick, 1997), in which individuals take the initiative, with or without the help of others, in diagnosing their learning needs, formulating learning goals, identifying human and material resources for learning, choosing

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 169 Proceedings of International Conference of Educational Innovation through Technology and implementing appropriate learning strategies, and evaluating learning outcomes (Knowles, 1975). However, most existing studies focus primarily on SDL process in face-to-face settings, but the level of self-direction needed may change in different contexts especially in online context. In fact, it is generally believed that online learning gives more control of the instruction to the learners (Garrison, 2003; Gunawardena&McIssac, 2003). Some scholars consider SDL critical in distance education settings with its unique characteristic of the physical and social separation of the learner from the instructor or expert as well as other learners (Long, 1998). Recent research in an online distance education indicates that students need to have a high level of self-direction to succeed in online learning environment (Shapley, 2000). The importance of self-direction in learners also can be seen in Guglielmino’s opinion, “our societies move forward through the efforts of dedicated self-directed learners (Guglielmino, 2008).” Moreover, whether a learner can be self-directed is also a key indicator to measure if one learns how to learn, the abilities of self-directed learning are regarded as key competencies in lifelong learning (Harding, 2007).

As stated above, self-directed learning ability is very important for succeeding in online learning, an important design objective of online learning environments should be improving online learner’s self-directed learning abilities.

3. Personalized Design Framework As self-direction is a personal intrinsic attribute, there exist significant differences among learners. Based on the Staged Self-Directed Learning Model of Gerald Grow (Grow, 1991), the self- direction of learners can be divided into four levels (see Table 1): low, moderate, approximate, and high. Students at different level have disparate characteristics and teachers play various roles.

Table 1.The self-direction level Level Student’s characteristic Teacher’s role Low Dependent Authority, Coach Moderate Interested Motivator, guide Approximate Involved Facilitator High Self-directed Consultant, delegator

In accordance with learner-centered concept, on one hand, online learning environments design should suit for adult learners’ characteristics; on the other hand, the design should be personalized (considering differences among learners). Based on Gerald Grow’s model, we proposed the personalized design framework (see Figure 1).

Personalized design of online learning environments is to match the learner’s level of self- direction and help the learner advance to higher levels. As Figure1 shows, specific design of components in online learning environments, including learning activities, resources, supports, and tools, should be proposed for learners according to their self-direction level. The class A, B, C represents three design patterns, which gives design rules and typical examples to support learners of different levels of self-direction to advance respectively.

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Figure1. Personalized design framework of learning environments to facilitate self-directed learning

4. Strategies for Personalized Design 4.1. Analyze and Elaborate Self-Directed Learning Ability In order to get more specific personalizing strategies, the components of self-directed learning ability should be analyzed and elaborated. Based on review on related publications, self-directed learning abilities may include: meta-cognitive, self-management (goals-management, time- management), self-planning, monitoring progress towards goals, self-reflection (reflecting on one’s learning process and outcomes), and self-evaluation ability. There are different strategies to facilitate different component abilities development. Different learners have different levels of each component, different activities and tools should be provided. From actively attending in self-directed learning activities and forming self-directed learning habits, learners gain different component abilities development.

4.2. Locate Each Learner at a Certain Stage The Self-Directed Learning Readiness Scale (SDLRS) developed by Guglielminois used to locate each student at a certain stage (Guglielmino, 1978). According to their scores distance learners were divided into four groups. At the same time, learners’ self-direction level is dynamic; E-portfolio should be used to record their dynamic learning process, which will be used for measuring the development of learners’ SDL abilities.

4.3. Personalized Design Patterns Pattern A, B, C gives basic rules and strategies for learning environments design to facilitate each group’s self-direction advance to next stage respectively. We only discuss the design of the two most important components of learning environments: activities and resources.

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Table2.The personalized design patterns Pattern C B A From Low to From Moderate to Student’s level From Approximate to High Moderate Approximate Student’s From Dependent to From Interested to From Involved to Self- characteristic Interested Involved directed Teachers set goals. Teacher helps student Teacher gives direction, Teachers give set goals. student sets goals by more synchronous Teachers give themselves. online direction and some synchronous Teachers observe learners’ explanation. online direction and study and give suggestions Teachers give explanation. Activities when students call help. immediate feedback. Teachers give feedback Typical activities: Group Typical activities: periodically. projects, Internship, Coaching, Drill, Typical activities: Dissertation, Individual Inspiring lecture Discussions, Seminars, work, Self-directed study plus guided Group programs group. discussion. facilitated by teacher. Redundant materials, Clear instructions, Redundant materials Various materials not Detailed with guidelines. restrict to goal-related. explanation. Resources Typical examples: Typical examples: Typical examples: Guide book, Exercise, Background materials, “How-to” videos, Blogs, Wiki Unsolved reality problem, Exercise, Test logs, Wiki

In table 2, since each pattern has different objective, we give the rules of design and typical examples. As learning tools and supports design, it can be recommended dynamically based on the need of activity implement and students’ abilities status.

5. Conclusion There are some limits in this research: the paper mainly proposed a personalized design framework, its feasibility, practicality and validity needs further test through practice; the personalization is relative, we just divided learners into four groups; since online learning environments is more and more complicated, we discuss only pedagogic aspects including learning activities and learning resources design. Practice and experiment research will be conducted in follow-up studies.

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References Garrison, D. R. (2003). Self-directed learning and distance education. In M. G. Moore &W. Anderson (Eds.), Handbook of Distance Education (pp. 161-168). Mahwah, NJ: Lawrence Erlbaum. Grow, G. O. (1991). Teaching learners to be self-directed. Adult Education Quarterly, 41(3), 125- 149. Guglielmino, L. M. (1978). Development of the Self-Directed Learning Readiness Scale (Doctoral dissertation, ProQuest Information & Learning). Guglielmino, P. J. (2008). Productivity in the workplace: The role of self-directed learning and the implications for human resource management. International Journal of Human Resources Development and Management, 8(4), 293-305. Gunawardena, C. N. & McIssac, M. S. (2003). Distance education. In D. H. Jonassen (Ed.), Handbook of Research for Educational Communications and Technology (pp.355-395). Mahwah, NJ: Lawrence Erlbaum. Harding, T. S., Vanasupa, L., Savage, R. N., & Stolk, J. D. (2007).Work-in-progress-Self-directed learning and motivation in a project-based learning environment. In Frontiers in Education Conference-Global Engineering: Knowledge Without Borders, Opportunities without Passports, 2007. FIE’07. 37th Annual (pp. F2G-3). IEEE. Knowles, M. S. (1975). Self-directed learning. New York: Association Press. Long, H. B. (1998). Developing paradigms for self-directed learning. Oklahoma: University of Oklahoma. Pilling-Cormick, J. (1997).Transformative and self-directed learning in practice. New Directions for Adult and Continuing Education, 74, 69-77. Shapley, P. (2000). On-line education to develop complex reasoning skills in organic chemistry. Journal of Asynchronous Learning Networks, 4(2). Retrieved from: http://www.sloan-c.org/ publications/jaln/v4n2/index.asp

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174 EITT 2013, Williamsburg, VA, USA, November, 2013 Liu, G., Chen, Y., & Zhou, Y. (2013). Study of second life based on learning activities in inquiry-based learning system Proceedings of International Conference of Educational Innovation through Technology, 175-182.

Study of Second Life Based on Learning Activities in Inquiry-Based Learning System

Geping Liu Southwest University Email: [email protected]

Yingbo Chen Ankang University Email: [email protected]

Yiliu Zhou Southwest University Email: [email protected]

Abstract: This article aim at present problems under the inquiry-based environment, combined with the advantage of Second Life and Sloodle learning platform, then designed inquiry learning environment based on Second Life, and at last elaborated the process of the environment technology.

Key Words: Second Life, Inquiry-Based Learning, Learning Activity, Sloodle

1. Introduction At present, the New Curriculum Reform is executing in the area of Basic Education (Elementary and Secondary Education) in China. We have learned that independent autonomous learning is encouraged, and how to improve the students’ initiative to learn and inquire is one of the focuses in this reform (Yang, 2010). There are many articles focus on the design and practice of Inquiry- Based Learning currently (Litmanen, 2012; Kolloffel, 2011; Erlandson, 2010).

However, in the present learning environment, there are some deficiencies in Inquiry-Based Learning. It can’t create vivid learning situation to help learners to start an Inquiry-Based Learning activity and support suited explore tools to implement an Inquiry-Based Learning activity. It can’t integrate the management of learning process and the learning contents yet. This article proposes a solution that creates Inquiry-Based Learning environments and organizes Inquiry- Based Learning activities with 3D virtual world: Second Life and Sloodle. That is, on the one hand, creating lifelike learning environments and exploring tools with the modeling tools in Second Life and Linden scripting language, on the other hand, managing and supporting the process of Inquiry- Based Learning with Sloodle. There are several traits of the created learning environment in this study: strong situational, interactivity, and opening-up learning space, which could develop the students’ creativity.

2. Design of Second Life Based of Inquiry Learning Activities The study analyzes two critical factors which are hardware parts and software parts to design the learning activities. The hardware sections include three elements: virtual environments, resource

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 175 Proceedings of International Conference of Educational Innovation through Technology environments, and support tools. And the software sections include the learning activities and the organizing environments .Based on five factors, centered on the design of learning activities, this article design a Second Life Based of Learning Activities model, which is shown in Figure 1. Based on the virtual environments, the five factors mentioned above are connected closely. The learning resources and the support tools cooperate with each other to support the whole process of the learning activity, and the learning activity certainly is the core of the whole learning environment.

Figure 1. Second Life Based Inquiry Learning Environment Model

This article takes an example of the theme of exploring ocean world to show how to guide the learning activity. The flow map of the theme is shown in the Figure 2 below.

2.1. Plan Themes and Goals Teachers should plan the themes and goals of the inquiry activity according to the learners’ characteristics before starting a learning activity. Especially, the teachers choose low structured problem situations and interesting problems when setting problems so as to stimulate the learners’ desires. This article chooses exploring the ocean world as the theme and the goals are set as follows: learners should know of the kinds of sea creatures by inquiry; learners should grasp the physical traits, lives habits, physiological functions and food chains of sea creatures by experiencing the learning activity; learners should know of the diversity of sea creatures, learn to appreciate their lives and understand the importance of protecting marine environments.

176 EITT 2013, Williamsburg, VA, USA, November, 2013 Study of Second Life Based on Learning Activities in Inquiry-Based Learning System

Figure 2. Flow Map of Second Life Based of Learning Activities

2.2. Design the Inquiry Tasks Teachers should design instructional objectives in the form of sub-tasks, learners could achieve the goals by completing specific targets. The degree of difficulty must be kept in the zoneof proximal development and the tasks should represent the effects and activities that the learners want to take part in.

2.3 Create Inquiry Situation In Inquiry-Based Learning activities Based Second Life, which provided 3D modeling tools and Linden Script, teachers use them to create activities, listed in Table 1. Take an example, the teacher represent a section report about marine pollution. Then the teacher said like that, The Ocean is the origin of life on Earth. Nowadays, the pollution of marine environment has been severely influenced the existence of marine life. In order to protect marine life, we will submit a report on current situation of marine life to the relevant departments. All of you will be divided into several groups to have an inquiry study. And we will share our research achievement after two weeks and then submit our research report. According to this way, this case study conducts learner to the problem situation.

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2.4 Experience Inquiry Situation The central link of inquiry learning activities is through experience. We can explore the virtual learning environment to complete the inquiry task and solve practical problems. In specific situations, learners collected information that related to the task, through field visited, first-hand experience, assessed to data and info, people interviewed, virtual experiments, seminars and other forms, to obtain reliable data, what prepare for the research achievements. This study took the specific inquiry process about the explore groups of marine fish on Exploring the Ocean World for example, introduced the process of experience exploration activities, as shown in Table 1.

Table 1. The Process of Inquiry Activities on Exploring the Ocean World Inquiry Inquiry Tasks Inquiry Activities Places Seeking for information on marine fish, to learn the Learners are Virtual types of marine fish, its physical characteristics, physical divided into Library structure, habits, fish food chain, etc. four groups Labeled the marine fishes to count the types in the virtual to explore Virtual ocean, to observe the physical characteristics of various the types of Aquarium marine fish types of fish. and the Virtual The avatars of learners into various types of fish living in physical Museum the ocean, through virtual operating experience the fish characteristic Experience living, then summary up the habits of various types of fish. s, physiologic al structure Virtual Anatomy the model of various type fish, to observe its and habits of Library internal structure and physiological structure. the varieties of fish. Then Through viewing text, images, video, specimens and Virtual summary up models to understand the marine fish species, physical Gallery the hierarchy characteristics, physical structure and habits. of the food chain of Virtual In the end, by group communication and display, to marine fish. Lecture summary up the fish food chain structure.

2.5 Show the Gains Each team member showed and exchanged the variety of information at this section that them obtained them under the inquiry scenario in the form of images, videos, models, then shared their experience and evaluate each other.

2.6 Summarize and Evaluate After the exchange between the groups, getting a preliminary conclusion, then the teachers and peers evaluated the groups’ conclusion and the learning process, get the final conclusion. Evaluations of inquiry-based learning activities are diversified. For instance, we can take advantage of the reflection tool of evaluation under the environment access to the records of the learners’ learning, and give the process evaluation on learner. Also, we give the summative evaluation aimed

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at the learner’ works, while encouraged self-assessment, peer assessment, teachers’ evaluation and in other multi-angle evaluation way, to make the entire evaluation more scientific.

After the evaluations have completed, teachers would sum up the evaluations of the inquiry activities, reflected that was the reflection of the whole activity. At the same time, we arouse the learners to think deeply also encourage them to begin new exploration activities. The conclusion of Exploring the Ocean World was designed that learners report the team achievements in the virtual lecture hall, obtained teachers and experts affirmed.

3. The Realization of Technologies of Inquiry-based Learning Environment Based on Second Life 3.1 The Realization of the Internal Virtual Environment of Second Life The internal virtual environment of Second Life means a virtual world which is exploited by tools of modeling, Linden Script, some other 3D modeling software such as Blender and 3DMAX and graphic processing software just like Photoshop. The world is composed orderly by many kinds of visual objects (PRIM, the basic units which are used by users to create objects). Basing on virtual library, the paper builds various places in the virtual space exemplified in Table 1.

3.2 Realization of the Sloodle Platform Functions 3.2.1. Structure of Sloodle platform. Second Life virtual learning environment can provide an immersive learning environment, and on this basis, Sloodle system can realize the tracking and management of the learning process. In this study, we associate Second Life with Sloodle and bring them to maximize their potentials to the fullest to support learning activities. Sloodle platform functions are shown in Figure 3.

Figure 3. Inquiry-based learning platform supported by Sloodle

3.2.2. Link between Second life and Moodle. The two modes of link between Second Life and Moodle are as follows: A. Try to modify the database and code of Moodle to link to Second Life. Modify the database and the code of Moodle platform so that it can link to the Second Life. We should use application programming interfaces and HTML, linden script language and the two platform exchange parameters through the XML - RPC remote method. Second Life's built-in linden script language offers many ways to make communicate with external web server. Such as Second Life send mail to the Internet of the E-mail via the Object, It also can send data to

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the web server by XML - RPC and HTTP requests. This is the common extension method of internal Second Life resources offer. B. Bring the learning content of Moodle into Second Life directly. In this method, the Linden Script will be able to achieve. In this way, the system can get resources in the form of Web links, and it is just a copy of the web interface. The first plan has a great advantage in building a virtual learning environment, but requires more technical requirements.

3.2.3. Structure of Sloodle. The data layer, logic layer and presentation layer constitute the structure of Sloodle. The user's account, password, homework files, interaction records and chat logs in the data layer, and all the data are stored in the database. The interactive features of the system, online interaction, experimental operation, and skills training are in the logical layer. Logic layer comprises the logic layer of Moodle and Second Life, and the logic layer comprises the logic layer of Moodle and Second Life, the logic layer of Moodle is implemented by PHP script stored in server contacting with database, and the logic layer of Second Life is implemented by Linden script, which permit users to u create objects in the client through the network, e-mail , XML Remote Procedure Call（XML—RPC）and HTTP request, etc. to contact with external server. The logic layer of Second Life is implemented by HTML format and 3D interactive objects. Users can enter the Moodle system through browser and connect to the server by HTTPS. The script of server can check whether the user has permission to enter or reply. In principle, the interactive record will be kept in the Moodle database while the users are interacting with the Second Life client. Sloodle and Second Life communication architecture are shown in Figure 4.

Figure 4. Support the Sloodle structure with Inquiry-Based Learning activities

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4. Conclusion This study takes advantage of the situational, open, interactive features on Second Life, combined with learning activities management and learning process record functions of Sloodle, to produce the inquiry learning activities based on the Second Life and provide a reference to implement the effective inquiry learning.

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References Erlandson, B. E., Nelson, B. C., & Savenye, W. C. (2010). Collaboration modality, cognitive load, and science inquiry learning in virtual inquiry environments. Educational Technology Research and Development, 58, 693-710. Kolloffel, B., Eysink, T. H. S., & De Jong, T. (2011). Comparing the effects of representational tools in collaborative and individual inquiry learning. International Journal of Computer-Supported Collaborative Learning. 6, 223-251. Litmanen, T., Lonka, K., Inkinen, M., Lipponen, & Hakkarainen, K. (2012). Capturing teacher students' emotional experiences in context: does inquiry-based learning make a difference? Instructional Science, 40, 1083-1101. Luo, J., Liu, G., & Xie, T. (2011). Design and realization of second life based learning environment in virtual library. China Distance Education, (1), 81-82. Xie, T., & Liu, G. (2010). Construction of problem-based learning environment in Second Life. Modern Educational Technology, (3), 108-110. Yang, L. (2010). Reflection for thei nquiry learning under new curriculum reform. New Curriculum Research, 191, 122-123. Zhang, G. (2010). Preliminary exploration on education applications of sloodle based in the distributed virtual learning system. Modern Educational Technology, (6), 79-81. Zhang, L., Li, Y., & Duan, A. (2008). Inquiry-based learning in virtual quest virtual network environment. China Audio-Visual Education, (10), 74-76.

182 EITT 2013, Williamsburg, VA, USA, November, 2013 Ma. J. & Li, Y. (2013).On using corpus-integrated peer review for the EFL College learners in China. Proceedings of International Conference of Educational Innovation through Technology, 183-192.

On Using Corpus-integrated Peer Review for the EFL College Learners in China

Junming Ma, Caiqiang Li Southwest University Email: [email protected]; [email protected]

Abstract: This longitudinal case study sets up an online peer review system and explores in this system online peer review aided with corpus for an English class of 37 EFL Chinese college learners over one year. Based on analyses of the electronic feedback the learners received, comparison of their initial and revised drafts, and follow-up questionnaire as well as interviews, the study shows that corpus-integrated online peer review in combination with teacher review is preferable for the college English learners.

Keywords: corpus-integrated, online peer review, teacher review, EFL college learners

1. Introduction Learning to write fluently and expressively is presumably the most difficult macro-skill for language learners, especially for second or foreign language learners. In China, college English learners in their writing display problems ranging from vocabulary to syntax and from structure to content, and achieve little encouraging and steady progress in English writing regardless of whether their English teachers review their writings thoroughly or not. What might be the efficient and beneficial way of giving feedback on the writing of the college English learners?

2. Literature Review Peer review emerges as a promising way of giving feedback and helping learners on their writing as the process approach to writing gains preference. In peer review, learners give each other feedback on writing-in-process in order to encourage revision and improvement in performance. Peer review enhances learners’ autonomy and responsibility for their writing, sharpens learners’ awareness of the shortcomings and strengths of their writing, increases learners’ motivation, helps in learners’ writing performance and language acquisition, and develops learners’ self-confidence (Jacobs, 1989; Hedgcock & Lefkowitz, 1992; Tsui, & Ng, 2000; Yang, Badger & Yu, 2006; Lundstrom & Baker, 2009).

Peer review occurs traditionally through the medium of paper or by face-to-face conference. With the development of education technology, some attempts are made to conduct peer review through the medium of the internet. Online peer review is regarded as having higher degree of genuineness and frankness in contrast to written or face-to face peer review (Jiang, 2005; Guardado & Shi, 2007). In our initial effort to employ written peer review, we found that writing in the paper form was prone to tear and loss and the communication between peers were not convenient, which can be perfected by writing electronically.

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The successful carryout of peer review can be affected by learners’ perception of it, classroom atmosphere as well as the training of peer reviewing (Nelson, & Carson, 1998; Berg, 1999; Min, 2006; Wang, 2007). It is vital to get learners mentally and technically ready for peer review before employing it for giving feedback. The goal of getting learners ready can be achieved by providing to them training or guidelines. As for the design of either training or guidelines, there are little sources available.

There is another issue which little research has addressed. EFL learners generally express little confidence and uncertainty in peer commenting due to their perception of their linguistic competence. They need linguistic support for writing and commenting. How can linguistic support for writing and commenting be provided to maximize the efficiency of peer review?

Corpus is a massive collection of natural texts, which are mostly products of real life situations. Study of the use of natural language allows learners to get a better “feeling” for the language and learn the language like it is used in real situations. Such a learning process is data-driven, and learners are self-promoted to learn and to structure their knowledge of the language. Moreover electronically readable corpora reduce dramatically the time needed to find particular words or phrases with the highest degree of accuracy.

In the light of the features of corpus and linguistic needs as well as cognitive levels of learners, it is feasible to integrate corpus into our peer review. However, a scatter of research is available on the integration of corpus into peer review.

3. Research Description The research is undertaken in an EFL class of 37 college students in China over one year. It explores the integration of corpus into peer review, of which research resources are quite meager.

3.1. Research Questions In this exploratory study, we mainly address the following three questions: 1) Is online peer review preferable for EFL college learners? 2) How can learners be better prepared for peer review? 3) How can corpus be integrated into peer review to maximize linguistic support for writing and commenting?

3.2. Data Collection and Analysis Learners’ initial and revised drafts for each writing task are collected and compared in the light of the feedback they received. By comparing their different drafts, we can examine the effects of feedback upon their writing. A follow-up questionnaire is employed at the end of this longitudinal study to see the learners’ perception and evaluation of our peer review mode. Individual semi- structured interviews are also carried out to gain in-depth understanding of learners’ views on our peer review. The data collected by means of questionnaire is analyzed by statistics and data from interviews is analyzed by theme.

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3.3. Research Procedures 3.3.1. Needs Analysis We first analyze learners’ needs of peer review prior to the employment of it. We randomly interview several learners of different linguistic levels and find that some of them question the legitimacy of peer review. The main reasons for the skepticism are 1) they are not confident about the linguistic competence of themselves and their classmates; 2) they want to rely more on teacher review. We need to provide them with linguistic support to relieve their doubts and develop their confidence so as to get them both mentally and linguistically ready for peer review.

3.3.2. Online Peer Review System Design Based on the analysis of learners’ needs, we set up an online peer review system.

Figure 1. The structure of online peer review system

1) Online Peer Review System The system consists of a link to a free online corpus and four main sub-systems: student- to-student communication system, student-to-teacher communication system, bulletin board and supervision system. In student-to-student communication system, students can accomplish their peer review tasks and exchange their comments on the writings. Students can communicate with other peers within groups or out of their groups by means of in-group communication and between- group communication. In student-to-teacher communication system, the teacher and a student can initiate a chat about writing and commenting. Bulletin board posts some useful resources, such as the guidelines of peer review, guides to the corpus and the peer review system, the criteria for final evaluation, requirements and FAQ. Supervision system is designed to supervise writing and commenting, which is still under construction.

2) The Corpus The corpus that the peer review system draws references to is called the Compleat Lexical Tutor. It is developed by Tom Cobb and comprises three major sections according to the user’s identity: learners, researchers and teachers. For learners section, it gives learners an opportunity to learn and test vocabulary and grammar. For researchers section, it divides into several parts, such as Range, Vocabprofile, Concordance, Text tools, etc. It helps users to find out the use and the

EITT 2013, Williamsburg, VA, USA, November, 2013 185 Proceedings of International Conference of Educational Innovation through Technology frequency of a word in texts and lexical knowledge of a text writer. For teachers section, teachers can devise for their students vocabulary exercises, like cloze and spelling.

Figure 2. The homepage of the Compleat Lexical Tutor

For our online peer review, we mainly make use of Vocabprofile and Concordance in the section of researchers. By using Concordance, students can figure out the use of a word or phrase in natural situations and learn to use them. By using Vocabprofile, students as well as the teacher can find out the lexical knowledge of a student writer. Students are also encouraged to explore the functions in the learners section.

3.3.3. Grouping 37 students form 6 groups, six or seven peers a group. Writings are basically reviewed within groups. Students are asked to at least review a paper of a group member. They are also encouraged to comment on the compositions of others out of their group. Group members can decide the order of commenting, in other words, who they would like to review each time.

In order to get students actively involved in peer review, grouping used in peer review is that we apply to classroom activities. In our daily classroom activities, we maintain the same grouping, saving the effort to rebuild group cohesion for a new group. Members are quite familiar with each other, and know better how to present a telling critique of peers’ writing.

3.3.4. Training Prior to the implementation of peer review, we spend about a month on kinds of training, namely, the use of the Compleat Lexical Tutor, techniques of peer review, the criteria for final evaluation, and the use of online peer review system. Each training session deals with one training topic.

Generally every training session goes through the following stages: 1) Teacher’s presentation. The teacher demonstrates the use or explains to the learners the materials relevant to peer review. 2) Group discussion. Learners in groups discuss what the teacher has presented, sharing their

186 EITT 2013, Williamsburg, VA, USA, November, 2013 On Using Corpus-integrated Peer Review for the EFL College Learners in China understanding and crystallizing their puzzles. 3) Question and answer. Learners present their questions concerned and the teacher offers clarification. 4) Practice. Learners make use of and get themselves familiar with what the teacher presents. 5) Follow-up discussion. Learners in groups share their further understanding and use and clear their puzzles with the help of the teacher. When the training ends, we start the implementation of online peer review.

3.3.5. Implementation Students are asked to write six essays altogether in two terms. For each essay, they spend ten days writing, ten days commenting, and ten days revising. The teacher reviews some writings online and gives comments on the writing as a whole in the class after learners finish their peer review. Then learners are expected to revise their essay and submit a final draft.

When the students are not sure about the use of certain expressions during writing or commenting, they can consult the Compleat Lexical Tutor by clicking to Concordance. Concordance gives a list of several words, phrases, or distributed structures along with immediate contexts, from a corpus or other collection of texts for language study. Here is a picture of sorting the use of the word “aggressive” by using its sentence concordance.

Figure 3. Sorting the word “aggressive” by sentence concordance

The sorting results are not fully presented here for the restricted space. The word sorted is aligned center in a different color. If the user clicks the word sorted on the result list, he can get the original text in which the sorted word is used. By sorting a word or words, learners can also observe the collocation of expressions, the pragmatic functions of expressions, the differences between synonyms, and some new words, which are seldom presented in a dictionary. The corpus thus can offer substantial help in learning and using expressions appropriately.

When a student wants to know the lexical knowledge of a peer or himself, he can consult Vocabprofile, which offers an immediate lexical evaluation of the passage inserted. Vocabprofile

EITT 2013, Williamsburg, VA, USA, November, 2013 187 Proceedings of International Conference of Educational Innovation through Technology on the Compleat Lexical Tutor is based on Laufer and Nation’s Lexical Frequency Profiler. It divides the words of texts into first thousand level (K1 words), second thousand level (K2 words), academic word level (AWL), and technical (MED) words or “offlist”. It estimates lexical proficiency by calculating tokens, types and type-token ratio of a text. Token refers to the number of words in a text, while type means the number of different words in the text. Type-token ration is calculated by dividing the number of different words (type) by the number of words (token) in a text. The closer type-token ratio is to 1, the higher lexical proficiency as well as the more complicated structure of a text is. Vocabprofile also presents type and token as well as percentage of words in different levels, which gives another angle to view the lexical proficiency in detail. Figure 4 below presents a profile of a student writing by Vocabprofile.

Figure 4. A profile of a student writing by Vocabprofile

The figure is divided into four sections. The third section from the top shows the statistics of the student writing in terms of type, token and type-token ratio. The bottom section presents the student essay in different colours, which differentiate the word categories ranging from K1 words to offlist words.

Words in this student composition (tokens) are up to 427, and different words (types) total 216. So the type-token ratio of the passage is 0.51. The words the student used mainly fall into K1 category, accounting for 83.37%. As for its K2, AWL and offlist, the percentages are 7.03%, 4.45% and 4.92% respectively. According to Ringbom (1998), the percentages of K1, K2, AWL and offlist of writings by native English learners are 70%, 10%, 10% and 10% (Liu & Hu, 2012: 68). In light of these percentages by native learners, we can see that the student concerned overused K1 words and underused K2, AWL and offlist, with AWL ranking last. According to Liang, Li and Xu (2010:138), the percentages of AWL and offlist are improved standards in text complexity. In other words, the student can reach a higher level of writing by avoiding overusing K1 words and increasing the use of AWL and offlist words.

We also encourage the students to paste their drafts on an essay- scoring web called Pigai, which can give an essay an instant grade and some revision suggestions mainly for grammar. In addition, it is important to remind the students of the grading criteria for final evaluation while they do revising and reviewing. In such a way they know what is expected of them in their essays.

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The students can revise their writings by themselves according to the feedback from Pigai and the Compleat Lexical Tutor and in light of the criteria. After they are sure about their essays, they can hand in their electronic writing in online peer review system, waiting for commenting by their peers. The peer reviewers can also make use of the Compleat Lexical Tutor when commenting. The reviewer and the writer can communicate with each other for clarification when commenting by means of in-group communication system and between-group communication system. They can chat with each other online or leave messages to each other if one is not available online at that time.

After receiving the feedback on the writing from a peer as well as the teacher, the student writer can revise his writing and hand in the final draft.

4. Findings and Discussion With the analysis of the electronic feedback the learners received, comparison of their initial and revised drafts, and follow-up questionnaire as well as interviews, we record the following main findings.

4.1. The Majority of the Students Prefer Online Peer Review to Paper-form or Face-to-face Peer Review.

Figure 5. The students’ preference for peer review through different media

In Figure 5 the data from questionnaire shows that the majority of the students (81%) prefer online peer review to paper-form (14%) and face-to-face peer review (5%).

The chief reasons for such a preference stated in the interviews are 1) convenience. The students say that it is convenient for them to hand in and review the essays of classmates. They can easily communicate with each other with little time- or place-restriction. 2) an easy access to corpus. The students report that they can access the corpus when writing and commenting, which provides immediate help to them. 3) reading more peer articles. They can enjoy as many other articles of peers as they like, and read their commenting. They learn to improve their writing and reviewing from their classmates.

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4.2. The Students Report Gains of Varied Kinds from Peer Review.

Figure 6. The students’ gains from peer review

A multiple-choice item in the questionnaire asks the students to decide the top three writing- related benefits they reap from peer review, which is depicted in Figure 6.

Among the benefits reported by the students, improving grammar, developing ideas and achieving coherence rank top. The students obtain content-level benefits as well as grammatical benefits.

An analysis of the electronic feedback the learners received indicates that the learners give both grammatical feedback and content-level feedback in light of the criteria for final evaluation presented by the teacher. The students are suggested by their peers to polish their writing by adding some convincing examples to the argument, deleting certain irrelevant sentences or examples, presenting a new and concise beginning or conclusion, etc.

A comparison of the students’ initial and final drafts confirms the varied benefits reported in the questionnaire. The students on the whole are more careful in spellings, the grammar, and the use of the word. They also add or delete some sentences or examples, change sentence patterns and orders, and alter transitional expressions, etc.

4.3. The Corpus Offers Inspiring and Constructive Feedback on Their Revising and Reviewing. The students interviewed generally show a favorable attitude towards the use of corpus. They say that Vocabprofile helps them look at their word knowledge in a critical and scientific way, of which they have never been aware. With the analysis by Vocabprofile, they pay increasing attention to the word use in the writings, trying to increase the K2 words, AWL and offlist words in their writings. Their awareness of word use in writing is sharpened, which is a long-term benefit.

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Concordance is quite interesting and inspiring. It is easy to search for an expression with abundant feedback. Learning expressions in natural situations is inspiring and delightful. When encountering an unfamiliar expression in an article of a peer, they find it convenient and useful to consult the corpus. Besides, they like to explore the other functions of the Compleat Lexical Tutor.

Initially some students shied away from the corpus, assuming it impossible for them to use such a source. With constant help from the teacher and their peers, they gradually pick up their confidence and begin to use the corpus and to incorporate the use of the corpus into their writing and commenting.

5. Conclusion This paper reports the practice and findings of our corpus-integrated online peer review for our EFL College students. When doing revising and reviewing, the students derive writing support from different sources, such as the Compleat Lexical Tutor, peers and the teacher. They display gains of content-level and grammar-level in their writings. Our students perceive the corpus- integrated online peer review as beneficial to the development of English writing skills and boost confidence in English writing.

References Adolphs, S. (2006). Introducing electronic text analysis: a practical guide for language and literary studies. London: Routledge. Berg, E. C. (1999). The effects of trained peer response on ESL students’ revision types and writing quality. Journal of Second Language Writing, 8 (3), 215-241. Cai, J.G.. (2011). A comparative study on online peer review and teacher review for Chinese college students. Foreign Language World, (2), 65-72. Campbell, C. (2003). Teaching second language writing: Interacting with text. Beijing: Foreign Language Teaching and Research Press. Carson, J. G. & Nelson, G. L. (1994). Writing groups: Cross-cultural issues. Journal of Second Language Writing, 8 (3), 215-241. Guardado, M. & Shi, Ling. (2007). ESL students’ experiences of online peer feedback. Computers and Composition, 24 (4),443-461. Hedgcock, John & Lefkowitz. (1992). Collaborative oral/aural revision in foreign language writing instruction. Journal of Second Language Writing, 1 (3), 255-276. Jacobs, George. (1989). Miscorrection in peer feedback in writing class. RELC Journal, 1, 68-76. Jacobs, G., Curtis, A., Braine, G. & Huang, Su-Yueh. (1998). Feedback on student writing: Taking the middle path. Journal of Second Language Writing, 7 (3),307-317. Jiang Yuhong. (2005). The effect of online peer review on the development of writing competence. Foreign Language Teaching and Research, 37 (3), 226-230. Lee, G. & Schallert, D. L. (2008). Meeting in the margins: Effects of the teacher–student relationship on revision processes of EFL college students taking a composition course. Journal of Second Language Writing, 17 (3), 165-182. Lian, Macheng, Li Wenzhong & Xu Jiajin. (2010). A course of corpus use. Beijing: Foreign Language Teaching and Research Press Liu, Y.S. & Hu,Z.J. (2012). Autonomous vocabulary learning and assessment based on online free corpus The Compleat Lexical Tutor. Shandong Foreign Language Teaching, (6), 64-69.

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Lundstrom, Kristi & Baker, Wendy. (2009) To give is better than to receive: The benefits of peer review to the reviewer’s own writing. Journal of Second Language Writing, 18 (1), 30-43. Min, Hui-Tzu. (2006). The effects of trained peer review on EFL students’ revision types and writing quality. Journal of Second Language Writing, 15 (2), 18-141. Mendonca, C. & Johnson, K. (1994). Peer review negotiations: Revision activities in ESL writing instruction. TESOL Quarterly, 28 (4), 745-769. Nelson, G. L. & Carson, J. G. (1998). ESL students’ perceptions of effectiveness in peer response groups. Journal of Second Language Writing, 7 (2), 113-131. Tsui, Amy B.M. & Ng, Maria. (2000). Do secondary L2 writers benefit from peer comments? Journal of Second Language Writing, 9 (2), 147-170. Wang Ying. (2007). Review of research on feedback in second language writing. Journal of Shandong University, (5), 48-52. Yang, Miao, Badger, Richard, & Yu, Zhen. (2006). A comparative study of peer and teacher feedback in a Chinese EFL writing class. Journal of Second Language Writing, 15 (3): 179-200. Yang, Miao. (2006). A comparative study on teacher review and peer review in English writing in China. Modern Foreign Languages, 29 (3), 293-301. Yoon, Hyunsook & Hirvela Alan. (2004). ESL student attitudes toward corpus use in L2 writing. Journal of Second Language Writing, 13 (4), 257-283.

Acknowledgement The research is supported by Social Science Project of Southwest University (SWU06112) and the Fundamental Research Funds for the Central Universities ( XDJK2012C030).

192 EITT 2013, Williamsburg, VA, USA, November, 2013 Nie, Y.,Jiang, T., & Yue , S. (2013). The exploration of practice model of network vourses effective teaching . Pro- ceedings of International Conference of Educational Innovation through Technology, 193-202.

The Exploration of Practice Model of Network Courses Effective Teaching

Yong Nie, Tingting Jiang, Sha Yue Shaanxi Normal University E-mail:[email protected], {723180505, 543201756}@qq.com Abstract: Network education is a new form of education, which generated after the traditional education. Network courses teaching is a new teaching form, which generated following the traditional teaching and modern teaching. The wave of education informatization , implementation of network teaching is one of the most important ways of schools’ implement modern education informatization , and how to improve the effectiveness of network teaching has become the major problem to accelerate the pace of education informatization .This article is based on the effective teaching theory ,which analyzes the content and elements of model about network courses effective teaching, constructs the mode of network courses effective teaching from the macro-level, and on this basis, combined with the author’s practice to build a practical model of network courses effective teaching. Keywords: network education; network courses; effective teaching; model 1. The Content Analysis of Effective Teaching Mode of Network Courses Teaching theory expert Bingde Li (1991) in China said: “teaching mode, a stable, systematic and theoretical relatively teaching paradigm, needs teaching ideas’ guidance and around a theme about teaching activities, which is the link between learning theories and teaching experience. “Under the traditional teaching mode, the teacher speaks, students listen, the teacher answers as to students do not understand，the modern network teaching mode emphasizes students' learning specially , stresses organic unity of the leading role of teachers and the dominant status of students. The student is not a container of accepted knowledge passively, but a body of constructing and creating knowledge initiatively.

There are a lot of researches on network teaching mode currently, but is it really effective? At present, the domestic research on effective teaching theory as represented by Professor Qiquan Zhong, Professor Zhong said: "Effective teaching must promote the all-round development of students effectively, and the all-round development of students is an effective way to improve students’ learning skills and enhance the professional standards of teachers (Zhong, 2007).” The effectiveness refers to specific progress or development of students through the teaching of teachers over a period of time mainly.

The author in the text builds the effective teaching mode of network courses according to their many years’ experience in network education, combined with effective teaching and teaching modes. To build the effective teaching mode of network courses, we must clear the network’ position in the network teaching first of all, it is a technique and also a platform, which can also be viewed as a medium. Network teaching, network courses teaching, network courses effective teaching, all networks act as a means of teaching. Based on such understanding, this paper defines the network teaching as “a kind of teaching approach based on web “.With non-linear distribution openly, it provides teaching resources environments wealth abundantly, for the development of the learner’s personality provide optimal educational space, that is, to replace Newtonian (Li, 1992)

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 193 Proceedings of International Conference of Educational Innovation through Technology mechanics with Einstein’s space-time view (Du & Liu, 2013), providing favorable conditions for development of learners ‘ personality.

To build the effective network courses teaching mode, there must have the following three levels:

First, from technical aspects to think about, network teaching passed information by modern educational technology, teaching and learning is the issuer and receiver of information, or is similar to information sender beginning and the receiver terminal, it is interactive, open, free, sharing and equal. Network courses teaching is different from traditional teaching, whose direction is pointing to the future; and network courses teaching is different from modern teaching, which points to now and view learners as tools to adapt to the real needs, resulting in a loss on the value of human civilization; network courses teaching advocates the practice and innovation, represents the beauty of the human civilization society, encourages people to pay more attention to information in the future. So, if there is no modern education technology, network course teaching doesn’t matter.

Second, the social aspects of rational thinking, teaching is a social phenomenon, the network teaching has its own development law (Jiang & Zhang, 2006), from traditional teaching to modern teaching and network courses teaching, is a process of development of education, principles of teaching, law of teaching, teaching logic, teaching methods and the effect is different. It is different from traditional teaching and also associated with traditional teaching. No matter what the form of teaching is, all construct theoretical framework and practice mode from various aspects, such as training goals, curriculum setting, teaching content, teaching styles, teaching management and evaluation and so on, so is network courses teaching.

The last, from truth, goodness, and beauty level, from the height philosophy wisdom to review, network courses teaching has means of modern education technology, and also has the support of modern teaching theory, teachers teach effectively and students learn effectively, pursuit of multiple intelligence development, advocates to train innovation ability and practice ability, to promote full free of people development, this is a kind of education art.

To sum up, the entire contents of the network courses effective teaching mode includes three fundamental aspects at least: the first is the modern educational technology, the second is the modern education theory, and the third is education and teaching practice. Those three aspects compose macro-framework about the network courses effective teaching mode. If there is no involvement of courses and teaching theory, network courses teaching is only application of computer technology. Modern education theory out of the modern educational technology and network educational technology, which is equal to leaving the core achievements of the development of science and technology, will become empty sermonizing.

2. Components of Effective Teaching Mode of Network Courses Rapid development of the information industry and science and technology provides education, teaching and learning with new platforms and tools. However, if you want to improve the effectiveness of teaching by the new technology, you have to combine modern educational theories and modern educational technology, make it networking about application of modern educational

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theory. From Johann Amos Comenius’ “great teaching theory” to Herbart’s five paragraph teaching, from Markov Chan’s “development views” to Gagne’s “coupling-cognitive” learning theory, to David P．Ausubel's "learn and taught" theory, these teaching theories had played a huge role in past teaching activities, network information era still need to review about their meaning of these theories seriously, reference its reasonable ingredients by reflective criticism.

Before teaching entering the network, teachers are indoctrination in the process of teaching. Students are in a passive state, completely dominated by teachers in the classroom, ignoring the subject position of students. Materials is the basis of teaching, which is the main content of students' learning, teaching media are presentation tools that assist teachers in teaching. Traditional teaching with the school as the center, separated from school and society, enable students to separate from their life, "which makes school education separate from society life and become a divorced from social institutions, reducing school responsibilities towards the community and the schools' right to get social support, thus affecting the teaching quality and effect, can not develop talents the community need.( Xiang, 2013.) “

After entering the network, teaching has changes: Teachers are no longer the master of the classroom, teachers and students are equal in network teaching, teachers are the students ‘ mentors and facilitators. Students are subjects of processing about information and knowledge, who learn independently to a large extent. Materials are no longer the only source of information, students can find something to suit their own learning resources, from teaching materials, networks and so on, and access to a wealth of knowledge and information. Instructional media can also create more realistic situations. In network teaching platform, teaching is inseparable from the platform. Network teaching, not textbook-centric, not classroom-centered, not teacher-centered, had changed teaching mode with teacher-centered, which is conducive to students ‘ initiative to explore, discover and create, and the cultivation of creative talents.

Network course is an effective teaching, which is a new teaching mode that summarizes teacher-centered mode and student-centered mode and its theoretical benefits. The core of this new mode is that we must exert the guiding role of teachers, but also fully reflect students’ principal role. This new mode put teachers, students, teaching content, teaching media integrate, beyond the teacher-centered or student-centered teaching model. The construction of network courses effective teaching mode, which is not denying traditional teaching mode and modern teaching mode absolutely, but a “sublation” of traditional teaching and modern remote teaching mode, both overcome their limited and insufficient, and absorb their advantages and reasonable parts, so that make modern education theory integrate, including pedagogy, curriculum and teaching theory, and learning theory Together with modern education technology, and network education technology.

3. Construction and Practice of Network Courses Effective Teaching Online courses as an indispensable resource that carried out online teaching , it is a construction pattern which follows the affects of the effectiveness of online teaching directly (Hu, 2008).Modern educational technology, network technology, which must integrate the modern education theory, make them effective, it is of great value and significance to construct network courses effective teaching mode.

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3.1. Macro-Mode Construction of Network Courses Effective Teaching The construction of network courses effective teaching mode, the first thing to consider is the macro network education technology. Network education technology makes educational philosophy and theory advanced, modern and Avant-garde can be achieved, so as to construct the network courses effective teaching mode to be possible. According to the famous instruction design theorists Robert Mills Gagne and Kali’s “classic system instructional design mode” (He, Lin & Zhang, 2006) and domestic educational psychologist Shao Ruizhen’s instructional design patterns (Pi, 2000), as well as the author served as primary teacher of the Shaanxi Normal University network course “modern educational technology”, with many years of experience, we build the effective teaching mode of network courses.

Secondly, the construction of network courses effective teaching mode cannot be separated from modern teaching theory. “Instructional design theory has a very strong practicality, which can play a direct role in guiding teaching” (Liu, 2003). We want to design network teaching through using modern curriculum teaching theory, instruction design theory integrated teaching objectives, teaching content, teaching subjects, instructional strategies, and instructional media, teaching evaluation and so on, involving many education principles, drawing on instruction design theory, it is conducive to achieve modern educational theory networking and make network teaching more effective.

Network courses designers should do: first, instructional designers need to analyze learning needs, learner characteristics, and subject characteristics .The purpose of instruction design is to highlight the principal position of learners, exert learners’ enthusiasm and initiative, to guide learners to achieve success .Second, to identify teaching objectives. Through analyzing learning content, you should be determined to the knowledge points and skills in order to complete the teaching goals. Clarify teaching objectives in order to provide basis for teaching strategies and teaching evaluation in the future. Thirdly, identifying teaching strategies. Design of teaching strategies, which is to study some specific issues ,such as the teaching orders, the arrangements of teaching activities, selection of teaching organization form, the choice of teaching methods and so on .The design of Teaching strategies, that is design a teaching form to create the most optimal teaching situation to excite learners’ motivation maximize. IV, selection and application of instructional media .The use of teaching media is not the more the better, but according to the teaching goals, educational content, teaching objects, and teaching conditions to select and apply instructional media. Effective teaching media can help to improve the quality of teaching, achieve teaching objectives, which make teaching to be a double effect. V, teaching evaluations. Teaching evaluation refers to analysis of the instruction design of the back-end or terminal analysis. Effective teaching evaluation can judge student’s knowledge base before you start class, so as to set different goals for different learners; also can improve teaching plan, teaching methods for students learning in the course of the process, which can make the teaching process becomes to a controlled process, so as to make the teaching effects more closer the desired objective of teaching design ;also can summary the condition of students learning after course, find the student’s weaknesses in order to take corrective action. In short, effective evaluation can improve the quality of teaching and teaching effectiveness.

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Finally, the construction of effective teaching mode of network courses should also consider domestic teaching practice. Network educational technology and modern educational theories are imported from abroad from a certain extent , they must be combined with the educational reality of domestic, take the way of China, so that they can rooting, flowering, fruiting on the land of China, in order to promote the development of education practice.

Based on the above analysis, the authors construct the macro-mode of practice of network courses effective teaching (Figure 1).

Figure 1. Macro-mode of network courses effective teaching

No theory divorced from reality, nor from the theory of the actual. Unrealistic theory is empty; the theory divorced from reality is blind. Domestic education reality, there must be theoretical guidance, modern educational theories must guide the modern education practice, if the teaching practice of our country divorced from modern educational theory, divorced from modern educational technology and network technology, it is bound to lag behind the times.

3.2. The Construction of Network Courses’ Effective Teaching Practice Model In general, a complete teaching mode includes theoretical basis, teaching goal, operation program, implementation condition and teaching evaluation，these five factors are also a fundamental framework that constructs every teaching mode.Based on this framework, the author constructs the network courses’ effective teaching mode.

First of all, we consider the theoretical foundation. According to the modern education theory, curriculum and teaching theory, learning theory and effective teaching theory and other modern teaching theories, we found since Johann Friedrich Herbart's "four-step teaching method"(Yu, Hong, & Zhang, 2008) all of the teaching mode are “injection” modes. John Dewey’s “five-step mind method”(Yu et al., 2008) began to emphasize the main status of students, but ignored the

EITT 2013, Williamsburg, VA, USA, November, 2013 197 Proceedings of International Conference of Educational Innovation through Technology guiding role of teachers. Since the 1950’, with the rapid development of science and technology, the problem of “teaching” and “learning” once again caused the people’ exploration .

Therefore, after compared traditional teaching mode that gives priority to teach with modern teaching mode that gives priority to learning, we construct the network courses’ effective teaching mode in order to solving the unity of teaching and learning and the unity of educational science and educational technology. Secondly, we consider the teaching goal which realizes the highest benefit of education and teaching through effective teaching and effective learning.

Thirdly we consider operating procedures, namely network operating procedures that can research and solve teaching and learning and their relations. The fourth is implementation conditions, it requires teachers and students learn and master the modern teaching technology, network education technology， because they create new teaching content, teaching means, teaching environment, teaching time and space for teachers and students, and this also lays the foundation for the formation and operation of network courses effective teaching model.

Aiming at the problems appeared in the development of network education in our country, "pilot college network of college teaching quality has become the focus of the public and media questioned the problem (Su, 2001)", "There is no generally accepted successful innovation model of teaching and learning (Ding, 2005)”, based on the above analysis, the author combines the professor Li Yi’s paper that published in global education prospects “network courses system construction principle (Shan & Li, 2001)”with my teaching practice in the network course for many years, construct a microscopic, concrete network courses effective teaching practice model, as shown in the figure ,which is an integrated model that is double main intelligent dynamic multilateral interaction practice evaluation。

Figure 2. Effective teaching practice model integrated double master, intelligent, dynamic, multilateral interaction and comprehensive evaluation

The starting point of this model is the design and development of network courses，a mature discipline curriculum which is elaborately designed by teacher and design management and has completely discipline curriculum content ,teaching activities designed in advance and the shared resources ,communication tools and other rational design , in accordance with requirements of

198 EITT 2013, Williamsburg, VA, USA, November, 2013 The Exploration of Practice Model of Network Courses Effective Teaching the teaching target, is integrated into the network course platform, namely we must design smart dynamic network courses that has the superior function firstly。

Then, we need install the network courses on the web server to openly run. With the help of the speaker teachers and administrators, network courses implement the teaching function, and complete the teaching process at the same time; Finally, in the learning process or after the completion of the course, we need objectively to evaluate the network courses teaching as a whole, the evaluation is diversified and practical, and then it need to make the corresponding feedback, according to the feedback to judge the issue is network course design or operation problems in the process of network teaching in order to give reasonable dynamic changes. For network teaching, the process is a process of continuously circulation, eventually can make the effect of network course teaching optimized.

This operation of the mode can realize effective teaching that is double master, intelligent, dynamic, multilateral interaction and the integrated evaluation.

Double main teaching model overcomes the separation of "teaching" and "learning" in traditional network courses teaching, the goal is to achieve effective teaching. The operating procedure is to implement computer network model construction theory; it is based on the guide of the modern curriculum and teaching theory, effective teaching theory, constructivism theory, multiple intelligences, and reflective teaching. It mainly points using the teachers' dominant and the students' network teaching application, implements it in the trinity of "teaching - learning - tube" intelligent network course platform, provides quality learning resources and services for the students, and create conditions for autonomous learning for the students, such as curriculum development.

Intelligent is the intelligent features of the whole network courses background management. Background management mainly has students’ registration login management, students’ learning process management, namely students’ online learning time, learning frequency, learning knowledge points, learning success rate, learning process monitoring are all intelligent management. Teachers or administrators can callout course background data to check the state of student learning at any time from the short-range or long-range, students can also view the state of their own learning. It also has intelligent management on resources, assessment, learning evaluation, etc. Can construct the model of intelligent convenience to teachers, managers, and is also convenient for learners. So, constructing an intelligent model is convenient for teachers, managers, and the learners.

Dynamic mode refers to dynamic transplantation when design different courses, framework and module function are unchanged, but the content of the course has been changed to another course. For the same course, it means dynamically modifying and adding some functional modules, teaching content, learning materials. This dynamic of change can be made in the middle of the course or after the end of the course, whenever you are free or not. The dynamic model for network courses design is very effective.

Multilateral interaction refers to the interaction between teachers, students and managers. The interactions between teachers and students concretely include face-to-face interaction (the

EITT 2013, Williamsburg, VA, USA, November, 2013 199 Proceedings of International Conference of Educational Innovation through Technology seminar),indirect synchronous or asynchronous interaction (video conference, electronic mail, BBS, etc.)Interaction between tutors and students performs as follows: teachers’ guidance and timely feedback in the whole process of the students’ learning; Interaction between teachers and managers mainly refers to that in the teaching process when the teachers find the problems existing in the network course design or have a good idea, he timely communicates with manager in order to dynamically change network course modules.

Practice evaluation refers to a diverse evaluation as a guide, comprehensively evaluate students’ learning process and learning results combining theoretical study and practical works. Learning process evaluation contains the evaluation of the learners learning time, learning content, and learning effect. Learning effect evaluation contains situations of the students’ target completion, task submission and completion, network test and completion of practical works.

This effective teaching model integrated double master, intelligent, dynamic, multilateral interaction and comprehensive evaluation puts the unity of the learning and teaching as the core problem, uses the method that combine science and technology, theory and practice, puts modern network technology and education science together, promotes the effective of the network courses, and realizes the network courses effective teaching.

Because of the difference of the disciplines and teachers’ needs, the different difficulties of the technologies such as foreground design and the background development, so developing an excellent curriculum is not easy, the model that this study has built can help to solve the trouble problem, make the development of curriculum convenient, quick and normative.

3.3. The Run of the Network Courses Effective Teaching Practice Model The run of the Network courses effective teaching practice model, on the one hand points to the run within the model, refers to its operating procedures can be run; on the other hand it points to the run outside the model, which is run in real education practice. Both of the two types of run are equally important, first is the internal run which can checkout whether the internal inspection model sound reasonable or conform to the requirement of operation procedure, if internal mechanism has a problem, it can’t normally run. External operation is a problem of the unity of theory and practice, Theory without practice is empty, and the practice without theory is blind. So in network courses implementation, how practice produce theory, how theory guide the practice are questions worth thinking about.

The first is the internal operation of the network courses effective teaching model. In the network teaching, the computer network provides students with abundant learning resources, rapid information retrieval and query tools, a variety of communication tools, such as online simulation good cognitive learning environment and support the students independent or cooperation to acquire knowledge. However if there is no teachers’ default teaching making software which can edit teaching contents and learning resources, the model is difficult to run normally to get effective results; If learners don’t have right learning purposes and attitudes, lack of scientific learning method, this model can also be difficult to get effective results.

200 EITT 2013, Williamsburg, VA, USA, November, 2013 The Exploration of Practice Model of Network Courses Effective Teaching

In network teaching, the teacher can be absent, namely teachers and learners can be in a state of “quasi permanent separation”, “man - machine” or “man - machine -man” relationship will weaken the direct communication between teachers and students, so we are sure machine will never replace people after the comparison of “man - machine” or “man-machine-man”.

This means the network teaching doesn’t absolutely negate the traditional teaching, but dialectical self-negation. If the intersubjectivity of network courses effective teaching practice model, such as teaching theory, curriculum theory, learning theory, effective teaching theory, teaching scientific theory, don’t increase the “technical content” to realize effective teaching network, effective teaching won’t be achieved without network teaching technology. Network courses effective teaching model ask for the unity of science education theory and education science and technology. Only by implementing the unification of science and technology, can we make the normal operation of teaching model and achieve effective teaching results.

The second point is the external operation of the network courses effective teaching model. Constructing a teaching model, it will have its social service function. This research constructs a double master, intelligent, dynamic, multilateral interaction and the integrated evaluation network courses effective teaching practice model, from the surface, it is a network teaching system. Whether from the network courseware, network distance education, network quality course, or network courses effective teaching form, it all depends on network teaching media, such as the network platform, this reflects the teaching time, makes us refreshing. If teachers or students don’t understand the computer network technology, teaching will not be able to carry out.

All in all, the normal operation of the network courses effective teaching practice model is the proof that whether the teaching mode is reasonable, scientific, feasibility or not.

4. Conclusion The research on network teaching in this paper directly points to the present China’s network courses teaching practice, this is also the basic value orientation of the research. Constructing network courses effective teaching practice model is also from the teaching practice in China. As a main teacher of national network courses in shaanxi normal university, many years’ teaching experience let me deeply feel it is difficult to improve the effectiveness of the network course teaching without curriculum theory, teaching theory, learning theory and effective teaching theory and other modern teaching theory, the combination of the modern education technology and modern education science, educational technology needs education scientific theory.

The creation of the network courses effective teaching practice model also needs the support of theories. The network courses effective teaching practice model constructed in this paper is created in the guidance of modern curriculum and teaching theory, learning theory and effective teaching theory. This teaching model has not only theoretical basis, but also a clear goal and procedures of operation, it is also practice directed, it is constructed according to computer network technology and modern teaching theory, it can solve teaching and learning problems in current teaching practice of china.

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So this teaching model is established in theory, it is also of great significance in practice. The separation of teaching and learning, education science and educational technology, theory and practice aren’t solved, the education and teaching of china is unable to move forward. Network courses effective teaching practice model reveals that under the condition of network teaching, network teaching media provides the most powerful support and the best service for the main intelligent dynamic multilateral interaction.

References Ding, X.F. (2005). The assurance measures for the quality of online education around universities in our country .China Distance Education, (3), 54. Du, Y.Y. & Liu, B. (2013).Einstein and religion. Study of Natural Dialectics, (1), 90-95. He, K.K., Lin, J.F & Zhang, W.L.(2006). Instructional system design. Beijing: High Education Press. Hu. B. (2008).Network curriculum design based on constructivist learning theory. The Journal of Henan Radio & TV University, (7), 74-76. Jiang, X.Y.& Zhang, S.J. (2006).teacher’s role and its development in the network. Higher Agricultural Education, (9), 48-50. Li, B.D. (1991). Pedagogy theory. Beijing: People’s Education Press. Li, Z.F. (1992). Again on relativistic space time theory and its evaluation. Study of Natural Dialectics, (3), 61-64. Liu, Y.X. (2003). The formative research of instructional design theory. Open Education Research, (5), 13 -16. Pi, L.S. (2000).Instruction design- theories and technologies of psychological. Beijing: High Education Press. Shan, M.X. & Li ,Y. (2001).Online course system construction principles. Global Education Outlook. (11), 36-40. Su, X. (2001). The eternal theme. China Distance Education. Xiang, X.M. (2013). the logical relationship between life education and school education. Educational Research, (8). Yu, W.S., Hong, M. & Zhang, R.(2008) .Theories and models of effective teaching. FuZhou: Fujian Education Press, 15-16. Zhong, Q.Q. (2007).The value of effective teaching .Education Research, (6),31-35.

202 EITT 2013, Williamsburg, VA, USA, November, 2013 Rufer, R. & Adams, R. (2013).Deep learning through reusable learning objects in a MBA program. Proceedings of International Conference of Educational Innovation through Technology, 203-212.

Deep Learning through Reusable Learning Objects in a MBA Program

Rosalyn Rufer , Ruifang Hope Adams State University of New York Email: [email protected]; [email protected]

Abstract: The use of an interactive reusable learning object is important in on-line learning environments, especially for complex theoretical constructs. A reusable learning object can re-enforce student learning throughout their degree program and thus facilitate the learning process. A case study of the use of educational technology in an on-line MBA program demonstrates an effective way to apply educational technology to weave the learning throughout the student’s degree program and thus improve student learning outcomes. This paper will provide evidence of improvements in the student learning and the process used to develop the reusable learning object.

Keywords: deep Learning, reusable Learning object, MBA program

1. Introduction Idrosa, Mohameda,Esaa, Samsudina, and Dauda (2010) recognized that “a single learning object may be used in multiple contexts for multiple purposes” (p. 703).“Learning objects are self- contained learning components that are stored and accessed independently. A reusable learning object is any digital resource that can be reused to support web-based learning” (Valderrama, Ocana &Sheremetov, 2005, p. 274). According to Mavrommatis (2008), reusable learning objects are small learning components that can be combined and reused in different contexts and that these objects are “best” designed to facilitate knowledge rather than communicate knowledge. Readings and mini-lectures in an on-line learning environment communicate knowledge, in the case study presented here. However an interactive reusable learning object (RLO) was used to support online student learning in a MBA program. This model facilitated the student’s ability to critically assess a firm’s resources and identify those resources that could be leveraged to create a sustainable competitive advantage (Barney, 1991). The data presented here will demonstrate the effectiveness of using a RLO as a method of ‘weaving the learning” throughout the student’s degree program.

2. Literature Review Much has been written about learning styles and student learning outcomes. In a traditional classroom, the faculty member facilitates synchronous learning and collaboration. This becomes more difficult in a web-based learning platform. As indicated by Lee & Su (2006).

Internet users have much more diverse backgrounds than students. Therefore, web-based learning has to be dynamic in order to accommodate learners’ different backgrounds, competencies, and interests. To meet this requirement, learning object service must have the following dynamic properties: active, flexible, adaptive and customizable (p. 6-7).

Furthermore, differences in student learning styles are exasperated by the linear design of many

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 203 Proceedings of International Conference of Educational Innovation through Technology web-based systems. As a result, the differences in learning outcomes may be related to the student’s ability to adapt to the mode of the information presented, not just their ability to learn.

“Learning styles [have been] described by the cognitive, affective, and psychological behaviors of how students learn; approaches to learning looked at three ways to engage in learning: a surface approach (rote memorization), a deep approach (exploring and questioning), or a strategic approach (with tactics to earn the desired final grade); and intellectual development (with the highest level defined as that which follows the scientific method)” (Adams & Rufer, 2010, p. 2).Basedon this previous work by Rufer and Adams (2010), we understand that changes in pedagogy using technology that provides both deep learning and at the same time interactivity can engage students regardless of learning styles. “Boyle delineated three possible layers of explanation for learning: the physiological, cognitive and interactional layers. He argues that the interactional layer is the appropriate one for the learning designer and that ‘context’ is the key concept at this layer” (Boyle & Ravenscroft, 2012, p. 1226).Context here can be viewed as an activity system that “weaves together” the learning, resulting in “deep learning.”

“Deep learning applies substantive insights from the learning disciplines to exploit the affordances of the technology, in order to develop contexts that empower learners to achieve educational goals” (Boyle & Ravenscroft, 2012, p1225). According to Boyle and Ravenscroft (2012), the design [of interactive technologies] requires not just a construction of the overall learning context, but detailed concern with the tasks, the activities of learners, and the means of knowledge representation used (p.1230). In an on-line program, educators must be concerned about the design of the pedagogy as it relates to the diversity of the learner.

The pedagogy under evaluation in this paper is part of an MBA program developed for adult learners through a web instructional management system. This program was chosen because the learners are self-directed, come from diverse backgrounds and in many ways benefit from a flexible pedagogy because of time and space constraints. However, the lesson learned about improving learning outcomes through deep learning, has application for traditional students, as well as those taking on-line courses?

3. A Case Study A layering of tasks can help the learner gain a deeper understanding of the concepts (Kurubacak, 2007). This was found to be the case in the MBA Marketing Management course, where it was determined that readings (textbook and on-line mini-lectures) were not sufficient to teach students how to determine the buying behaviors of potential customers, a new concept taught in this course (Rufer & Adams, 2012). The next layer of learning that was implemented was to include narrated power point lectures and webinars to align with learners that were auditory as well as visual. In addition on-line discussions were incorporated to move from contextual learning to reflective learning, through collaboration.

Further enhancement to the pedagogy in the MBA Marketing Management course included the use of delivery through web 2.0 technology (Second Life, a virtual world environment). This further increased collaboration and at the same time addressed the learning style of kinesics learners (Rufer & Adams, 2012). The increase in learning activities and collaboration, between

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student to student, student to instructor, and student to content improved the learning outcomes for understanding how to assess potential customer buying behaviors, by increasing deep learning through the layering described here. However, there were other concepts that students struggled with; including those that had been previously taught in earlier courses in the MBA program. Thus while the layering of learning helped to reach diverse learners, it was not sufficient to facilitate the learning process.

One of learning goals of this MBA program is to teach students how to make strategic decisions that will enable the organization to sustain its competitive advantage. As part of the process students apply common strategic management tools such as a SWOT and competitive analysis. In addition, it has well been established that it is important to be able to leverage an organization’s processes and core competencies to sustain its competitive advantage (Ray, Barney, & Muhanna, 2004). Barney (1991) first looked at the firm’s resources and their value, rarity, ability to be imitated and the ability of the firm to operationalize these resources to sustain a competitive advantage known as VRIO model. Students are taught this model in their first course of the program. Later in the MBA Marketing Management course, students are asked to use this model to identify a viable strategic direction for their marketing plans. However it was found that only 72% of the students were able to apply this model to effectively identify the sustainable resources of the organization, as indicated in Table 1.

Table 1: Percent demonstrating understanding of VRIO model % demonstrating Class VRIO SAEC 77% MMS 72.4% SEL 77% average 75%

Furthermore, as students moved from the advance Marketing Management course to their capstone project (SAEC and SEL), only 77% were able to apply this critical management model, in spite of several layers of learning, as indicated in Table I. The capstone course for the MBA is divided up into two parts. The first part assesses the macro and micro environmental factors that affect the organization’s performance (called SAEC in Table 1). The second part is the development of a full strategic plan including the optimum strategy for leveraging the competitive advantages of the organization (called SEL in Table I).Since students in SAEC and SEL had previously completed the Marketing Management course, it was expected that 80 to90% of the students would have been able to demonstrate competency in this area. In all three courses, there are readings and mini-lectures on the model, as well as on-line discussions of the role of the model in assessing the resources to determine an organization’s strategy. Capstone students also present their application of the model as part of blended learning and reflection at a face to face residency with the professor and their classmates, where the professor highlighted the proper way to apply the model (Barney &Hesterly, 2006).However students fell short of meeting the expected learning outcome goal. It was believed that these layered activities would create a learning environment able to reach diverse learning styles. To improve student learning outcomes, a variety of educational technologies were

EITT 2013, Williamsburg, VA, USA, November, 2013 205 Proceedings of International Conference of Educational Innovation through Technology considered to facilitate the learning (as opposed to communicate the context of the field).

The previously applied layered activities should have been able to reach diverse learner, through visual (the readings), auditory, and kinesics activities at the residency. Collaboration and reflection through the on-line discussion was added to enhance the earlier layers of to provide a deep learning at the student level. These web-based learning activities appeared to be “dynamic in order to accommodate learners’ different backgrounds, competencies, and interests” (Lee & Su 2006, p. 6-7). Yet only 77% of the students grasped the concept by the end of their degree program. One reason may be attributed to the fact that this content knowledge was not used anywhere else in the program and may have been easily forgotten (Dernt&Motschnig-Pitrik,2005).Another reason may be reflective of the learner’s style of learning and how engaging the on-line learning was for the student.

It became our objective to incorporate an interactive learning activity that would “weave together” the learning throughout the student’s degree program. To accomplish this objective we developed a reusable learning objective(RLO) that could be incorporated in the first course of the program (called Scanning the Business Environment), a course taken at the midpoint of the degree program(the marketing management course), and the capstone course (SAEC and SEL). This RLO was also designed to be interactive, engaging students who learned through visual and kinesics learning activities and thus facilitating the learning of the students.

4. Methodology: The RLO Educational Technology Design Process To improve student learning in this MBA marketing management course, a team was formed to address the problem. Collaboration was an important step in developing a solution for this learning objective. One member from the team was an expert in the field of marketing and strategic management and the other an expert in instructional design. As such we began the process of developing the RLO by forming a “community of practice”. According to Berkani&Chikh (2010) “one person can share the best way to design a special kind of learning situation based on his own experience, which may enable the other members to be inspired from it in order to design other learning situations” (p. 4437). The marketing and strategic management expert identified the concept that student were not properly applying. In this case it was the application of Barney and Hesterly’s model of how to assess an organization’s resources for sustainability (Barney &Hesterly, 2006). Students wanted to identify which resources were rare, which were valuable, which were not easily imitated; rather than assessing each resource for providing the firm with a sustainable competitive advantage. We felt that it was important to develop the RLO to help students envision this complicated topic: the relationship between resources and sustainable competitive advantage. The individual proficient in instructional design felt the RLO needed to be designed as a “highly interactive learning objects … [to] allow for continuous, bi-directional interaction with all essential parameters” (Hanisch&Straβer,2003, p. 647). According to Hanisch&Straβer (2003), to create a “highly interactive learning objects, requires expertise in subject, programming, pedagogies, didactics, and design” (p. 649). The objective was to “design them (the RLO) within the framework of a well-planned curriculum, one that incorporates standards compliant classification schemes allowing for consistent labeling of RLOs and efficient retrieval of the RLOs from databases “(Leon, 2002, p. 2). When creating the RLO, the instructional designer considered how to turn “good” instruction

206 EITT 2013, Williamsburg, VA, USA, November, 2013 Deep Learning through Reusable Learning Objects in a MBA Program that might be found in a traditional classroom into an on-line learning object. The first step in the design of this RLO was to map out a decision tree that students should follow to assess the sustainable competitive advantage of an organization’s resources (see Figure 1). The course instructor identified ten common resources that could provide an organization with a sustainable competitive advantage. If the resource was not valuable the decision tree led the student to a node that stated the resource was a disadvantage, if it was valuable but not rare, it was identified as providing the firm competitive parity. If it was both valuable and rare but could be imitated, it was identified as providing a temporary advantage. If the resource was valuable, rare, not easily imitated, and the organization could leverage the resource through its operations, then the resource was identified as a sustainable competitive advantage.

Figure 1.RLO decision tree

The instructional designer identified several technology resources that could support this type of decision making process.” Intelligent Reusable Learning Components Object Oriented (IRLCOO) are described, a special type of Reusable Learning Objects (RLO) producing learning content rich in multimedia, interactivity and feedback” (Valderrama, Ocana,&Sheremetov, 2005,p. 274). One type of technology resources that can provide for interactivity and feedback is that of an interactive PowerPoint presentation. According to Littlejohn, Falconer, and McGill (2008): A set of PowerPoint slides [can] provide the information content at the heart of learning activities representing all five forms [in which learning resources may be use]: 1. Narrative – if downloaded by the learner from a website or database; 2. Communicative – if used as the basis for a discussion; 3. Interactive – if searched or scanned for bibliographic entries; 4. Adaptive – if edited with PowerPoint software; and 5. Productive – if the ideas from the slides are used as the basis for the reconceptualization using concept mapping software (p. 760).

A prototype RLO developed using PowerPoint in this case study was embedded in the Web based course management system, where learners could download it and use it any time. Guided by Littlejohn’s principle, The RLO design processes designed here contained all five forms:

During the design phase, the narrative activity instruction direction was governed by an overall navigation flow. Each of the resources probed an evaluation of the concept and solicitude a decision, to reach either a conclusion or evaluate a further decision steps for the concept. In addition, as

EITT 2013, Williamsburg, VA, USA, November, 2013 207 Proceedings of International Conference of Educational Innovation through Technology part of the narrative for the students, we asked students to print out the last page of the power point to fill in as they moved through the decision making process. It was also suggested that students replace any resources that were not identified by the designers with those that were not a core competency of the organization (strength from the SWOT analysis).

4.1 Communicative The RLO was designed with a unified communication message. Most of interfaces designed with global instruction, and all the navigation buttons named consistently, such as “Home”, “Go to the Next Question”, or “Go back to Previous Question”, etc. According to Boyleand Ravenscroft (2012), “design requires not just a construction of the overall learning context, but detailed concern with the tasks, the activities of learners, and the means of knowledge representation used” (p. 1230). The instructional designer paid close attention to this as she created the interactive PowerPoint presentation.

4.2 Interactive The RLO was developed with interactive mechanism, and student can jump to any resource sections, use as many times as they needed, test different scenario, or adapt the tool to their relevant organization whenever they wanted (see the “adaptive” form in this design process). The instructional designer created these interface in order to create interactive experiential knowledge for the learner. “Experiential Knowledge is the knowledge that is often codified and easily expressed, captured, stored and reused” (Berkani&Chikh, 2010, p. 4440).We expect that an increase in student learning comes from providing learning approaches that are congruent with a variety of cognitive learning styles and an increase interaction and reflection. We propose that design patterns do not only increase the efficiency and flexibility of the design effort for novices, but also increase their understanding of the design process and the domain in which they design. Furthermore, we considered the cognitive effect of offering knowledge in the shape of design patters, and its implications for learning efficiency (Kolfschoten, Lukosch,Verbraeck, Valentin, & de Vreede, 2010, p. 653).According to Kolfschoten, et al.,(2010) “a learning task is less complex when part of it is already understood” (p. 654).In this case study the learner demonstrated greater ability in evaluating the value, rarity, inimitability, and the ability of the organization to leverage each resource in a systematic, interactive, and repetitive decision making process.

4.3 Adaptive In this RLO we used a design pattern to allow learners to evaluate each resource separately.The RLO was designed as non-linear to facilitate adaptively as a learner is free choose any resource to evaluate. As indicated earlier, student prior to beginning this process created a SWOTand competitive analysis for their organization under evaluation. This provided the students with a list of core competencies of their organization under evaluation.It was our expectation that by doing this, the learner would then develop a sense about the importance of each resource for the organization’s sustainable competitive advantage.Thus this RLO was not only interactive it was also adaptive based on the SWOT and competitive assessment.

4.4 Productive As a result, student can get very informative visual expression to help him/her to make final decision as relate to the marketing strategies. (See Figure 2).If student reach this level of

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learning they will have transcended from a surface approach to learning to that of intellectual development.

Figure 2.Example final decision strategy

Table 2: Percentage demonstrating mastery of concept before and after RLO Class Control (no RLO tool) % after using tool SAEC 17/22 77% 40/43 93.0% MMS 21/29 72.4 62/70 88.6% SEL 7/9 77% 23/24 95.8% average 75% 92.50%

Table 3: Chi-squared testing for relationship course Value df Asymp. Sig. (2-sided) SAEC Pearson Chi-Square 3.345b 1 .067 N of Valid Cases 65 MMS Pearson Chi-Square 3.951c 1 .047 N of Valid Cases 99 SEL Pearson Chi-Square 2.582d 1 .108 N of Valid Cases 33 Total Pearson Chi-Square 9.306a 1 .002 N of Valid Cases 197 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.22. b. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 2.71. c. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 4.69. d. 2 cells (50.0%) have expected count less than 5. The minimum expected count is .82.

5. Findings As noted earlier, the concept of developing strategy around the resources of the firm is a learning objective in the marketing management course, the capstone project, and the first course in the MBA program. The RLO developed here was first applied in the marketing management course

EITT 2013, Williamsburg, VA, USA, November, 2013 209 Proceedings of International Conference of Educational Innovation through Technology and also applied in the capstone two- course sequence. Just as in the case study in the marketing management course, students in the capstone sequence showed mastery of this learning objective once they applied the RLO (see Table 2).The chi-squared test supported the expectation that there was a relationship between student learning outcomes and whether or not they used the interactive RLO (see Table 3).

The percent of students correctly evaluating their organization’s resources to develop a strategy increase from 75% to 93% overall during the fall 2012 term. The control (or those that did not use the RLO) was below the targeted 80 to 90% demonstrating competencies in this area. However with the RLO all three courses met or exceeded our targeted learning outcomes.

6. Future Research While “it is clear that developers are enthusiastically creating reusable learning objects (RLOs) in ever-increasing numbers, and are sharing them by placing them into learning object repositories (LORs)” (Bond, Ingram, & Ryan, 2008, p. 603), a PowerPoint may not be the only useful tool for this RLO. One technology tool considered by the instructional designer is the use of Generative Learning Object (GLO Maker). “GLO Maker is of interest for two reasons: it employs an explicitly generative approach to the design and realization of virtual contexts for learning and the design is placed within an explicitly layered approach” (Boyle & Ravenscroft, 2012, p. 1231). It was decided that the RLO should be designed in two phases the first with the PowerPoint technology as a prototype, since students were already familiar with this technology. The second phase would be to replicate the RLO using GL-Maker.

It is suggested that the Generative Learning Object (GLO Maker) authoring tool can be used to design some learning objects specifically tailored for a subject learning (Greaves, Roller, & Bradley, 2010), and can easily adapted for creating rich, interactive learning resources for different subject area or contents needs (Khademi , Haghshenas , &Kabir, 2011). The GLO-Maker populates publication in HTML CD-ROM package, SCORM package for import to any LMS, which requires no specialized programming skills to create media rich RLOs.Figure 3 shows the GLO-Maker authoring tool in Design.

Figure 3, GLO maker tool planning interface

GLO-Maker’s most unique feature is reusable pedagogical designs, not content, nor concrete learning objects. One of the benefits is to develop many specific learning objects based on similar pedagogical pattern

210 EITT 2013, Williamsburg, VA, USA, November, 2013 Deep Learning through Reusable Learning Objects in a MBA Program

7. Implications A RLO appears to be a successful tool for an on-line learning environment. It is an effective way to create collaborative learning communities, bringing together teams with disciplinary and design expertise. The reuse of an RLO provides for both an efficient and effective way of engaging students. As each application of the RLO improves student learning outcomes, the RLO itself can be modified based on successive results. For example in this case study the RLO was adapted by each student to include the core competencies found in their organization being evaluated. In addition, the technology design itself will be modified to evaluate different technologies. The first technology applied was that of a PowerPoint presentation. This was selected because of the familiarity of students with PowerPoint.Students were able to quickly work within this technology with little effort. Other technologies that will be evaluated in the future are GLO maker and Flash. Both can provide an interactive learning experience for the student. The RLO needs to be both interactive and layered, so that the student is able to reflect on the outcomes. The RLO studied here provided the students with the repetitive application of the theory for a “deep learning” experience. It is our expectations that GLO maker will have similar results as the Power Point presentation.

The use of an interactive RLO is important in on-line learning environments, especially for complex theoretical constructs. In the example here, neither textbook readings, discussion questions, nor mini-lectures were able to reach twenty-five percent of the students. However, ninety-five percent of the students were able to better understand how to assess an organizations sustainable resource through the RLO. This case study demonstrates an effective way to apply educational technology to weave the learning throughout the student’s degree program and thus improve student learning outcomes.

References Barney, J. B. (1991). Firm resources and sustained competitive advantage.Journal of Management, 17(1), 99-121. Berkani, L., &Chikh, A. (2010).A process for knowledge reuse in communities of practice of e-learning.Procedia- Social and Behavioral Sciences, 2(2), 4436-4443. Bond, S. T., Ingram C., & Ryan S. (2008).Reuse, repurposing and learning design – Lessons from the DART project. Computers & Education, 50(2), 601-612. Dernt, M., &Motschnig-Pitrik,R. (2005).The role of structure, patterns, and people in blended learning.The Internet and Higher Education, 8(2), 111-130. Greaves, L., Roller, S,.&Bradley, C. (2010).Repurposing with a purpose: a story with a happy ending.Journal of Interactive Media in Education, May, 1-16. Hanisch, F.,&Straβer, W. (2003).Adaptability and interoperability in the field of highly interactive web-based courseware.Computers & Graphics, 27(4), 647-655. Idrosa, S. N. S., Mohameda, A. R., Esaa, N., Samsudina, M. A., &Dauda, K. A. M.(2010). Enhancing self-directed learning skills through e-SOLMS for Malaysian learners.Procedia Social and Behavioral Sciences, 2(2), 2010, 698-706. Katz, H., Worsham, S., Coleman, S., Murawski, M.,& Robbins, C. (2004).Reusable learning object model design and implementation: lessons learned. In J. Nall& R. Robson (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2004 (pp. 2483-2490). Chesapeake, VA: AACE. Retrieved from http://www.editlib.

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org/p/11257 Kolfschoten, G., Lukosch, S.,Verbraeck A., Valentin E., &DeVreede, G. (2010). Cognitive learning efficiency through the use of design patterns in teaching.Computers & Education, 54(3), 652- 660. Kurubacak, G. ( 2007). Building knowledge networks through project-based online learning: A study of developing critical thinking skills via reusable learning objects.Computers in Human Behavior, 23(6), 2668-2695. Lee, G., & Su, S. Y. W.(2006). Learning objectmodels and an e-learning service infrastructure. International Journal of Distance Education Technologies, 4(1), 1-16. Littlejohn, A., Falconer I., &Mcgill L. (2008).Characterizing effective elearning resources. Computers & Education, 50(3), 757-771. Leon, J. (2002). Reusable Learning Objects: Hazards, Hi-Performance, and a New Convergence. In M. Driscoll & T. Reeves (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2002 (pp. 1788-1791). Chesapeake, VA: AACE.Retrieved from http://www.editlib.org/p/9349 Mavrommatis, G. (2008). Learning objects and objectives towards automatic learning construction. European Journal of Operational Research, 187(3), 1449-1458. Parnell, J. A., &Carraher, S (2001).The role of effective resource utilization on strategy’s impact on performance.International Journal of Commerce & Management, 11(3/4),1-34. Ray, G., Barney, J. B., &Muhanna, W. A. (2004).Capabilities, business processes, and competitive advantage: Choosing the dependent variable in empirical tests of the resource based view. Strategic Management Journal, 25, 23-37. Rufer, R. & Adams, R. H. (2012).Student centered marketing education through open learning resources and Web2.0 technology.American Marketing Association Winter Educators Conference, February, Conference Proceedings. Valderrama, R. P., Ocana P. B.,&Sheremetov L. B. (2005). Development of intelligent reusable learning objects for web-based education systems. Expert Systems with Applications, 28(2), 273-283. Yaghmaie, M., &Bahreininejad, A. (2011).A context-aware adaptive learning system using agents. Expert Systems with Applications, 38(4), 3280-3286.

212 EITT 2013, Williamsburg, VA, USA, November, 2013 Tang, H., Li, Q., Yan, Y., & Dong, Y. (2013). Students’ experiences of initial designers in a project-based learning case. Proceedings of International Conference of Educational Innovation through Technology, 213-218.

Students’ Experiences of Initial Designers in a Project-based Learning Case

Hengtao Tang, Qiyuan Li, Yu Yan, Yaozu Dong The Pennsylvania State University-University Park Email: {hzt111, qxl127, yzy122, yxd117}@psu.edu

Abstract: This paper showcases a design blueprint highlighting students’ experiencesas initial designers in a project-based learning case. Traditional curriculum design is suspect to generate “inert knowledge” that cannot be applied in multiple practices. Researchers thus propose flexible adaptive instructional designs in order to strengthen students’ understanding and construct “usable knowledge” that can be transferred in various settings. The blueprint focuses on how K-12 students’ perceptions of healthy diet will be improved through the experience of initial designers. An emerging structure of what it is like for a student to complete those learning cycles will be constructed from the future data and analysis.

Keywords: flexibly adaptive instructional design, initial designers, project-based learning, STAR LEGACY, challenge

1. Introduction A number of schools and business training intends for curriculum guidelines thatprovides everything from the “exact content” to the “exact sequence of instruction” to the “exact teaching techniques” (Schwartz, Lin, Brophy, &Bransford, 1999a, pp. 189). The results of instruction and/ or training seem successful at first glance but turn out to be a failure in transferring knowledge to multiple practical contexts due to lack of understanding. Whitehead (1929) defines the “inert knowledge” problem that denotes the condition of failing to transfer and apply knowledge.

Many studies indicate that traditional instructional designstend togeneratethe problem of inert knowledge (Bereiter&Scardamalia, 1985; Bransford, Franks, Vye, &Sherwood, 1989; Gick&Holyoak, 1983; Perfetto, Bransford, & Franks, 1983). Schwartz et al. (1999a, 199b) proposed to integrate flexible adaptive instructional design and view design as a collaborative and emerging process involving “initial designers”, teachers, community members, and even students themselves. Through STAR LEGACY cycles, flexible adaptive instructional design help teachers and learners see where they are in a complex sequence of learning and make the learning cycle explicit. STAR LEGACY cycles may have several systemic circles and each cycle consists seven procedures including 1) look ahead, 2)the initial challenge, 3) generate ideas, 4) multiple perspectives, 5) research and revise, 6) test your mettle, and 7) go public(Schwartz et al., 1999a & 199b). Upon the completion of STAR LEGACY cycles, students are expected to gain more involvement and construct “usable knowledge” in a progressive and reflective way.

This design blueprintintends to examine what students experience with project-based learning look like with the case of promoting healthy diet within K-12 students. According to World Health Organization (WHO) (2012), 65% of the world’s population lives in countries where overweight and obesity kills more people than underweight and more than 40 million children under the age

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 213 Proceedings of International Conference of Educational Innovation through Technology of five were overweight in 2011. The situation implies it is significant to understand that these are preventable and be equipped with knowledge about how to avoid. From an individual perspective, healthy diet and living habits are fundamental to reduce food related disease. Additionally, supportive environments and communities are important in shaping people’s choices of healthy food and increasing their interests to take routine exercise (accessible, available and affordable). In order to help students realize where they are and better facilitate the learning process, three learning cycles will be designed and students will be motivated by challenges for each circle and then construct their own knowledge base and skills to apply in multiple contexts.

2. Design Blueprint The blueprintis expected to involve 20 students in a weekly K-8 health class as participants. Starting with the academic goals, the design blueprint will take two weeks for students to go through all the challenges. According to Bloom’s (1956)taxonomy,three types of goals are set up for the blueprint: cognitive goals, affective goals and psychomotor goals. Cognitive goals concerns with students’ understanding about the concepts of healthy diet/life. Affective goals deals with students’ attitude to health and healthy diet, usually described as “appreciate”. Psychomotor goals regard to students’ operational behaviors, usually described as “be able to” (Bloom, 1956). These goals are explicit for teachers to define and specific for studentsto follow. More important, these goals are nested from the simple superficial understanding to higher levels of application.

Academic Goals for Students • Cognitive Goals o Generate a basic concept of healthy diets and distinguish healthy diets from junk food. o Understand what harm keeping an unhealthy diet will bring about.

• Affective Goals o Be willing to pursue healthy life with appropriate diet. o Be willing to encourage people who are overweight rather than discriminate them.

• Psychomotor Goals o Create a healthy diet plan based on students’ own conditions. o Promote the significance ofhealth and healthy diet and help students keep off junk food and the bad habits.

The three challenges used offer students different entry point into the issue of Healthy Diet. For example, the first initial challenge emphasizes the factors that could harm human health, the second challenge consider how can we get away from malnutrition situation by eating healthy food. The third challenge is a project, in which student will design a healthy diet plan for themselves.

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Cycle 1: Learning Activities Circle Goals • Generate a basic concept of healthy diets and distinguish healthy diets from junk food. Look ahead • Understand what harm keeping an unhealthy diet will bring about. and reflect Reflections back • Students will see some pictures of food package. The students will understand the nutritional facts on the package after finish this learning unit.

• Student will read a news report: “Last year, New York Mayor Michael Bloomberg proposed a ban on large sugary drinks in an effort to curb Challenges obey.” • After reading they are going to think about “Are there any other food and drinks we need to control for a good health?”

• After viewing the challenge, students will be asked to write their own ideas about the challenge and submit their original idea to CMS Generate ideas discussion board. • They will later discuss and share with others about how they think on food we should control.

• A Discovery Documentary about food production. Multiple • A magazine article about why we should eat less fast food. perspectives • A video lecture on how different food culture over world

• Teacher will give students lectures on how to food ingredients. • Reading articles from WHO website • Students will look at legacies by other students Research and • Students will go to supermarket and take pictures of nutrition factor of revise different kinds of food. • They will make a comparison of different food nutrition and write a blog about the report (group work).

• Meet with teachers and get feedback Test your • Make a diagram of different kinds of unhealthy food, with at least 15 mettle food in it, and write a report on the food they choose, submit to CMS

• Students will do a group work on building a wiki, with topic “Health Diet”. Goal Public • Students will share their wiki link on CMS discussion board, and give presentation, get peer review from other students

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Before starting with the cycle 2, students will be provided the goals and objectives for this cycle so that they could locate where they are situated in the progress. The challenge of cycle 2 is “how can we optimize the diet for those children who are suffering malnutrition?” Around this challenge, students are expected to explore the sever question of malnutrition among children in current society and be able to come up with solutions on optimization of a specific diet plan for a child under the condition of malnutrition. They will be assigned a specific example of malnutrition and divided into several groups to generate their ideas and teacher will provide multiple perspectives from newspaper, journal article, and TED lecture. In addition, student-parent mutual interview will also be included as one specific perspective. For the procedure of research and revise, students will watch the documentary film “A Place at the Table” and TED lectures to help them gain a better insight. Furthermore, an in-class lecture by professionals will ensure students can get to know the fact and receive professional answers for their questions in an interactive way. After research and revise, students will continue with the legacy framework and finish formative assessment through a reaction paper with questions “What nutrient elements are required for human health? ” and “What should people do if they cannot sustain a sufficient amount of certain elements in their body?”. Teachers will make a response to students with feedbacks on how to improve their knowledge of nutrition. Finally, the optimized diet plan will be published by each group and peer- review will be integrated.

For Cycle 3, the challenge is to design a healthy diet plan for them. In order to design an efficient plan, students should know about their own diet habit in addition to the knowledge of nutrition elements. They will complete this project by themselves and take record of their diet habit to generate ideas. Additional readings and videos on healthy diet will be available for them to get multiple perspectives. Teachers also deliver in-class lectures to clarify more detailed information on how to design the plan. In order to test whether they obtain enough knowledge of nutrition, students will be required to take the test of “Food Guide Pyramid” and they are supposed to match the food with eating frequency and nutrient elements. Teachers will send feedbacks and students can further adjust their plan. Finally, students will post their diet plan to the discussion board and interact with peers and the teacher.

3. Discussion and Future Research Innovations in the instructional designs such as problem-based, case-based, and project-based learning has been implemented to solve the inert knowledge problems (Schwartz et al, 1999b). This design blueprint integrates the flexibly adaptive instructional designs and provides challenges for students to explore through cycles of learning with the identity of “initial designers”. Learners and contexts, two core elements within learning, are diversified in practical settings. As Schwartz et al (1999 a) state, flexibly adaptive instructional designs, featuring with STAR LEGACY framework, are the principles that can be “optimally adapted to fit diverse communities of learners, plus help people involve with learning to know enough about the processes of learning to make sound instructional decisions and adaptions of instructional materials” (pp. 212). As initial designers, students will be navigated through challenges and locate themselves within the learning cycles. As mentioned above, they are expected to understand the process and the context and also generate “usable knowledge” rather than “inert knowledge”to transfer and apply in multiple settings.

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All the assumptions of this design blueprint are all based on the literature and need empirical data to examine its reliability. In the implementation of the design blueprint, upon completion of those STAR LEGACY cycles, students will also complete reflection of the whole learning process and researchers will also conduct interview with each participant. Then researchers will complete qualitative analysis of those data from students’ reflection paper and interview notes. Based on those analysis and data, new patterns concerning students’ experience of initial designer in this project-based learning cycle will hopefully be emerged.

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References Bereiter, C., & Scardamalia, M. (1985). Cognitive coping strategies and the problem of “inert” knowledge. In S. F. Chipman, J.W. Segal, & R. Glaser (Eds.), Thinking and Learning Skills: Current Research and Open Questions, 2,65-80. Bloom, B. S. (1956). Taxonomy of educational objectives, handbook I: the cognitive domain. New York: David McKay Co Inc. Bransford, J.D., Franks, J.J., Vye, N.J., & Sherwood, R.D. (1989). New approaches to instruction: because wisdom can’t be told. In S. Vosniadou& A. Ortony (Eds.), Similarity and Analogical Reasoning. New York: Cambridge University Press. Gick, M. L. & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1-38. Perfetto, G.A., Bransford, J.D. & Franks, J.J. (1983).Constraints on access in a problem solving context. Memory and Cognition, 11, 24-31. Schwartz, D.L., Brophy, S., Lin, X. & Bransford, J. D. (1999b). Software for managing complex learning: Examples from an educational psychology course. Educational Technology, Research and Development, 47(2), 39-58. Schwartz, D.L., Lin, X.,Brophy, S. & Bransford, J. D. (1999a). Towards the development of flexibly adaptive instructional designs.instructional-design theories and models, Volume II, 183-213. Whitehead, A.N. (1929). The aims of education. New York: Macmillan WHO (2012). World Health Organizations. Retrieved from: http://www.who.int/mediacentre/ factsheets/fs311/en/. Retrieved on April 15th, 2013.

218 EITT 2013, Williamsburg, VA, USA, November, 2013 Techatassanasoontorn, C., Asino, T., Briskin, J., Stager, S., & Yan, Y. (2013). Using mobile technology for active learning in the big classroom. Proceedings of International Conference of Educational Innovation through Technology,219-222.

Using Mobile Technology for Active Learning in the Big Classroom

Chakorn Techatassanasoontorn, Tutaleni Asino Pennsylvania State University Email: [email protected]; [email protected]

Jessica Briskin Affiliates Risk Management Services, Inc. Email: [email protected]

Sarah J. Stager, Yu Yan Pennsylvania State University Email: [email protected], [email protected]

Abstract: Personal response systems (PRS) have led to more active interactions in classrooms by allowing students to participate in lessons at the same time. Such technologies change classroom interactions and improve student’s learning outcomes. As students owned mobile devices- a mobile phone, a smart phone, a tablet, and a laptop computer – decrease in cost, there are now more affordable ways to integrate the technology. In this study, we review possible ways of connecting students using their own mobile devices and recommend solutions that help ease the deployment of such technology in classrooms. How teachers and students interact and how pedagogy can change will also be examined.

Keywords: mobile learning, active learning, learning outcomes, participation, clickers

1. Introduction Active learning, especially in large classrooms has traditionally occurred at random, involving mostly students whose names the teacher can recall. This meant that most of the students who did not get called on to answer questions were not always actively engaged in the lesson and end up being passive participants in their learning. Numerous studies (Bonwell & Eison, 1991; Ladousse, 1987; McKeachie, 1999; Van Ments, 1994) found that active learning enhances student-centered learning, maximize participation, is highly motivational, and engage students to a deeper understanding of learning activities. Authors such as McCarthy & Anderson (2000) further suggest that using Active Learning in the classroom significantly enhances undergraduate students’ performance compared to traditional teaching methods. Today’s learners have the benefit of various technologies such as clickers which can be used to address the obstacle of how to make particularly large classrooms conducive to active learning.

Clicker technologies allow teachers to pose questions and receive responses from all of the students in the classroom, instantly. Such technologies enable the teacher to assess the students’ understanding by having them answer questions in real time. Liu, Liang, Wang, and Chan (2003) found that clickers increased in-class interactions as well as fostered two-way communication. Despite its benefits however, a study by Keogh & Wang (2010) found that students had some

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 219 Proceedings of International Conference of Educational Innovation through Technology concerns with the cost of the clicker device compared to the number of courses that employ that device. Furthermore, this same study found that teachers do not change their pedagogy in order to effectively utilize clicker devices.

Clickers or similar technologies, if implemented effectively, allow teachers to connect with students in a lecturing teaching style and may lead to greater student engagement (Terrion & Aceti, 2012). Most of the students are now equip with a personal mobile device, which can be used as a PRS device. Moreover, there are many free services available online that can transform personal mobile device into a PRS device. Therefore, teachers who are interested in adopting this technology need only to examine the classroom for a reliable wireless connection in order to begin investigating whether the PRS system will make a difference in their student’s learning outcomes.

Our study was designed to compare classrooms using three different interactions: 1) students- lecturing, PRS with anonymous voting, and PRS with identifiable voting. The participating teacher used the same materials and same questions with all classes. Our investigation was guided by the following research questions:

RQ1: Does active learning using a personal response system improve student’s pre-test and post-test score? RQ2: Does active learning using a personal response system improve student’s grade for this course?

2. Method To address student attention and the participations created by audience response systems in three different medium size classes, the instructor used free WIFI version of audience response systems- Socrative and Infuse learning to deliver three different styles of the same questions to all three classes. All of the questions used in all classes are the same. However, the first treatment group’s responses were anonymous and the second treatment group’s responses were identifiable. The control group was asked and responded using the traditional lecturing style.

During the 14 weeks of lecturing sessions, there were 9 sessions with the use of personal response system in both treatment groups. From a population of 65 students from each class, there were 55 students that participated in the study. At the end of the course, there were however 50 students participants who could be analyzed for this study. The device, expected grade, and GPA were collected at the pre-test. At the end of the learning session, the student’s perceived benefits were collected from the two treatment groups as well as expected grade. The total course score will be collected from the teacher after the final grading is finished.

The teacher agreed for an interview with the investigator after the course grades were finalized. The individual interviews were conducted through online communication tools- Skye and Google Hangout.

The available students’ personal devices were collected at the pre-test on the first day of the classroom. There were approximately 90% of the students who brought their own personal devices

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(i.e. smartphone, tablet, or laptop computer) to the classroom everyday and were willing to use their device as a PRS device. Unfortunately, the WIFI network in the classroom was not always reliable enough to run the PRS questions. However, the teaching was separated in two continuous sessions- lecturing and laboratory. After the first one hour of lecture, the teacher moved the class to the computer laboratory. Then, the lecture and hands-on practice continued with the students. The teacher used PRS to ask the students questions during the lab time. There was a maximum of 4 questions for each meeting. The students were free to use their personal devices as well as the computers in the lab to participate in PRS questions. Therefore, all of the students’ treatment groups were able to participate in the teacher’s questions. In the regular lecturing session, the students have to raise their hands in order to participate in the teacher’s questions.

The first half of the teaching, the teacher used Socrative for both treatment groups. Due to difficulties to connect to the website and unreliable response collection of the service, the team decided to switch to Infuse learning during the last 7 weeks of teaching. Infuse learning provides rich features that the teacher liked as well as the connectivity is more stable compared with the Socrative program. All of the questions and answers during the course were collected as well as the real examination scores were collected. All of the sensitive data from each student are treated according to strict Penn State IRB requirements.

3. Preliminary Results At the submission of this paper to the proceeding, the class was just concluding and the grades had not yet been submitted. Moreover, with 50 participants, the classroom was smaller in size than originally envisioned at the conception of the study. The teacher asked 2-4 questions in each session with the use of PRS. Initial analysis was done using participants’ pre-test and post-test scores. The difference between the post-test and pre-test was used to determine the improvement in the knowledge. There was not a significant effect of active learning using PRS devices on student’s improvement in pre-test and post-test score at the p<.05 level for the three conditions [F(2,144) = 1.045, p = .354].

Further analysis will be completed after the students’ final grade has been submitted. Discussion and conclusion will be included after the final analysis.

References Bonwell, C. C., & Eison, J. A. (1991). Active learning: creating excitement in the classroom. ASHE- ERIC Higher Education Report No. 1. Washington, DC.: George Washington University. Keogh, P., & Wang ,Z. (2010). Clickers in instruction: one campus, multiple perspectives. Library Hi Tech, 28(1), 8-21. Ladousse, G. P. (1987). Role play. Oxford: Oxford University Press. Liu, T., Liang, J., Wang, H., & Chan, T. (2003).The features and potential of interactive response system. Proceedings International Conference on Computers in Education (pp. 315-322). Hong Kong. McCarthy, J. P., & Anderson, L. (2000). Active learning technique versus traditional teaching styles: two experiments from history and political science. Innovative Higher Education, 24(4), 279-294. McKeachie, W. J. (1999).Teaching tips: strategies, research, and theory for college and university

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teachers. Boston: Houghton Mifflin. Terrion J. L., & Aceti V. (2012). Perceptions of the effects of clicker technology on student learning and engagement: a study of freshmen Chemistry students. Research in Learning Technology, 20, 1- 11. Van Ments, M. (1994). The effective use of role play. London: Kogan Page.

222 EITT 2013, Williamsburg, VA, USA, November, 2013 Wang, S. & Chen, H. (2013). Flipped classroom: An innovative teaching model in the digital age. Proceedings of International Conference of Educational Innovation through Technology, 223-228.

Flipped Classroom: An Innovative Teaching Model in the Digital Age

Shuyan Wang, Huiruo Chen The University of Southern Mississippi Email: [email protected], [email protected]

Abstract: Thru the development of educational technologies, the growth of social networking, the ease of multimedia creation, the use of cloud computing, and the sharing of open resources, teachers are able to adopt some teaching strategies and methods which could not be implemented in the past. Therefore, flipped classrooms came into being, perfectly representing constructivist learning theories. This article will discuss what a flipped classroom is, why it is widely accepted, and what challenges it faces. This article will also investigate some studies and practices of flipped classroom as well as provide some recommendations.

Keywords: flipped classroom, individual learning, reverse instruction, student-centered class,

1. Introduction The term flipped classroom has been very popular in recent years. It has attracted more and more attention and is being widely used as a new teaching model in Northern America. Although the term flipped classroom is new, the concept of is not. In the early 20th century, John Dewey pointed out that education should be student-centered instead of teacher-centered, where students construct their own understanding and knowledge through experience and reflection over those experiences. Constructivism emphasizes on deeper understanding of knowledge and improving students’ critical thinking and problem solving, not just content memorization. Constructivism pays more attention to student self-assessment, communication, collaboration, and support among peers during their learning process. Therefore, teachers often ask their students to preview the learning content before class and review the key points after class. However, not all students can preview or review the content as required.

Thru the development of educational technologies, the growth of social networking, the ease of multimedia creation, the use of cloud computing, and the sharing of open resources, teachers are able to adopt some teaching strategies and methods which could not be implemented in the past. Therefore, flipped classrooms came into being, perfectly representing constructivist learning theories. This article will discuss what a flipped classroom is, why it is widely accepted, and what challenges it faces. This article will also investigate some studies and practices of flipped classroom as well as provide some recommendations.

2. Definition of Flipped Classrooms Flipped classrooms are also known as backwards classrooms, reverse instruction, flipping the classroom, and reverse teaching. Flipped classrooms were also defined in different terms. Knewton (n.d.), the world’s leading adaptive learning company, defined flipped classrooms as a new teaching method and classroom model. According to Knewton, flipped classroom inverts the traditional

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teaching model and method. It brings more classroom interactions between teachers and students. Teachers created teaching video for students to view before class and moved “homework” to the classroom.

Robert Talbert (2013) defined flipped classrooms as a platform;“like a platform in the computing world, the inverted classroom specifies the ‘hardware’ and ‘software’ architecture for the course — the systems used to house and deliver content, the grading protocols and rubrics, and so on — that allow the ‘application software’ in that platform to run (¶4).” He said that adopting this approach does not mean a teacher is going to have to switch to a new way of teaching; instead, this platform gives the teacher the freedom to explore many different ways of teaching, possibly multiple methods within the same semester or even the same class meeting. It is an approach to the instructional design of a course that reorganizes where, and how, information transfer and internalization takes place.

According to Educause Learning Initiative (2012), the flipped classroom is a pedagogical model in which the typical lecture and homework element of a course are reversed. Short video lectures are viewed by students at home before the class session, while in-class time is devoted to exercises, projects, or discussion.

To make it simple, flipped classroom is a reversed teaching model that delivers instruction at home through interactive, teacher-created videos and moves “homework” to the classroom. Typically, teacher takes videos or recorded screen casts of his/her lecture which will become the homework for the students. Students watch those lectures online at home or at school before class, and then come to class with their own questions or problems about the lecture. This means students learn and understand content outside of the class at their own pace and practice and implement the content in the class.

3. Fast Adoption of Flipped Classrooms There are several reasons flipped classroom have spread so fast. First of all, it is easy for students to catch up with missed work because the lecture video is online and can be accessed anytime, anywhere. Secondly, it is easy for students to learn the content at their own pace because they can always stop and rewind if they do not understanding the content. Thirdly, it reduces students’ anxiety about homework because they complete their homework in the classroom with the help of the teacher. Fourthly, they have more time and opportunity to interact with peers and teacher both online and in the classroom. Fifthly, students have more individualized learning because the lectures are watched at home so that they enjoy the differentiated and customized learning experiences. Since students learn the content outside of the classroom, teachers can spend more time with students for individual questions. In addition, students have the opportunity to ask questions and work through problems with the guidance of their teachers and the support of their peers in a collaborative learning environment.

The most important reason is flipped classroom motivated students learning interests and helped increase students testing scores. According to Knewton (n.d.), after using flipped classroom model, the rate of freshmen who failed English dropped form +50% to 19%; the rate of freshmen who failed math dropped from 44% to 13%. Classroom Window (2012) conducted a survey on

224 EITT 2013, Williamsburg, VA, USA, November, 2013 Flipped Classroom: AnInnovative Teaching Model in the Digital Age teachers’ view of flipped classrooms. As of June 21, 2012, 453 flipped instructors completed the online survey. Survey results indicate that 88% of educators agreed that flipping their classroom improved their job satisfaction, 67% reported improved student test scores, 80% noticed improved student attitude, and 99% would use it again next year. Among the teachers who completed the survey, 46% of them were science teachers, 32% math teachers, 12% English teachers, and 95% of participants were secondary school teachers.

Finally, the development of technology and cloud computing makes it easy for teachers to create lecture videos and interact with students outside of the classroom. Although studies indicated that flipped classroom worked great in science and math classes, this model can be used in almost every class. Teachers are interested in flipped classroom because a well-designed flipped classroom is a true student-centered classroom where the teacher is not the “sage on the stage”, but the “guide on the side” and all students are engaged in their individual learning. A flipped classroom is a student- centered, skill-based, and technology embedded classroom which represents constructive learning theories.

4. Studies and Practices of Flipped Classrooms There are quite a few successful practices of flipped classroom in K-12 settings. AaronSams taught Chemistry and AP Chemistry with the flipped classroom model at Woodland Park High School in Woodland Park, Colorado. He found that his students come to class with time to do more experiments, explore the content, and interact with each other. According to Sams (n.d.), his students do not just show up to learn new things instead they apply what they learned at home through the video and ask questions about the assignments. Therefore, his students are more engaged in the classroom activities. As a result, there is a great increase on students’ grades. There are fewer Bs, Cs, and Ds than before. More and more students get As.

The Oak Grove High School (Hattiesburg, MS) math teacher, ShaunaHedgopeth, stated that 80% of her students hated math before she flipped her class. After flipping the class, students may not love math but at least they do not hate it any more. Students are willing to learn math, ask her questions through emails, and discuss math problems with other students, which was not the case before flipping the class (Hedgopeth, n.d.).Greg Green, the principle of Clintondale High School, flipped his classrooms for a year and found out that the failure rate at their th9 grade center reduced by 33% in English, 31% in Math, 22% in Science, and 19% in Social Studies – plus the discipline rate dropped by 66% (Green, n.d.).

Shelley Wright teaches English Language Arts, sciences, and technology in Moose Jaw, Saskatchewan in Canada. She had flipped her classroom and had received great results among her students. Her classroom is best described as a student-centered, tech embedded project based learning/inquiry learning environment. According to Shelly (2012), her student developed the skills they needed although it was not quick, efficient or easy at the start. “But it is necessary for their development as creative, critical problem solvers who will live, and work, in our complex world (Wright, 2012).”

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Although she had a large class and only a couple of iPads, a few computers, and cell phones, Shelly flipped her class and everyone learned. Shelly noticed that her students did not need her to locate or create videos for them after student got familiar with the new way of learning. Accord- ing to Shelly (2012), the flip faded away and was gone for good. There was no need for her to assign video homework or create portable lectures. Her students learned how to learn so that they were able to find their own resources. Shelly thought this was a much more important skill than following her directions or using the resources she told them to use. According to Shelly, the flip disappeared from her classroom as this shift occurred. Her classroom had become “a place where students discovered and shared their own resources, while engaging in projects with each other (Wright, ¶11, 2012).”

5. Challenges of Flipped Classrooms “Sometimes when we’re changing, success can look like failure (Shelly, ¶16, 2013).” Al- though the flipped classroom is highly recommended by many teachers and educators all around the world, the flipped classrooms have garnered criticism from some scholars who believe that flipping is simply a high-tech version of an antiquated instructional method: the lecture (Ash, 2013).Some teachers worry that flipped classroom gives students more fixable time to learn online. It is good for some aspects; however, using flipped classroom model to form class means that students have to be supervised themselves and teachers’ guidance role become weaker than traditional classrooms. Teachers cannot ensure that every student has watched the videos before class, so they cannot promise their students’ progress.

Mr. Musallam, an adjunct professor at the University of San Francisco’s College of Education, began flipping his classroom in 2006, but after noticing little difference in student learning despite the extra in-class time for labs and hands-on activities, he shifted his perspective. He said that delaying the direct instruction increased students’ curiosity. Also, he felt that student could not form any more ideas on their own. Therefore, he suggested that teachers should be realistic about what a flipped classroom really is(Ash, 2012).

In The fuss over flipped classroom, Grafton (2012) listed pros and cons of flipped classrooms. Some of the cons include students spent more screen time after adopting a flipped model. Golbe and Mail recently conducted a study and found that 9.7% of teens in Ontario spend seven or more hours per day staring at a screen (cited in Grafton, 2012). If a student takes multiple flipped classes, she or he needs more hours for watching videos every night. In addition, not all students have convenient access to mobile devices and the Internet so that flipped classrooms can cause further digital division.

6. Future of the Flipped Classrooms The obvious result of flipped classrooms is the changes in students’ grades. The fact is that students’ grades from the above samples have increased after their teachers flipped their classrooms. After bringing flipped classroom, teachers have more time to help studentsindividually, andit also help build a stronger teacher-student relationship. As Bergman (2012) stated, thevideos freed him up to walk around and interact with the students. As a student said, “It’s like I have three

226 EITT 2013, Williamsburg, VA, USA, November, 2013 Flipped Classroom: AnInnovative Teaching Model in the Digital Age teachers in one classroom.”(MiQuanWright,cited in Bergman, 2012). Flipped classroom promotes students’ interests in learning and produce the ability for students to master contents. It also offers an opportunity for teachers to share information with other teachers.

Shelly (2012) was right when she said that we live in a world where information content is ubiquitous. With an Internet connection, students can search any information or knowledge they need. Therefore, memorizing the content is not as important as the skills to be able to navigate and make sense of such a world.

As described in diffusion of innovation (COI) theory (Rogers, 1962), flipped classroom model will also go through the following stages:1) knowledge – teachers are aware of the flipped classroom model and don’t know a lot about it; 2) persuasion – teachers are interested in the model and seek more information to form a favorable or unfavorable attitude toward the flipped classroom model, 3) decision – teachers consider to adopt or reject it based on their own interests, 4) implementation – teachers try the model in their curricular and see if it is appropriate for their classes, and 5) confirmation – teachers evaluate the results of flipped classroom model and make the decision to apply it in a larger area. Every new technology went through these five stages and was either adopted widely and became part of our teaching or disappeared eventually. Not all innovations will be disseminated.

7. Conclusion and Recommendations Flipped classroom brings a new teaching method to schools. It helps increase students’ understanding and promoteslearning enthusiasm. From flipped classroom model, students learned how to learn (Wright, 2012) so that they become active, independent, and life-long learners. However, to adopt this model, teachers have to realize that flipped classroom is not a synonym for online videos or online courses; instead, the interaction and the meaningful learning activities that occur during face-to-face class time is the most important (Bergmann, at el, 2012). To achieve the best result, teachers have to be well-prepared for the class, especially the in-class activities, which should be closely related to the videos students viewed before class. Flipped classroom model required more working time from teachers; therefore, it is very important for teachers to have good time management skills. Literature review and data analysis described successful stories of adopting flipped classroom model in K-12 among science and math teachers. More researches need to be done in other K-12 disciplines and higher education settings.

References Ash, K. (August 29, 2012). Educators Evaluate ‘Flipped Classrooms’, in Education Week. Retrieved from: http://www.edweek.org/ew/articles/2012/08/29/02el-flipped.h32.html?print=1 Bergmann, J., Overmyer, J., &Wilie, B. (2012). The flipped class: What it is and what it is not,in The Flipped Class: Myth Vs. Reality. Retrieved from:http://www.thedailyriff.com/articles/ the-flipped-class-conversation-689.php Classroom Window (June 21, 2012). Improve student learning and teacher satisfaction in one flip of the classroom. Retrieved from: http://edudemic.com/wp-content/uploads/2012/06/ Flipped-Infographic-800.gif

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Educause Learning Initiative, (February, 2012). 7 things you should know about flipped classroom. Retrieved from: http://net.educause.edu/ir/library/pdf/eli7081.pdf Grafton, D. (2012). The fuss over flipped classroom. Retrieved from: http://visual.ly/fuss-over- flipped-classrooms Green, G. (n.d.). Flipped classrooms get results at Clinton High School, in TechSmith. Retrieved from: http://www.techsmith.com/customer-stories-clintondale.html Hedgepeth, H. (n.d.). Capturing students’ attention with technology, inTechSmith. Retrieved from: http://www.techsmith.com/flipped-classroom-shauna-hedgepeth.html Knewton (n.d.), Flipped Classroom:The Flipped Classroom Infographic. Retrieved from: http:// www.knewton.com/flipped-classroom/ Rogers, E. M. (1962). Diffusion of innovations.The Free Press: A Division of Simon & Schuster, Inc. Sams, R. (n.d.). Put students at the center, in TechSmith. Retrieved from: http://www.techsmith. com/flipped-classroom-aaron-sams.html Talbert, R. (March 8, 2013). The inverted classroom as platform. Retrieved from: http://chronicle. com/blognetwork/castingoutnines/2013/03/08/the-inverted-classroom-as-platform/ Wright, S. (Oct. 19, 2012). The flip: End of a love affair. Retrieved from: http://shelleywright.wordpress.com/2012/10/19/the-flip-end-of-a-love-affair/ Wright, S. (April 22, 2013). Beta: the courage to fail & Change. Retrieved from: http://shelleywright.wordpress.com/2013/04/22/beta-the-courage-to-fail-change/

228 EITT 2013, Williamsburg, VA, USA, November, 2013 Wang, Y., Petrina, S., Feng, F., & Zhao, J. (2013). Designing immersive virtual languae learning environments. Proceedings of International Conference of Educational Innovation through Technology, 229-238.

Designing Immersive Virtual Language Learning Environments

Yi Fei Wang , Stephen Petrina , Franc Feng, Jing Zhao The University of British Columbia, Canada Email: [email protected]; [email protected]; [email protected]; [email protected]

Abstract: This study aimed to document a detailed instructional design phases of an immersive language learning environment in 3D virtual worlds. Data for understanding affordances of a 3D virtual world for designing immersive language learning was collected through group discussions, observations, survey questionnaires and the video-stimulated post interaction interviews. The results indicated that the instructional design of meaningful learning artifacts in a 3D virtual world might achieve the goal of immersive language learning by providing language learners an immersive, embodied, co-present and simulated hypothetical situation in a graphically rich and dynamic environment.

Keywords: virtual world, immersion, embodiment, co-present, distributed

1. Introduction 3D virtual worlds distinguish themselves from other types of computer applications by replicating a hypothetical real-life simulation in a graphically rich and dynamic environment (Dalgarno & Lee, 2010a; McLellan, 2004; Mennecke, Hassall, & Triplett, 2008; Mikropoulos & Strouboulis, 2004). Numerous studies explored the beneficial aspects of 3D virtual worlds for language teaching and learning such as rich learner engagement, representations, interaction, embodied actions and identity constructions (Bers, 2001; Brey, 1999; Dalgarno & Lee, 2010b). This study was built upon these previous research projects and explored the immersion and presence of 3D virtual worlds for designing immersive virtual language learning environments. Such immersion and presence of 3D virtual worlds may provide foreign language learners with opportunities to go beyond context boundaries. They can learn a target language without physically stepping out of their home countries.

2. Methodology Language teaching and learning in virtual worlds calls for a design framework that prioritizes a nonlinear progression, which may enable language learners to “steer their way through their zone of proximal development” within a language learning environment rather than transferring knowledge from teachers to students in a linear way (Angeli, 2008, p. 271). Consistent with the embodied, situated and distributed theoretical design framework, this study revised Middleton’s cyclic model of design-based research and followed the iterative process to “deal with complexity through “progressive refinement” and multiple iterations (Collins, Joseph, & Bielaczyc, 2004, p. 18; Middleton, Gorard, Taylor, & Ritland, 2008) (Figure 1). These multiple iterations made it possible for a design to function beyond its initial conditions of development. What separates design-based research from earlier research methodologies is the iterative research process between

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the laboratory and the classroom, between the nomothetic approach and the idiographic approach, between the cross-sectional design / the longitudinal design and the microgenetic analyses, and between qualitative methods and quantitative methods.

Figure 1. Revised Middleton’s cyclic model of design-based research

3. Phase one: Grounded models The study explored how a 3D virtual world platform might be shaped as an immersive language learning environment. Two specific questions were formulated and explored: How should we design immersive language teaching and learning activities in virtual worlds to engage language learners? Do language learners learning in the specific designed virtual environment feel real?

4. Phase two: Development of artifact We had two concerns in choosing the virtual world platforms: the complete control over the 3D virtual world and the location where the virtual world would be hosted. Hence, we began this study from an extensive research journey by examining the four major open source virtual world platforms – OpenSimulator, RealXtend, OpenCobalt and OpenWonderland.

5. Phase three: Feasibility study The feasibility study was conducted through a thorough literature review of the four open source virtual world platforms and a testing of each system by researchers. In terms of server host, we found that OpenSimulator, RealXtend and Open Wonderland platforms shared the same function, being hosted locally, except Open Cobalt, which used a P2P service.

All four platforms can have inworld voices imbedded. In terms of connection with the course management system, OpenSimulator achieves this goal through Sloodle, which blends the multi-user virtual environments of OpenSimulator and Moodle into a single 3D virtual learning environment. In terms of transferability, OpenSimulator has 300 out of 330 key functions in Second Life fully implemented. Direct skills, avatars and all related assets can be transferred from Second Life to OpenSimulator. Templates created for Second Life also work in OpenSimulator. In terms of NPC, OpenSimulator supports Non Player Characters (NPC) functionality through NPC “bots”, which can populate the landscape and make the virtual world realistic and interactive. As a result, the comparison of OpenSimulator, RealXtend, OpenCobalt and OpenWonderland helped us decide OpenSimulator would be the best fit for our special needs.

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6. Phase four: Low fidelity prototyping The preliminary HWL Virtual World was not designed from scratch. After surveying a number of virtual world design tools such as Holodeck and researching possible artifacts for inclusion within our world, we built the HWL Virtual World based on merging original files from Linda Kellie’s design using Diva’s Distribution 0.7.2 version of OpenSimulator.

7. Phase five: Field study The field study at phase five aimed to evaluate the further modification of the HWL Virtual World. Suggestions of the more robust design became the focus of the field study.

7.1. Research Design Nineteen pre-service teachers (ages between 20 and 35 & K-9 grade level), selected from an undergraduate teacher education program, participated in the preliminary evaluation of the HWL Virtual World. They were invited to install standalone Diva preconfigured 0.7.2 version of OpenSimulator (16 macs and 3 pcs) and Linda Kellie’s design on their own computers. Choices of Linda Kellie’s design were based on the participants’ preference. Nineteen participants were divided into five groups (four groups with 4 pre-service teachers and one group with 3 pre-service teachers). All participants were in the same lab and communicate face-to-face instead of using the inworld voice. We used participant observation and group discussion techniques with open questions to generate stories of participants’ experiences.

7.2. Research Findings Throughout the analysis of the data, an excellent fit between some of the language learning objectives and all of the following Linda Kellie’s designs was found 1.http://www.lindakellie.com/oar.htm(Total sim) 2http://www.lindakellie.com/oar6.htm(City) 3.http://www.lindakellie.com/oar14.htm(Western town) 4.http://www.lindakellie.com/oar15.htm(Freebie Mall Sim 2.0)

Two concerns were raised by the participants in this study. These two concerns guided the more robust design of the HWL Virtual World.

7.2.1. Unclear learning elements in the HWL Virtual World. The participants in this study indicated that learners might feel lost in the HWL Virtual World since it was difficult for them to figure out where the learning elements were. One of pre-service teachers commented: I’m confused with this virtual land, because aren’t the students using the technology to learn technology or are they using the technology to play? I can’t figure out learning elements in this virtual land. Are they using this virtual space to learn programming and skills on the computer, then that’s great; otherwise, if it’s just for play, it’s different.

7.2.2. Similar as the real world classroom. The second concern was that all of the HWL Virtual World exemplified the classrooms in the real world. The participants could imagine how virtual worlds could be used to facilitate teaching and learning. But it was difficult for them to envision how the virtual world classroom could be designed different from the real world classrooms.

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The thing that excites me about this possibility is not necessarily for every day, regular kids that come into the classroom. The thing that excites me about being able to have a virtual classroom, which is essentially what this is, taking online courses and giving people an actual place where they can go and interact with their course and with their course material, and it doesn’t excite me necessarily for the regular kids, but it excites me for the kinds that don’t have the opportunities, for whatever reason, to make it into a regular school, the kids that live way up north where their schools are one-room schoolhouses, the kids that have such severe anxiety that going out into the actual world stresses them out so much that they can’t do it. This is a steppingstone that they could come to school and to a classroom without having to actually go to a classroom.

8. Phase Six: High Fidelity Prototyping We designed a mock module for a Grammar and Proofreading course. This module aimed to test language competency and prepare learners for a writing course. The module was about using verbs in sentences. It had several learning objectives: distinguish among linking verbs, action verbs and participles; differentiate between transitive and intransitive verbs; construct sentences using present tense, past tense and future tense; form sentences using active and passive voices. All learning content such as videos, activities and assessments, were uploaded onto MOODLE, a learning management system.

The video tutorials were designed based on similar scenarios in HWL Virtual World - the real estate company, the clothing store, the shoe store, the supermarket, the hotel and the restaurant using Xtranormal.

We further conducted a more robust design of the HWL Virtual World. First of all, we removed all un-necessary worlds but kept only four of them: Total Sim, City, Western Town and Freebie Mall Sim. We redesigned these four regions as orientation region, customization region and two role-playing regions (Figure 2).

Figure 2. Map view of the HWL virtual world.

Secondly, we built chatbot and time machine in the HWL Virtual World to facilitate learning. The purpose of chatbot was to provide learners a clear learning tour – a learning tour guide in the HWL Virtual World. Time machine aimed to allow learners to notice the change of time, facilitating learners to convert sentences using past tense, present tense and future tense.

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Thirdly, we built four scenarios on HWL 1 role-playing region: a real estate company, a clothing store, a shoe store and a supermarket; two scenarios on HWL 3 role-playing region: a hotel and a restaurant. The orientation region was designed similar as the classrooms and campus in the real life for the sake of reducing instructors’ and learners’ anxiety of using the technology. Learners and instructors met on this region to know each other and get information of in world learning activities.

We also designed a brochure for instructors and learners, guiding them through the learning process. The brochure explained the details of using the module in MOODLE and all four regions in the HWL Virtual World. The brochure was uploaded onto the HWL Virtual World as a notecard shown to everyone when learners logged in the HWL Virtual World.

9. Phase Seven: Field study The field study at phase seven aimed to evaluate the more robust design of the HWL Virtual World. Suggestions of the effectiveness of the more robust design of the HWL Virtual World became the focus of the field study.

9.1. Research Design The HWL Virtual World was hosted on a local server in the language school where we conducted the experiment. Eight participants were divided into four groups (each groups with 2 language learners).

We encouraged the participants to explore the use of chatbot and time machine in the HWL Virtual World. They were required to conduct conversations on Region 1 and 3 of the HWL Virtual World. We used participant reconstructive interviews and participant observations to generate stories of their experiences.

9.2. Research Findings Chatbot, time machine and video tutorials created a supportive context woven throughout learners’ conducting inworld conversations. One of the major affordances that learners mentioned was that these inworld digital learning artifacts built a supportive online learning environment. John and Kalie’s conversation revealed that they had the highest rating of learning support from chatbot. For them, chatbot as a learning support did foster their learning. John and Kalie in a clothing store KALIE: May I help you? JOHN: Yes. I would like to buy a T-shirt. KALIE: What color do you like? JOHN: Green. KALIE: Oh, Mu… Here’s the green one. Do you know… Mu… where can we get help with our sentences? seeking help

JOHN: Video tutorials, Chatbot and Time machine. assistance KALIE: Where is the chatbot? confirmation JOHN: At the front door. (Kellie’s avatar and John’s avatar went to the front door together.)

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KALIE: Hello, can you help me? Chatbot: Hi there! KALIE: I would like to buy a T-shirt. Chatbot: What color do you like? KALIE: Pink. Chatbot: Sure. Please right click the pink T-shirt on the wall and then you can select ‘buy’ button on the bar chart. an answer that Kellie is looking for KALIE: Thank you! Chatbot: No problem! It’s ok… (Kellie’s avatar and John’s avatar went inside the clothing store, standing in front of the clothing wall.) KALIE: What color do you like? JOHN: Green. KALIE: Sure. Please right click the pink T-shirt on the wall and then you can select ‘buy’ button on the bar chart. supported by chatbot JOHN: Got it! Thank you!

Kalie appeared to be unsure how to respond to John’s choice of green T-shirt. She switched her turn to the chatbot, hoping that it might provide her a hint. The chatbot showed her one way to respond to John. Kalie learned the expression from the chatbot and applied it when she and John went inside of the clothing store. In fact, there were many other expressions that Kalie could use to respond to John. For example, Kalie could have said “Here you are’ or “Would you like to try it? In this scenario, the chatbot functioned as instructional scaffolding, providing Kalie and John some language hint so that they could continue their conversation. Both of Kalie and John relied on the perceived information to finish their inworld conversation. This scenario might represent a successful design case of using a chatbot to provide instructional scaffolding.

Similarly, time machine provided instructional scaffolding and support through relating to a particular learning environment.

10. Phase eight: Definitive test The definitive test at phase eight aimed at the further measurement of participants’ immersion in the HWL Virtual World. The in-depth investigation focused on whether learners felt the virtual world was operatively real enough to enable them to transfer their learned language skills in the HWL Virtual World into real life settings.

10.1. Research design A total of 80 EFL learners from one of language schools in Beijing China were selected randomly to participate in the experiment. All participants were randomly assigned one of the experimental conditions. The experiment sought to find significant differences among four groups. The first group of participants was told that they would practice learning activities in the HWL Virtual World. A second group was told that they would chat with chatbot in the HWL Virtual World. A third group of participants was told that they would use the time machine in the HWL Virtual World. The fourth group of participants was told that they would use both chatbot and time machine in the HWL Virtual World.

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Two questionnaires were used in this experiment: the Igroup consortium’s Igroup Presence Questionnaire (IPQ) and Witmer and Singer’s Immersive Tendencies Questionnaire (ITQ). Witmer and Singer’s ITQ questionnaire was used to measure EFL learners’ immersive tendencies in HWL Virtual World.

10.2. Research Findings It appeared from the data that there was no statistical difference between the first three groups on all Immersive Tendencies subscales. There were statistical differences between Group One and Group Four, between Group Two and Group Four as well as between Group Three and Group Four on Immersive Tendencies Total and Immersive Tendencies Focus.

Presence Total – To summarize, since Group Four had a higher score on Immersive Tendencies Total and Immersive Tendencies Focus, we can only conclude that the chatbot and the time machine increased learners’ presence total compared with virtual environment group. Learners who experienced the chatbot and those who experienced the time machine felt the same to obtain a sense of presence within a virtual environment (Table 1).

Table 1. Presence Total - post hoc tests

The mean difference is significant at the 0.05 level

Table 2. Spatial Presence - post hoc tests

The mean difference is significant at the 0.05 level.

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Spatial Presence - To summarize, since Group Four had a higher score on Immersive Tendencies Total and Immersive Tendencies Focus, we can only conclude at this study that the chatbot and the time machine increased learners’ spatial presence compared with virtual environment group. Learners who experienced the chatbot and those who experienced the time machine felt the same sense of being physically present in the virtual environment (Table 2).

Presence Involvement – To summarize, since Group Four had a higher score on Immersive Tendencies Total and Immersive Tendencies Focus, we can only conclude at this study that the time machine increased learners’ presence involvement compared with the virtual environment group. There were no differences in presence involvement in the virtual learning environment between learners who experienced just the virtual environment and those who experienced only the chatbot. Learners who experienced the chatbot and those who experienced the time machine expressed similar attention devoted to the virtual environment and the involvement experienced (Table 3).

Table 3. Presence Involvement - post hoc tests

The mean difference is significant at the 0.05 level.

Table 4. Experienced Realism - post hoc test

The mean difference is significant at the 0.05 level.

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Experienced Realism – To summarize, since Group Four had a higher score on Immersive Tendencies Total and Immersive Tendencies Focus, we can only conclude at this study that the chatbot and the time machine increased learners’ experienced realism compared with virtual environment group. There were no differences in experienced realism in the virtual learning environment between learners who experienced the chatbot and those who experienced the time machine (Table 4).

General Presence – To summarize, since Group Four had a higher score on Immersive Tendencies Total and Immersive Tendencies Focus, we can only conclude at this study that the chatbot and the time machine increased learners’ general presence compared with virtual environment group. There were no differences in experienced realism in the virtual learning environment between learners who experienced chatbot and those who experienced the time machine (Table 5).

Table 5. General Presence - post hoc test

The mean difference is significant at the 0.05 level.

11. Conclusions This study was comprised of three phases of the intervention design and four phases of studies, offering distinct theoretical perspectives and data analytical techniques to describe and measure the iterative process of the design of the HWL Virtual World.

The result yielded from this study prompted us a critical philosophical understanding of the learning theories in designing 3D virtual worlds for immersive language learning. By applying learning theories as embodied, situated and distributed, this study generate important findings for the instructional design processes of the HWL Virtual World. In particular, it pointed to the importance of how theories can guide the design of meaningful in world learning artifacts. Given the example of chatbot and time machine for teaching and learning verbs and tenses in the HWL Virtual World, a further investigation into the level design, locales, stages and missions, would be extremely helpful. As well, further experimental studies on the effects of combined learning artifacts should be conducted. This study provided an excellent test of models for design-based research and in the process we were challenged to be nuanced and add low and high fidelity stages to Middleton’s helpful model. Future studies will hopefully test and validate our revision.

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Consistent with design-based research, we view this study as iteration and are excited about prospects of redesigning and testing learning artifacts in virtual worlds.

References Angeli, C. (2008). Distributed cognition: A framework for understanding the role of computers in classroom teaching and learning. Journal of Research on Technology in Education, 40(3), 271-279. Barab, S. (2006). Design-based research: A methodological toolkit for the learning scientist. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences. Cambridge, MA: Cambridge University Press. Bers, M. U. (2001). Identity construction environments: Developing personal and moral values through the design of a virtual city. The Journal of The Learning Sciences, 10(4), 365-415. Brey, P. (1999). The ethics of representation and action in virtual reality. Ethics and Information Technology, 1(1), 5-14. Collins, A., Joseph, D., & Bielaczyc, K. (2004). Design research: Theoretical and methodological issues. Journal of the Learning Sciences, 13(1), 15-42. Dalgarno, B., & Lee, M. (2010a). What are the learning affordances of 3_D virtual environments? British Journal of Educational Technology, 41(1), 10-32. Dalgarno, B., & Lee, M. (2010b). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10-32. Gitelman, L., & Pingree, G. B. (2003). New Media, 1740-1915: MIT Press. Holec, H. (1981). Autonomy and foreign language learning. Oxford: Pergamon. McLellan, H. (2004). Virtual realities. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (2nd ed., pp. 461-497). Mahwah, NJ: Lawrence Erlbaum. Mennecke, B., Hassall, L. M., & Triplett, J. (2008). The mean business of Second Life: teaching entrepreneurship, technology and e-commerce in immersive environments. Journal of Online Learning and Teaching, 4(3), 339-348. Middleton, J., Gorard, S., Taylor, C., & Ritland, B. (2008). The “compleat” design experiment: From soup to nuts. In A. E. Kelly, R. A. Lesh & J. Y. Baek (Eds.), Handbook of Design Research Methods in Education: Innovations in Science, Technology, Engineering, and Mathematics Learning and Teaching. New York: Routledge. Mikropoulos, T. A., & Strouboulis, V. (2004). Factors that influence presence in educational virtual environments. CyberPsychology & Behavior, 7(5), 582-591.

238 EITT 2013, Williamsburg, VA, USA, November, 2013 Yan, Y., Li, Q., Tang, H., & Dong, Y. (2013). Using teaching for understanding framework in high school psychological health classes. Proceedings of International Conference of Educational Innovation through Technology, 239-243.

Using Teaching for Understanding Framework in High School Psychological Health Classes

Yu Yan, Qiyuan Li, Hengtao Tang, Yaozu Dong Pennsylvania State University Email: { yzy122, qxl127, qxl127, yxd117}@psu.edu

Abstract: Psychological health courses are required in Chinese high schools. However, a great amount of students only learn the terms in psychology health without truly understanding these terms. Teaching for understanding is an educational pedagogy which is emphasizing student’s understanding of knowledge by conducting series of performance around the topics. With the help of technologies, it is easy to represent multiple learning materials and develop various learning activities which will help students’ understanding of the knowledge. In this study, we re-designed a high school psychological class, by using the framework of teaching for understanding integrated with information technology. We generated a topic “understanding psychological disorder”, and organized nested learning activities that help students to be fully engaged in understanding how to recognize and prevent themselves from psychological disorders. The pilot study shows that students performed better on real-situation problem solving questions, compared to traditional lectured classes.

Keywords: teaching for understanding, psychological health, curriculum design, high school, project-based learning

1. Introduction and related work Middle school psychological health courses have been officially initiated in China since 1999, however, no general and scientific curriculum standard has been designed in psychological health(Cai & Huang, 2002). Furthermore with great burden of examinations, Chinese students could not understand psychological health very well in the current instructional scheme, which could be reflected both in the psychological problems of high school students and little transfer or application of psychological skills in their lives(Li, Jin, & Sun, 2010).Therefore, it is critical to apply useful theoretical and practical scheme for understanding in psychological health courses.

Teaching for Understanding (TfU) framework is based on a five years project developed out of Harvard University’s Project Zero (“Project Zero: Teaching for Understanding,” 2013). According to Perkins(1999), students usually do “knowledge telling”, simply telling what they know about a topic rather than “finding and expressing a viewpoint.” Knowledge telling does not understand. Understanding something is a matter of being able to carry out a variety of “performances” concerning the topic(Perkins & Blythe, 2009). A student might be able to regurgitate reams of facts and demonstrate routine skills with very little understanding. Perkins brought us a “performance perspective of understanding”, that “understanding a topic of study is a matter of being able to perform in a variety of thought-demanding ways with the topic, for instance to: explain, muster evidence, find examples, generalize, apply concepts, analogize, represent in a new way,and so on” (Perkins, 1993). He explained further that “If understanding a topic means building up

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 239 Proceedings of International Conference of Educational Innovation through Technology performances of understanding around that topic, the mainstay of learning for understanding must be the actual engagement in those performances.”

Many researcher have done on improving students’ understand and learning outcome in psychology classes. Peering teaching is a common method to enhance students’ learning experiences (Muir & van der Linden, 2009; Wesp, 1992), by which students feel enjoyable and comfortable during the learning and teaching process. Role play could (Banziger, 1984) also be an effective way to conduct problem-based learning in order to enhance students’ learning experiences. Turing large psychology class into small one is a way to personalize students’ experience in order to engage students into active learning(Benjamin, 1991).

In this study, we combined peer teaching and project based learning to redesign a psychology health class under the teaching for understanding framework. Our hypothesis is that, using teaching for understanding framework in psychological healthy class will improve students’ understanding of psychological health, therefore truly enhance student’s psychological health level and help build a positive attitude to life.

2. Research Design In this study, we designed a teaching unit in psychological health class with the topic of “understanding psychological disorder” using teaching for understanding framework. Symptom Checklist-90-Revised (SCL-90) was used as the major learning material. It is the instrument evaluating a broad range of psychological problems and symptoms of psychopathology.

The overall goal of the unit is for the students to understand psychological disorders, and how disorders can be recognized and prevented. According to Bloom’s Taxonomy, we set three types of goals: cognitive goals, affective goals and psychomotor goals. Then a series of thought-demanding activities will be provided to understand as well as facilitate the understanding to advance. Students will engage in those activities and assess what they have achieved along the process. Furthermore, those activities will be learner-centered and support various learning styles so that students can dominate this inquiry process in their own favorite manner. Project based learning and discussion board will be used to help students fully engaged in related learning activities.

3. Pilot study In the current study, we selected two classes from one high school in Shanxi Province in China, each has 61 students. The two classes are taught by the same instructor in psychological health class. The instructor taught one class (the experimental class)by using teaching for understanding framework. The experiment class students were asked to build up a project to explore and present one of the disorder dimensions in SCL-90. Also, they are allowed to post what they are found to the school’s online discussion board while they are developing the project. Another class (the control group class) was taught by the instructor using the traditional lectured to teach and learn all dimensions of SCL-90. After two weeks of learning, a followed up survey was administrated to evaluate the motivation, expectation of learning effects and learning performance of the two groups. The survey firstly asked students about their general motivation and satisfaction to take high school psychology class with a 5 points scale. Then they are asked about the motivation and satisfaction of the classes about SCL-90 in the past two weeks. They are followed by a test of all

240 EITT 2013, Williamsburg, VA, USA, November, 2013 Using Teaching for Understanding Framework in High School Psychological Health Classes the dimensions in SCL-90 to evaluate the understanding level of students. In addition, an interview is carried out for the teacher.

4. Result and Discussion The result indicated that the general motivation and effect expectation of experimental group is lower than the control group. This tendency does not coincide with the hypothesis. During the interview with the instructor, she indicated that according to her observation, the students from experimental class seemed to be more engaged in class activities, which was opposite with the survey result.

Furthermore, no significant motivation change or effect expectation change is found after the intervention of this class (Table 4.1); it indicated that one specific class may be not sufficient to change the long-term attitude of students about psychological class. We may take the second survey at the end of the semester to see if there will be significant differences after TfU framework has been used for longer time.

Table 4.1 The Attitude Difference of Students

Experimental Group Control Group Sig. n M SD n M SD

General motivation 61 3.52 1.02 61 4.33 0.68 0.00**

Specific motivation 3.44 0.99 3.96 0.65 0.00**

General effect expectation 3.48 0.92 4.16 0.66 0.00**

Specific effect expectation 3.21 1.02 3.95 1.76 0.00**

Motivation change -0.82 1.13 -0.36 0.66 0.10

Effect change -0.26 0.77 -0.21 0.69 0.71 Note. **indicated it is less than 0.01 (2-tailed).

The test of all the dimensions in SCL-90 demonstrated significant difference between experimental group and control group. The test provided nine cases for students to diagnose which dimension is appropriate to describe the symptoms of their friends. This test assessed the application of the knowledge they learned in the course, which require a high level of understanding. The total score of experimental group is significantly better than the control group (Table 4.2), which demonstrated that the understanding performance of experimental group is generally better than the control group. In the analysis of each dimension, it is indicated that experimental group performed significantly better than control group in paranoid ideation, phobia, and interpersonal sensitivity, which are the most difficult three dimensions according to the accuracy (Table 4.2). This result reflected that with the increase of problem difficulty, learning for understanding instructional approach is more helpful for the students to solve the problems. With the learning for understanding instructional approach, students are more competent in solve difficult, ill-structured case in the practical environment.

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Table 4.2 The Performance Difference of Students

Experimental Group Control Group Accuracy Sig. (%) n M SD n M SD

Obsessive-compulsive 61 0.73 0.44 61 0.62 0.49 68.0 0.177

Somatization 0.77 0.43 0.66 0.48 71.3 0.164

Phobia 0.74 0.44 0.56 0.50 64.8 0.037*

Depression 0.85 0.36 0.92 0.28 88.5 0.260

Interpersonal sensitivity 0.79 0.41 0.57 0.50 68.0 0.011*

Paranoid ideation 0.64 0.48 0.44 0.50 54.1 0.029*

Anxiety 0.85 0.36 0.77 0.42 81.1 0.251

Psychoticism 0.87 0.34 0.80 0.40 83.6 0.332

Hostility 0.69 0.47 0.67 0.47 68.0 0.848

Total 6.93 1.80 6.01 1.96 0.008** *indicated the significant is less than 0.05, **indicated it is less than 0.01 (2-tailed).

5. Conclusion The result of this research indicated that learning for understanding instructional approach is beneficial for students’ performance in applying knowledge in practical cases. Specifically, the effects of learning for understanding instructional approach in improving students’ ability to solve difficult problem is much better than the easy problems. Accordingly, this approach is more competent in the improvement of problem solving ability of difficult, ill-structured problem rather than the opposite. However, no difference of motivation change or effect expectation change is found in either group; it indicated that one specific class is not sufficient to change the long-term attitude of students about psychological class.

References: Banziger, G. (1984). A problem-solving workshop: the middle east comes to a social psychology class.Teaching of Psychology (p. 36,38). Benjamin, L. T. (1991). Personalization and active learning in the large introductory psychology class. Teaching of Psychology, 18(2), 68–74. Cai, J., & Huang, J. (2002). Explore on the model of middle school psyological classess. Journal of Teaching and Management, (4), 30–32. Li, Q., Jin, Y., & Sun, X. (2010). Effect of mental health lessons on students’ mental health level. China Journal of Health Psychology, 18(12). Muir, G. M., & van der Linden, G. J. (2009). Students teaching students: an experiential learning opportunity for large introductory psychology classes in collaboration with local elementary schools. Teaching of Psychology, 36(3), 169–173.

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Perkins, D. N. (1993). Teaching for Understanding. American Educator: The Professional Journal of the American Federation of Teachers, 17(3). Perkins, D. N., & Blythe, T. (2009). What is Teaching for Understanding? Retrieved from http:// www.uknow.gse.harvard.edu/teaching/TC3-1.html Perkins, D. N., & Unger, C. (1999). Teaching and learning for understanding. In C. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (3rd ed., pp. 91–114). Mahwah, NJ: Erlbaum. Project Zero: Teaching for Understanding. (2013). Harvard Graduate School of Education. Retrieved from http://www.pz.gse.harvard.edu/teaching_for_understanding.php Wesp, R. (1992). Conducting Introductory psychology activity modules as a requirement for advanced undergraduate classes.Teaching of Psychology (pp. 219–220).

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244 EITT 2013, Williamsburg, VA, USA, November, 2013 Zhao, C.L., & Huang, Z.F. (2013). The application research of intelligent push technology in smart learning environment. Proceedings of International Conference of Educational Innovation through Technology, 245-252.

The Application Research of Intelligent Push Technology in Smart Learning Environment

Chengling Zhao, Zhifang Huang Central China Normal University Email：[email protected]; [email protected]

Abstract: The design and application of smart learning environment has become a new research field now. The intelligences of smart learning environment come through in environment, resource, service and technology. The resource depends on education cloud and will be enriched in a large degree. However, information overloads, resource obscurity, resource wildering and so on are the identified problems in education cloud. So the learners can not search the appropriate learning resource correctly. This paper presents the application of Push Technology, in order to solve these problems. The objects, contents and ways of push technology will be discussed in this passage. Moreover we will design a mode for push service in the end.

Keywords: push technology, smart learning environment, education cloud, application research

1. Introduction 1.1. Background It is about more than ten years for education information construction since 1990s. The development of information technology in education, not only has made remarkable achievements, but also faces new challenges and problems. As for the constant process of educational information, the design and application of smart learning environment has become a new field in the current research of educational technology. As for the sustainable development of the internet of things, the ubiquitous network technology, interactive whiteboard technology, sensor technology, learning situations recognition and context-aware technology, artificial intelligence technology and some rational technologies, the smart learning environment is not an imagination but a reality that we can make it come true step by step. The development of smart classroom and smart school has been implemented in some parts of China. Shanghai will build several smart classrooms for secondary vocational school in the plan of Shanghai Secondary Vocational Educational Information Construction Plan. Ningbo of Zhejiang province has introduced smart classroom system. The system will promote small class teaching effect and Ningbo will explore whether every child encouraged by the new information technology of this system can have a positive and happy learning or not.

The construction and application of smart learning environment has an important significance to the educational informatization development to solve the problem. Moreover, the construction of intelligent learning environment is also important for reconstructing traditional learning environment, stressing teaching dilemma, changing teaching and learning methods, optimizing the process of teaching and management, promoting higher order thinking skills ability and improving the development of teachers.

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1.2. The Problem The educational resources of smart learning environment will be used in education cloud. The resource depends on education cloud will be enriched in a large degree and can satisfy the need for personal learning. However, some problems are leaded by education cloud, including information overloads, resource obscurity, resource wildering and so on.

1.3. Proposed Solution This paper introduces the application of Push Technology, in order to solve the problems. The application of personalized push technology is vital for smart learning environment. This technology can provide appropriate educational resources based on students. So the learning process, interest and result of students can be effectively improved through personalized push technology. And teaching quality, learning motivation, the cultivation of inquiry awareness and problematic consciousness can be enhanced by push technology.

2. Literature Review The earliest literature on pushes technology used in the field of information services was found from the late 1990’s. Since then, library information departments in some countries began to explore how to make use of push technology to meet the users’ personal information need better, and information analysis, screening and filtering technology based on the characteristics of individual needs were studied, and push technology had been applied to online initiative information push services. The application researches push services cover the following aspects: information navigation and retrieval (Burke, Hammond & Yound, 1997; Brin & Page, 1998, Serrano-Guerrero, et al,, 2011), personalized products recommendation (Cheung, Tsui & Liu, 2004; Liu, Lai & Lee, 2009), information –sharing system (Shihab, et al, 2008; Li & Kao, 2009; Kazienko, Musial & Kajdanowicz, 2011), information recommendation system (Bobadilla, Serradilla & Hernando, 2009; Bobadilla, Serradilla & Bernal, 2010), how to provide recommendation services by mobile platform (Lee, Cho & Kim, 2010), comparative analysis on push-pull query strategies in wireless sensor networks (Kapadia & Krishnamachari, 2006), push technology in the random information dissemination (Doerr, Friedrich & Sauerwald, 2009).

By contrast, the study of push technology in China started late, but was full of vigour. From 1997 to 2003, there were only less than 100 articles about push technology in china. Seen from the literatures collected, many of them were the introduction of push technology, and there were very little literature on the theoretical research. However, from 2003 to present, the papers on this technology were raised to more than 1500 and many of them research on the theory and application of push technology. In recent years, the research field mainly in the following areas: web catalogue recommendation, message retrieval , E-commerce personalization services, initiative personalized service in library, the application of push technology in mobile phones and other mobile terminal fields, email pushing and so on.

Push technology has been widely used in the field of information services throughout the world at present. However, the research of how to use the push technology to provide students with personalized information services in the smart learning environment is not yet involved.

246 EITT 2013, Williamsburg, VA, USA, November, 2013 The Application Research of Intelligent Push Technology in Smart Learning Environment

3. The Analyse of Push Technology Applied Smart Learning Environment 3.1. Concept and Characteristics of Smart Learning Environment 3.1.1.Concept of smart learning environment. There is no unified definition for smart learning environment until now. Smart learning environment is a learning space or an activity space that can apperceive learning scenarios, identify learner characteristics, provide suitable learning resources and convenient interactive tools, and it can record the learning process and evaluate learning outcomes automatically so as to promote the effective learning of learners (Huang, et al, 2012).

Smart learning environment (Zhu & He, 2012) is a new learning environment that can effectively promote the development of intellectual ability and appearance of wisdom action. It is guided by advanced thoughts and theories of learning (such as Learning Psychology, Study Science), teaching (such as Constructional Teaching Theory, Learning Environment Design Theory), management (such as knowledge Management) and utilization (such as Usability Engineering, Human Factors Engineering) and supported by appropriate information technology, learning tools, learning resources and learning activities. It has the ability to analyses the new data obtained by perceiving learning environment information from every side and the historical data formed in the learners’ learning process. It can identify learners’ characteristics (such as study ability, cognitive styles, and learning preferences) and learning scenarios, and then flexibly generate the most suitable learning tasks and activities so as to guide and help the learners to make the right decision (Zhu & He, 2012).

The author of this paper think it is a new learning technology, not only can be used in classroom management and teaching, but also can combine reality with virtual environment together. Smart learning space shown as materialized form and the smart support of the activity between teacher and student can demonstrate the smartness of smart learning environment. Students can experience the happy and effective learning by adopting new technology. This experience will enlighten students’ motivation and creation and stimulate new exploring spirit during learning. For the using of new technology to solve easy and inflexible problems, students can promote higher order thinking skills including creative ability, problem solving ability, decision making ability and critically thinking ability by doing more complex analysis.

3.1.2. Characteristics of Smart Learning Environment. The wisdom of smart learning environment is mainly reflected in the following aspects:

a. Situation perception: It can perceive learning environment information from all directions to analysis the students’ need and provide them with adaptive learning support. b. Highly interactive: It can bring all characteristics and utility of each subject in the smart learning environment into full play. It should have rich, diverse forms of interaction and a good interaction effect. c. Resource acquisition: It should provide rich digital learning resources for learners to choose at anytime and anywhere. And it should provide personalized diagnosis of learning so as to provide personalized learning resources according to the learners’ characteristics. d. Learning history record: It can record historical data formed in the learners’ learning process so as to mine and deeply analyze the data, and then provide persuasive formative evaluation and summative evaluation.

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3.2. The Character Analysis of Information Acquisition in Smart Learning Environment The educational resources of Smart learning environment will be used in education cloud. However, some problems are brought by education cloud.

3.2.1. Information overload problem. The reason is the amount of information in living environment is always far higher than its consumption and absorbing comparing to human’s memorizing things and processing information ability. A large number of redundant information serious interference with accurate analysis and correct choice related to the useful information. Because of the huge capacity of the cloud computing platform, so we don’t need to consider the capacity during integrating resource. As a result, overlooking the effective information filtration and information overloads problem become more seriously.

3.2.2. Resource obscurity. The originally clear information and resources are concentrated in the cloud computing platform and fuzzy. And the platform provider an interface for users and weaken people’s participation. So on one side, it frees people from trifles in learning, on the other side, users confuse about the truth of information.

3.2.3. Resource wildering. The resource depends on education cloud and will be enriched in a large degree. The learner can not find appropriate learning resource quickly and accurately.

3.3. The Advantages of Information Service of Push Technology In Smart Learning Environment The information delivered to users actively and timely through smart push technology bases on users’ character. The details of advantages are below.

3.3.1.Search and send information automatically. The learners’ character can be identified and predicted by smart push technology. And smart push technology sends learning resources to learners according to learners’ need. This need is collected automatically. So it can effectively auxiliary learners’ learning and stimulate learning interest.

3.3.2. Save query time. The needed resources are sent by smart push technology automatically, so it can decrease the time on querying information and learners have more time to do deeply thinking, so it can also promote learners’ high order thinking skills.

3.3.3. Improve information accuracy. The effective filtration of information based on learners’ character through push technology can get rid of interference information and increase the accuracy of information.

4. The Main Research Content of Information Service of Push Technology in Smart Learn- ing Environment 4.1. Push Object (see figure1) Objects of information push services in the smart learning environment including teachers, students, and teaching manager, in which the student is the main object of the service. What is the basis of pushing personalized resources to different students will be discussed in this part.

248 EITT 2013, Williamsburg, VA, USA, November, 2013 The Application Research of Intelligent Push Technology in Smart Learning Environment

Student user models can be created based on the basic information of the students, including learning styles, cognitive level and learning history. The basic information includes the student’s name, gender, age, grade, e-mail and so on. Learning style is the personality characteristics of learning method which learners sustained. It is the sum of learning strategies and learning tendencies. Cognitive level refers to the ability of the individual’s awareness, judgment and evaluation of external things. The level of cognitive related to practical experience, level of knowledge, thinking skills and information storage. It reflects their mastery of knowledge. Learning history recorded students’ historical learning process. System can continuously update student model by learning history.

Figure1. Student model

4.2. The Information Content of Pushing It should push diversified, systematic, personalized learning material, students to support their study effectively in smart learning environment. The learning process includes ‘before class’ ‘in the classroom’ and ‘after school.’ To promote students’ pre-class preparation resources, so that they can have a general understanding they will learn, including curriculum, lesson plans, teaching contents, teaching tools and so on.

It can make the learning resources, learning partners, learning situation path fitting in the class. Learning resources are divided in accordance with the kind and type. There are different kinds of resources, including text, video, audio, animation, etc. There are different types of resources, including ‘basic theoretical knowledge’, ‘applied knowledge’ and ‘expansible knowledge’. Recommending suitable learning partners to the learners in collaborative learning model can make each individual learners play the maximize advantages. Pushing learning path is to recommend personalized path from all possible learning sequences of the learning objectives knowledge point according to learner’s characteristics.

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It can promote personalized practice and learning path, according to different students, after school; make every student further consolidate relatively weak points.

4.3. Ways of Push Service The mainly push service ways are in the following:

4.3.1. Student subscribe. Students should fill demand details when subscribing, then the system can push information to them according to their customized demand.

4.3.2. System recommend resources to student based on the evaluation of the test. The student login customized test systems for testing, and solves the matching problem of pushing learning resources and personalized learning content according to the test results.

4.3.3. System automatically push. Tapping student’s learning information continually by the learning analysis technique, then update the student model and recommended resources accordingly.

Figure2 Push model design

250 EITT 2013, Williamsburg, VA, USA, November, 2013 The Application Research of Intelligent Push Technology in Smart Learning Environment

4.4. Push Model Design (see figure2) Learners login intelligent promote learning support system by the student terminal in the smart learning environment. They should register for the first time to fill in their basic information. Different types of push technology services can be chosen by learners. The types of services including ‘student subscribe’, ‘test’ and ‘automatically push’. And the students can select one or several services. The system will choose different resources from education cloud platform according to the chosen services and send them to learners. The resources chosen from repository are produced by knowledge recommendation module. The knowledge recommendation module is generated by recommend match operation. And the operation of student model, learning situation model, cloud resource is the way that the recommend match operation used.

5. Conclusions and Future Work The design and build of smart learning environment is the inevitable trend of education information developing to a certain stage. With the continuous development and application of a variety of new technologies, smart learning environment will never be a theoretical concept, but gradually develop into reality. At present, the development of smart learning environment is in its infancy, and theory and technology still need further improvement. It needs to go through a long stage of development to realize the design and application of the smart learning environment. The objects and contents and ways and the design of mode of push technology applied in smart learning environment are discussed above. The purpose of this paper of proposing the application of push technology in the smart learning environment is to provide a research framework, in order to arouse researchers’ attention to this application.

Near future work should be concentrated on refining the design model and how to evaluate the validity of the application of push technology in smart learning environment. The validity can be evaluated by the accuracy of the information pushing, pushing speed and so on.

References Brin, S. & Page, L. (1998). The anatomy of a large-scale hyper-textual web search engine. Computer Networks and ISDN Systems, 30:107-117. Bobadilla, J., Serradilla, F., & Hernando, A. (2009). Collaborative filtering adapted to recommender systems of e-learning. Knowledge-Based Systems, 22(4), 261-265. Bobadilla, J., Serradilla, F., & Bernal, J. (2010). A new collaborative filtering metric that improves the behavior of recommender systems. Knowledge- Based Systems, 23(6), 520-528. Burke, R. D., Hammond, K. J., & Yound, B. C. (1997). The Find Me approach to assisted browsing. IEEE Expert, 12(4), 32-40. Cheung, K. W., Tsui, K. C., & Liu, J. (2004). Extended latent class models for collaborative recommendation. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 34(1), 143-148. Doerr, B., Friedrich, T., & Sauerwald, T. (2009). Quasirandom rumor spreading: Expanders, push vs. pull, and robustness. In Automata, Languages and Programming (pp. 366-377). Springer Berlin Heidelberg. Huang, R, Hu, Y, Yang J. &Xiao G. (2012) The Function of Smart Classroom in Smart Learning Age. Open educational research, (4):22-27. Kapadia, S., & Krishnamachari, B. (2006). Comparative analysis of push-pull query strategies for

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wireless sensor networks. In Distributed Computing in Sensor Systems (pp. 185-201). Springer Berlin Heidelberg. Kazienko, P., Musial, K., & Kajdanowicz, T. (2011). Multidimensional social network in the social recommender system. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 41(4), 746-759. Lee, S. K., Cho, Y. H., & Kim, S. H. (2010). Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations. Information Sciences, 180(11), 2142-2155. Li, Y. M., & Kao, C. P. (2009). TREPPS: A trust-based recommender system for peer production services. Expert systems with applications, 36(2), 3263-3277. Liu, D. R., Lai, C. H., & Lee, W. J. (2009). A hybrid of sequential rules and collaborative filtering for product recommendation. Information Sciences,179(20), 3505-3519. Serrano-Guerrero, J., Herrera-Viedma, E., Olivas, J. A., Cerezo, A., & Romero, F. P. (2011). A google wave-based fuzzy recommender system to disseminate information in University Digital Libraries 2.0. Information Sciences, 181(9), 1503-1516. Shihab, E., Cai, L., Wan, F., Gulliver, A., & Tin, N. (2008). Wireless mesh networks for in-home IPTV distribution. Network, IEEE, 22(1), 52-57. Zhu Z. T, & He, B. (2012) Smart Learning as New Realm of e-Education. E-Education Research, (12): 5-13.

Acknowledgements This paper is supported by “Development of Low Cost and Experiential Informational Service key technology and terminal of rural area” which is supported by science supported plan as a major program during the 12th Five-Year Plan Period. (No. 2012BAD35B02)

252 EITT 2013, Williamsburg, VA, USA, November, 2013 Zhao, H., & Zheng, M. (2013). The investigation and analysis about the status quo of the resources in visualization teaching for deaf students. Proceedings of International Conference of Educational Innovation through Technology, 253-262.

The Investigation and Analysis about the Status Quo of the Resources in Visualization Teaching for Deaf Students

Huichen Zhao, Man Zheng Henan University Email: [email protected]; [email protected]

Abstract: As for the deaf students in the images era, the effective use of visual information can make up for the inadequacy and improve the learning effect. This paper took some special education school in Shangqiu area Henan province as an example investigated and analyzed the status quo of the resources in visualization teaching for deaf students.

Keywords: visualization teaching, deaf students, resources design

1. Introduction 1.1. Background The population of disabled person is about 70,000,000 in China, of which about 13,000,000 are deaf. The population of the deaf under 18 years old who should accept the education is about 100,0000. As very large and vulnerable groups, they are facing unimaginable difficulties and hardships in the study, work and life.

The rapid development and wide application of information technology promoted technological progress of all walks of life, and putted forward new demands to the deaf education. Visual teaching can make the complex teaching content concrete, visual and vivid. Easterbrooks & Baker（2002 ）pointed out that for the hearing impaired individuals, their learning was mostly derived from the visual information, the visual form of language information became the most feasible way.

As for the deaf students in the images era, the effective use of visual information can make up for the inadequacy and improve the learning effect. Teachers can use visual information effectively, mobilize the deaf children's image thinking, and arouse their emotion, which is more conducive to the knowledge imparting and the emotion exchange. Therefore, the application of the visual teaching for deaf children has very important meaning for improving the learning of deaf students.

1.2. Literature Review Many countries attached great importance the application of visual resources for deaf students, such as the United States established Beyond vision website, Japanese applied real projector to help teachers draw attention to deaf students. In view of the particularity of deaf students with visual, the application of visualization technology is increasing. According to the characteristics of the hearing impaired Children，Italian developed the online software (Logic - based e-Tool for Deaf Children), used basic architecture analysis and evaluation model, and combined the written language and sign language, by reading the world popular fairy tale "the ugly duckling", in order

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to train the reading ability of Deaf Children, raise its temporal reasoning ability. In addition, the visualization technology is penetrating into the auxiliary appliance of deaf students, expanding the deaf students' learning ability. Among them, the auxiliary software AudiSee made teacher's facial image transfer to the student desktop monitors or the big screen of the classroom, so deaf students can understand the teacher's lips, without regarding to the position of the teacher or using any language instruction. The invention of such software provides better tool support about visualization teaching for deaf students, encouraging visual teaching for deaf students from theory to practice deeply.

China have begun to focus on visual education for deaf children, and paid attention to develop resources in visual education for deaf students and gradually applied education resources to the teaching of the deaf students.

Firstly, in the aspects of visual cognitive, Li（2006）thought that the visual played an important role in the cognition of deaf students, suggested that we should present visual information through modern media, to help the deaf students use image thinking and improve the learning efficiency.

Secondly, in terms of visual scene building, Zhou（2006）pointed out about the developing direction of the deaf students' visual situation education with two aspects: expanding the scope of research visual situation and letting the deaf students better in visual situation; Fu（2011） according to Chinese teaching, put forward should give full play to the visual effects for language teaching in deaf school, in order to break through the language barrier, make up the deaf birth defects, and make information disseminate effectively.

Thirdly, in regard to the development of visual resources, Zheng（2008）divided the special education network resources into comprehensive resources, early intervention information resource, hearing impairment resources, visual impairment resources and assistive technology resources, etc., and then analyzed the research and application of special education network resources conditions; Chen（2009）in Xuzhou normal university thought the information resources in deaf education should be in line with the strong characteristics of the deaf students' visual sensitivity, put forward through the show of sign language, making it the voice and text vivid annotation and promoting national standard sign language in the country to get promotion and popularization, and developed the deaf sign language 900 video, animation "sign language" and "the sign language video e-book".

Fourthly，in terms of visual teaching conduct, Yuan（2008）suggested that we should us voice information visualization for Chinese phonetic teaching in deaf school, and make the pronunciation parts and method become visible and touched。Zhang（2009）pointed out that we should correctly used live-action video files, and vivid, slightly exaggerated animation and colorful images, image, according to the defects of the disabled children compensation theory, truly outstanding teaching important and difficult knowledge. Zhao&Zheng（2013） pointed out according to the implementation of deaf students' cognitive characteristics, information processing method in visual teaching for deaf students should be applied to analyze the teaching relations, an we should development targeted resources and tools as the support.

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In all, the domestic research focused on argument of the importance of visual environment for deaf students learn, focused on the studies from the tool level such as graphics, image rendering, the contents and forms of the resources in visual education is still single, humanistic care, and other issues are not enough.

1.3. Problem Proposed Visualization teaching has become the important way to optimize deaf teaching; the resource in visualization teaching has become the vital issues. Due to the special needs of the deaf students, deaf school rely more on teaching equipment than the ordinary school, in order to show the resources in visual teaching. But how to use teaching media, use what kind of teaching media, how to design the visual teaching resources and so on that have become the new problems in the visualization teaching for the deaf students.

2. Investigation of the Situation about Learning of Deaf Students According to their learning and thinking, the deaf students have some demand for visual learning content. Due to the lack of the ability of language, deaf students are interested in bright colors, vivid image and substantial action. Therefore, it is very necessary that visual teaching resources meet the learning characteristic of deaf students.

Through the investigation, it is helpful for us to understand and grasp the learning characteristic of deaf students. The application of visualization technology has suitable meaning to choose visualization technology and design the corresponding teaching strategies.

2.1. The Aim of the Investigation The aim of the investigation is to preliminary understand the general situation of the learning characteristics of the deaf students, to further grasp the basic situation and style of deaf students.

The investigation and analysis of learning way about deaf students can explore suitable learning resources and design teaching resources, which can meet the learning characteristics of deaf students.

2.2. The Subject of the Investigation According to the sampling theory, this study randomly investigated the special education school teachers and students the Shangqiu area of Henan Province. The total was 180 questionnaires, 156 questionnaires recovered, and the recovery rate was 86.7%. Among them, 13 invalid questionnaires, 143 valid questionnaires, effective rate was 91.7%.

2.3. The Method of the Investigation This study used the method of questionnaire survey through statistical analysis of the data, we can clearly understand the preferences and find out suitable resources for deaf children. At the same time with personal interviews, we talked with individual teachers in deaf school, and dig out some non quantifiable factors, in order to understand the learning style of deaf students and arrange the teaching resource well.

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3. The structure of the questionnaire about the Resources for Deaf Students In order to understand the learning condition and find more appropriate learning methods for deaf students, we designed the issues containing radio, multi selection and sorting a total of 22 questions. The questionnaire covered the characteristics of deaf students learning, teaching method s, information ability and visual resources. The investigation about visual resources for deaf students can be targeted to solve these problems and design the visual resources, which will meet the characteristics of deaf students well.

Table 1. The dimensions and related problems of the questionnaire about resources design in visualization teaching for the deaf students Dimension Related Problems

1.how long most of deaf students can continue the attention in class, 2. What method can attract their attention in the class? Learning 3. As for illustrations book and text books, which do deaf students like? characteristics 4. Which way deaf students like to feedback learning content? of deaf students 5. Which characteristics of deaf students are the teachers difficult to deal with in the classroom? 6. What kind of teaching content can impress the deaf students greatly? 7. Which way do deaf students acquire knowledge besides classroom learning? 8. Which way do deaf students tend to contact new thing? 1. Do you use information means in the teaching process? 2. What kind of teaching methods do you adopt? Teaching 3. Do you show the knowledge structure to the students before class? strategies of the 4. do you think knowledge structure have effect for the deaf students? teacher 5. Which kind of teaching style do deaf students prefer?

Information 1. The attitude of the use of visualization technology in the teaching attitude and process? ability of the 2. What role does visualization technology play in classroom? teacher 3. What skills do the teachers need to master for the deaf student? 4. Do you pay attention to information education for the deaf students? The problem 1. Do you know something about visualization? of visualization 2 .do you think that the multimedia teaching software have problems in resources the application of deaf education? 3 .do you think that the deaf students are interested in visual technology? 4. What kind difficulties visual context can solve for the deaf students?

4. Application Status of the Resources in Visualization Teaching for Deaf Students According to the survey results, deaf students tended to the dynamic teaching auxiliary tool in the process of learning; the teacher used the information technology initiatively, especially used the multimedia to cater to the preferences of the deaf students, to improve the teaching quality .

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However, teachers had the awareness of using information technology tools to create visual context, but did not have the initiative consciousness of visualization design about teaching content for deaf students. Therefore, in the design of their visual teaching resources, the selecting and using of teaching media is already relatively mature, but the visual design of teaching contents is needed to strengthen.

4.1. Auxiliary Teaching Tool Deaf Students are Interested in According to the survey results, deaf students liked dynamic teaching aids in the learning process, and the majority of deaf teachers used information technology and do not excluded the use of multimedia and computer network. The survey results point out the direction for the design of visual teaching resources and the choice of teaching media.

In 143 copies of questionnaires, the deaf students were interested in the static picture of the 24 questionnaires, 118 questionnaires deaf students were interested in real subject, the choices deaf students were interested in video are 80, the questionnaires deaf students were interested in multimedia courseware were 113, but deaf students interested in the textbook were only 3 questionnaires.

According to the survey results, the deaf students were most interested in the mold material and multimedia courseware, followed by video. Therefore, for the design of their visual teaching resources, we can choose the teaching tools to optimize the learning and teaching for deaf students.

Table 2. The auxiliary teaching tool deaf students are interested in Static Television Multimedia Just the Real subject picture and recording courseware textbooks 24 118 80 113 3

4. 2. Teaching Way by the Teachers in Deaf Schools According to the results of the survey, 67% of the teachers often used multimedia to create teaching situation at ordinary times, 28% of the teachers used equipment and tools to assist teaching. The use of tool will give the teaching conveniently, but the resources design by the teacher will directly affect the learning effect.

Figure 1. Teaching methods of the teachers in deaf school

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4. 3. Knowledge Structure Shown by the Teacher for Deaf Students According to the survey results, 43% of the teachers occasionally presented knowledge context diagram to students, and 15% teachers never used the chart form show knowledge for the deaf students. Although the teacher in deaf schools have the consciousness of using the information technology to improve the teaching quality, but the initiative consciousness on instruction design is not enough.

Figure 2. The teachers presents knowledge structure for deaf students

Figure 3. The effect of the knowledge structure for deaf students

5. Problems about the Resources Visualization Teaching for Deaf Students In the questionnaire, the survey set up the problems about information technology and visualization resources for deaf students, such as the problem of the application of information

258 EITT 2013, Williamsburg, VA, USA, November, 2013 The Investigation and Analysis about the Status Quo of the Resources in Visualization Teaching for Deaf Students technology? How do the teachers understand visual teaching and the problems about the application of multimedia software in deaf education? According to the results of the survey statistics, the problems in the design of visual teaching resources of deaf students are as follows.

5. 1. Lack of Equipment, the Capacity of Teachers Needs to be Improved According to the sixth survey questions, we statistic the main problems existing in the application of information technology in deaf school, which included the lack of hardware equipment and the ability to use information technology by the teachers.

Figure 4. The problems in the application of visual technology

5. 2. The Form of Teaching Resources to is Single, and not Interesting Because the problem of the current multimedia teaching software and visualized teaching resources development was multiple choices in the questionnaire, so we did not count the percentage.

In the 143 recovered and valid questionnaires, 69 questionnaires suggested that the resources in visualization teaching did not conform to the characteristics of the students, 48 questionnaires suggested that the resources in visualization teaching did not match teaching contents. 116 questionnaires suggested that resources in visualization teaching were not interesting, 55 questionnaires suggested that the number of the resources in visualization teaching was small.

According to the survey results, the current resources in visualization teaching were not interested because of the single form, and the amount of the resources in visual teaching for deaf students was very little.

Table 3. The problems about resources development in visualization teaching Not in accordance Not in accordance with the Interest small with the teaching characteristics of ifferential number content students 69 48 116 55

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5. 3. Attention Teachers Pay to the Visual Teaching is not Enough According to the survey, 59% of the teachers just understood visual teaching for deaf students a little, 34% of the teachers only heard of visual teaching, but did not understand visual teaching for the deaf, only 3% of the teachers understood visual teaching very much. Therefore, the visual teaching resources quantity are few, the form is single, not fun, even not for the deaf.

This is partly because deaf teachers do not pay attention to visual teaching enough. Only let a small number of teachers develop resources in visualization teaching for deaf students, will inevitably make the form of the resources single.

Figure 5. Deaf teachers understand the level of visualization

6. Method for Improving Resources in Visualization Teaching for Deaf Students According the problems of the application about the resources in visualization teaching for deaf students reflected by the results of the survey, we should propose the method to improve the resources in visual teaching.

6.1. Promote the Visual Teaching The visualization teaching can improve the teaching efficiency in deaf schools, change the traditional teacher centered teaching mode, and cultivate the ability to learn autonomously and explore innovatively for deaf students.

The Application of visual teaching methods must base on the information equipment. According to the design and development of resources in visualization teaching, the relevant departments should provide the required software and hardware equipment.

Based on the size and characteristics of the school for deaf students, the school should make each classroom be equipped with multi-media equipment. So when each multimedia device are connected to campus network, the teachers can download the required electronic resources and teaching visualization with the desired picture, video and other resources in the classroom.

6.2. Improve the Ability of Visualization Teaching Deaf students mainly rely on vision to obtain knowledge in the learning process. They like bright colors, vivid image and the movement of objects. So the loss of the hearing makes

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them unable to speak and lead to their reading inability, and the main thinking is in images.

In the investigation about learning situation of deaf students, deaf students like the teachers who have the feedback results more intuitive. According to problems reflected by the results of the survey, the teachers’ ability to apply the multimedia equipment needs to be improved and the attention the teachers pay to visual teaching is not enough.

The leaders in deaf school should integrate training for the teachers, not only making them accept the knowledge of visualization teaching, but also training the ability to use information tools for visualizing teaching. The teachers can design, develop resources for visualization teaching with multimedia devices, and use them to carry out visual teaching, in order to improve teaching quality.

6.3. Comprehensive development of resources The thinking of deaf students is in image stage, both static and dynamic visual image visual image can attract their attention. Wall charts, slides, mould, material objects visualization teaching tool can provide static visual information for deaf students, television, video, and film can provide dynamic visual information for deaf students.

Because the form of teaching resources was single in special education and the quantity was quite scarce, deaf teachers can use knowledge related to visualization, get the benefit by mutual discussion, and develop the resources in visual teaching comprehensively.

The comprehensive development of teaching resources can be the integrated collection of network resources，such as pictures, animation, video, audio and other resources. The school can develop the teaching resources independently or the organizations can establish the corresponding resource through cooperation.

References Chen, L. (2009). The thinking about the construction of digital resources in deaf education based on the practice. China Educational Technology, (3), 60-63. Easterbrooks, S. & Baker, S.(2002).Language learning in children who are deaf and hard of hearing: Multiple pathways. Boston: Allyn & Bacon. Fu, M. (2011). The exploration on strategies of vision context construction in language teaching in deaf school. Modern Chinese, (3), 19-20. Li, S. (2006). Use modern information technology to promote effective learning of deaf students. Jinan: ShanDong Normal University. Yuan, Y. (2008). The new breakthrough in Chinese pinyin teaching for deaf school - “voice information visualization” teaching practice research. A Journal of Modern Special Education, (11), 22-23. Zhang, Z. (2009). The use of information technology in special education. Modern Educational Technology, (11), 36-39 Zhao, H. & Zhen, M.（2013. The research on visualization teaching design for deaf students. Modern Educational Technology, (08). Zheng, J. (2008). The integration and parsing of network resources in Special education. Beijing: Higher Education Press. Zhou, Y.（2008. The research on strategies of Vision context construction in language teaching in deaf school .Nanjing:Nanjing Normal University.

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Acknowledgement This paper has been sponsored by two programs as follows: (1) The national science and technology supporting program“the construction of fusion model between Chinese language and Uygur language and learning services model for early childhood” 2014BAH06F01; (2) Chinese postdoctoral science foundation funded project “theoretical construction and practical application of visualization teaching for the deaf students “(2012M511563).

262 EITT 2013, Williamsburg, VA, USA, November, 2013 Cui, G. Q. (2013). The relationship between adult students’ characteristics and their learning styles. Proceedings of International Conference of Educational Innovation through Technology, 263-270.

The Relationship between Adult Students’ Characteristics and their Learning Styles

Guoqiang Cui Yantai University Email: [email protected]

Abstract: Different learning styles usually direct students to achieve in different ways. This study examined the relationship between an adult student’s characteristics (age, gender, and race group) and their classroom learning profile. Survey was conducted to find out the difference between students’ age, gender, and race group and their VAK learning styles. Data was collected from 199 adult students of three schools from both U.S. and China. Research results revealed that more male students tend to have visual learning styles while more female students have auditory learning styles. Not much difference was found between male and female students’ kinesthetic learning styles. Results also indicated that students’ learning styles and habits have less relationship with their ethnicities.

Keywords: Learning Style, Adult Student,Visual,Auditory,Kinesthetic

1. Introduction Students of different characteristics could learn in many diverse ways through seeing and hearing, reflecting and acting, reasoning logically and intuitively, memorizing and visualizing, or drawing analogies and building mathematical models (Felder & Silverman, 1988). People in different groups or of different capabilities do not only learn in dramatically different ways, they also achieve in their unique ways (Dunn, 2001). To most individual students, learning would be most effective if they are taught in their own personal and customized way of learning. The ways students prefer in their learning are also referred to as learning styles. According to Grasha (1996), learning styles usually refer to different personal qualities that influence a student’s ability to obtain information, to interact with peers and the teacher, and otherwise to participate in learning experiences.

For students, understanding of their learning style preferences can have a significant influence on their academic performance and achieve (Peng, 2002). Knowing students’ learning styles will immensely help teachers to offer individual instructions and if students are distinct about their own learning styles, they will be able to learn in a most effective way that suits them. Realizing their personal and favorite learning styles would help students know their strong points while obtaining information and they can also become more realistic of their not-so-strong areas (Sissons, 2007). Positive results were also found that students’ learning can be greatly improved by tailoring teaching modality to students’ preferences or styles (Lynn, 1983). Besides helping students in the academic study, understanding of students’ learning styles will also help to improve student services such as in counseling area (Mathews, 1995).

The enormous diversities of students’ learning styles put teachers with pressure and challenges. Teachers have to perceptively realize students’ different learning styles and be explicit about the

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 263 Proceedings of International Conference of Educational Innovation through Technology way students process and absorb information (Anderson & Adams, 1992). Realizing the limitation of uniformity in most school’s courses and instructions, educational institutions of most levels are also seeking diversity and finding the balance between them (Guild &Garger, 1985). The diversity will greatly encourage tailored instructions to individual students and many studies have found that instructions that are consistent with students’ learning styles will immensely help produce effective learning outcomes (Andrews, 1981). Teachers should consistently watch students in order to completely understand them. Students’ personal differences need to be greatly considered, the instruction should be customized to students’ different abilities (Miller & Rose, 1975).

The study of learning styles has been going on for many years. In the past several decades, researchers have identified a lot of elements that contribute to students’ difference in learning and over 30 different kinds of learning style measurement have been expended (Guild &Garger, 1985). One classic learning style model is the Visual-Auditory-kinesthetic learning style which is well known for its abbreviated form VAK (Ibrahim, Morsi, & Tuttle, 2006). The VAK learning style focuses on the basic elements of the sensory preference and further discusses people’s preferences for collecting information or knowledge via many senses (Zina, 2004). According to the VAK learning styles, learners are mainly categorized into three kinds: visual, auditory and kinesthetic learners. For some people, they learn most from auditory input; others may depend on visual image. Still others learn most by kinesthetic ways. Usually each one has only one major learning model (Farwell, 1983).

Ever since its occurrence, the VAK model was adopted in a wide range in American educational institutions. More than 100 article have been published referring to the VAK learning style model (Kassaian, 2007).The questionnaire designed and presented according to the features of VAK learning styles by using a Likert-scale is by far the most common example of a learning styles instrument (Sharp, Byrne, &Bowker, 2007).

2. Literature Realizing that different students may have different learning styles, it is of great importance to investigate what factors can affect students’ learning styles. Researchers such as Dunn and Dunn (1979) argued that factors such as environment, emotion, sociology, physiology and psychology can all influence students’ learning styles. Bokhari (2011) also claimed that students’ learning styles are closely related to their attitude, personality, and characteristics. Among various factors that could possibly impact students’ learning styles, this study especially focus on three elements including age, gender, and ethnicities considering their inconsistent findings in literature.

Students of different age group might have different perceptions of the world as well as behaving differently based on their various life experiences. A review of literature indicates that there are currently inconsistent findings about students’ learning behavior among students of different age groups. For example, researchers such as Bromley (1958) argued that there is an age- related decrement in their learning behavior; however, other researchers such as Hulicka (1965) did not find the similar difference.

Regarding students’ gender factor, it is generally agreed that an understanding of the gender difference is the basis for understanding of their behavior (Keenan & Shaw, 1997; Zoccolillo,

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1993). With the growing realization of students’ different learning styles, people also recognize that males and females do not only have the physical difference, but they also have the psychological difference that has significant influence on the way people think and behave (Huesmann& Guerra, 1997). Past studies have demonstrated that there are great differences between males and females in learning orientation (Severiens& Ten, 1998), educational expectations (Freeman, 2004), and academic performance (Mortenson, 2001).

Besides students’ age and gender influences, students of different ethnicities could also perform differently because of their different cultural background. A number of research studies have been conducted to investigate students’ cultural or ethnic differences in their behaviors or learning styles. For example, Lam-Phoon (1986) conducted a study to compare learning styles between Asian students’ learning styles in Singapore and that of Caucasian students in U.S. He found that Asian students’ and Caucasian students’ learning styles are significantly different and Caucasian students have a higher preference for warmth, intake, and mobility. Dunn (1997) also argued that students do not perform or behave similarly when they have different cultural backgrounds. However, in another study, Aziz, Yi, Alwi, and Jet (2013) did not find the significant difference in learning styles across difference races.

Considering those inconsistent findings about age, gender, and ethnics in relation to students’ learning styles, this study will especially examine those three factors’ impact on adult students’ learning styles.

3. Methods 3.1. Purpose of Study This paper aims to examine the relationship between an adult student’s gender and their classroom learning profile. More specifically it examines the different students’ age, gender, and ethnics in relation to their perceptions of learning profile. Research questions are the following: a. How do students’ age relate to students’ learning profile? b. How do students’ gender relate to students’ learning profile? c. How do students’ race group relate to students’ learning profile?

3.2. Survey Instrument Survey methodology was used to determine the relationship between an adult student’s characteristics and their classroom learning profile. For purposes of this study, an individual’s classroom learning profile measures the efficacy of visual, auditory, and/or kinesthetic (VAK) modes of classroom instruction. A two-section questionnaire was developed by the researchers for this project. Four demographic questions were contained in the first section, ranging from gender, age, to ethnic background information. In the second section, 12 more questions were included utilizing a 5-point Likert scale to discern degree of agreement with statements regarding students’ different learning habits. A cover letter was also developed at the same time with detailed instruction and explanation to participants.

3.3. Participants 199 questionnaires were returned by participants from three schools both in the United States and People’s Republic of China. Of all the participants, 75 students were invited from an eastern

EITT 2013, Williamsburg, VA, USA, November, 2013 265 Proceedings of International Conference of Educational Innovation through Technology national university in China, while 68 other responses are drawn from a southern training base and another 55 others were from a southern public county school district. All participants from three different schools were adult students older than 18 years old.

3.4. Procedure In the two schools in U.S., questionnaires, cover letters, and empty legal envelopes were sent out directly to adult students. Students who were voluntary to participate sealed and returned the questionnaires to researchers. In the university in China, all materials were faxed to a designated teacher who was in charge of printing, sending out, collecting and then faxing questionnaires back to U.S. for analysis. All questionnaires were kept in a locked filing cabinet during data collection process and once data analysis was completed, all questionnaires were destroyed by shredding.

3.5. Research Design In this research study, a descriptive and co-relational design method was used. The dependent variable includes students’ perceived learning styles and the independent variables include students’ characteristics including age, gender, and ethnic background. Correlations were run between students’ characteristics and their perceived learning styles.

4. Results The sample consists of 199 adult students from both U.S. and the People’s Republic of China. Of all the participants, 45.7% of them were female and 54.3% were male students. The age of different groups of participants was diverse. 47.7% of them were between 18-25 years old, 20.1% were between 26-35 years old, 13.1% of them were between 36-45 years old, 12.1% of them were between 46-55 years old and 7% of them were 56 years old or older. Among all the diversities of participants, 39.2% of the participants were Asian or Pacific Islanders, 0.5% were American Indians or Alaskan Natives, 17.1% were Blacks or non-Hispanics, 2.5% of them were Hispanics and 40.7% of them were White Non-Hispanics.

VAK learning style questions were divided into 12 questions on the questionnaire. Statistical Package for the Social Sciences (SPSS) was used to analyze the data. Pearson chi-squares analyzed three demographic areas including gender, age range, and ethnic background.

4.1. Visual Learning Style Students’ visual learning style was analyzed through question 1 to 4 in the section 2 of the survey. Question 1 asks whether students prefer reading rather than listening to teacher’s explanation. The sample indicated that 23.1% of female students (12.1% strongly agree and 11% agree) as opposed to 40.8% of male students (9.3% strongly agree and 31.5% agree) agree that they prefer reading instructions themselves. Chi-square analysis, X2(4, N = 199) =12.240, p = .016, suggests that there is significant relationship between students’ gender and their preference towards reading instructions. Regarding students’ age difference in their preference for reading instructions, though a potentially significant age difference was found, 2X (16, N=199) =28.963, p=.024, the sample was too small to uphold the validity of Chi Square analysis (44%of cells have expected count less than 5). No significant relationship was found between students’ ethnicity and their preference towards reading instructions.

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Question 2 asks whether students are good at visualizing what they are studying. No significant relationship was found among students of different gender and age in their strengths in visualizing. Though there is a potentially significant ethnic background difference [X2(16, N =199) =40.823, p = .001], the sample was too small to uphold the validity of Chi Square analysis (56%of cells have expected count less than 5).

Question 3 asks whether charts, diagrams, pictures, and maps help them understand. No significant was found among participants of different gender, age, or ethnicity. Question 4 asks whether they can remember things better by writing notes or keeping printed details. No significant difference was also found among the participants.

4.2. Auditory Learning Style Students’ auditory learning style was demonstrated through questions 5 to 8 in the section 2 of the survey. Question 5 asks whether their first memory is of being spoken to. As indicated in the sample, there is no significant relationship between students’ gender and their first memory [(X2(4, N=199) =2.845, p=.584]. No significant difference was found in the subsequent two other variables (age and ethnicity).

Question 6 asks whether they would ask people than reading a map when trying to find a location. As indicated in the sample, there is significant relationship between students’ gender and their preference for asking rather than reading for help when trying to find a location 2 [(X (4, N=199) =9.845, p=.043]. The sample indicated that 49.5% of female students (19.8% strongly agree and 29.7% agree) as opposed to 30.9% of male students (7.5% strongly agree and 23.4% agree) agree that would rather ask people than read a map when trying to find a location. Regarding the age difference, though there is a potentially significant age difference [X2(16, N=199) = 31.877, p=. 010], the sample was too small to uphold the validity of Chi Square analysis (44%of cells have expected count less than 5). No significant was found among students of different ethnicity in their preference.

Question 7 asks whether they prefer reading aloud in order to better memorize notes. As indicated in the sample, there is a significant relationship between students’ gender and their preference for reading aloud to better memorize [X2(4, N=199) =10.458, p=.033]. The sample indicated that 55% of female students (13.2% strongly agree and 41.8% agree) as opposed to 36.1% of male students (11.1% strongly agree and 25% agree) agree that they prefer reading aloud to better memorize notes. No significant difference was found among students of different age or ethnicity. Question 8 asks whether they will evaluate all possible solutions before acting and no significant difference was found among three variables.

4.3. Kinesthetic Learning Style Students’ kinesthetic learning style was indicated through question 9 to 12 in the section 2 of the survey. Question 9 asks whether they will take notes to better comprehend. Though there is a potentially significant gender difference [X2(4, N=199) =13.123, p=.011], the sample was too small to uphold the validity of Chi Square analysis (20%of cells have expected count less than 5). No significant difference was found among students of different age or ethnicity. Question 10 asks whether they would job down several times in order to learn something new. No significant difference was found among the three variables.

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Question 11 asks whether they would prefer demonstrate by doing instead of oral explanation. Though there is a potentially significant gender difference [X2(4, N=199) =13.204, p=.010], the sample was too small to uphold the validity of Chi Square analysis (20%of cells have expected count less than 5). Besides that, no significant relationship was found between students’ age and their preference to demonstrate by doing rather than oral explanation [X2(16, N=199) = 16.817, p=. 398]. Though there is a potentially significant ethnic background difference [X2(16, N =199) 54.046, p = .000], the sample was too small to uphold the validity of Chi Square analysis (56%of cells have expected count less than 5).

Question 12 asks whether students feel to move with music while listening. No significant difference was found among students of different gender and age and their preference to move with music while listening. Though there is a potentially significant ethnic background difference [X2(16, N =199) 28.009, p = .032], the sample was too small to uphold the validity of Chi Square analysis (56%of cells have expected count less than 5).

5. Discussion The purpose of this study was to find out relationship between an adult student’s gender, age, and ethnic background and their classroom learning profile. Students’ learning styles were measured by the VAK (Visual, Auditory and kinesthetic) model. Questions 1, 2, 3 and 4 represented the Visual aspect, as compared to questions 5, 6, 7 and 8 representing the Auditory aspect and questions 9, 10, 11, and 12 representing the Kinesthetic aspect.

In all the visual questions, only one insignificant relationship was found. More male (40.8%) than female (23.1%) students agree that they prefer reading instructions themselves rather than listening to the teachers’ explanations and this indicates that more male students have visual learning styles. Two significant relationships were found in the auditory aspect. More female students (49.5%), as opposed to 30.9% of male students agree that they would ask people than reading a map when trying to find a location. More female students (55%) agree that they would read aloud to themselves to better memorize when studying for an exam, as opposed to 36.1% male students who agree. Two statistics suggest that more female students have auditory learning styles.

In all the auditory questions, two significant differences were found regarding students’ gender. One significant difference was found between students’ gender and their preference for asking rather than reading for help when trying to find a location. The other significant difference was found between students’ gender and their preference for reading aloud to better memorize. In the meantime, a potentially significant difference was found between age and students’ preference to read a map when trying to find a location.

Among all the kinesthetic questions, two potentially significant relationships were found regarding gender. One significant relationship was found between students’ gender and their better comprehension as a result of taking notes in class. More female students (89%) would agree they comprehend better by taking notes as opposed to 68.5% of male students who agree. In another potentially significant relationship, more male students (73.1%), as opposed to 66% of female

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students would agree that would demonstrate by doing. The above two potentially significant relationship might suggest that male and female students are equal in choosing their kinesthetic learning styles.

At the same time, some other potentially significant relationships were also found though they are not statistically significant in this research. The relationship between students’ age and their preference towards reading instructions rather than listening suggests that with the growth of age, people generally tend to prefer reading instructions by themselves, except for a decrease at the age group of 56+ years and this might be because of their sight problem when getting old.

Little difference was found in students’ ethnic differences. The potentially significant relationship between students’ ethnicity and their strengths in visualizing indicates that students’ ethnicity has little relationship with their strengths in visualizing (66.7% Asian/Pacific Islanders agree, as opposed to 61.8% Black/non-Hispanic and 76.6% White non-Hispanic who agree). Though 100% of American Indians or Alaskan Natives agree, there is only one participant so the data is not comparably significant. Little difference was also found between students’ ethnicities and their preference to demonstrate by doing rather than oral explanation. Same slight difference was again found between students’ ethnicity and their preference to move with music while listening. The above statistics might suggest that people’s learning styles and habits have less relationship with their ethnicities.

Above all, this research suggests that female students prefer auditory learning while male students prefer visual learning style. Little difference was found between gender and students’ kinesthetic learning styles. At the same time, this research also indicates that ethnicities have little influences on people’s learning styles.

For future researchers who want to find out the relationship between learning styles and students’ characteristics, translated questionnaires should be provided to participants if research is conducted in many countries with different language spoken. In this research, though questionnaire was written in simple English language and Chinese participants have been learning English for more than 8 years, English language may still hinder some participants to provide authentic responses.

References Anderson, J.A., & Adams, M. (1992).Acknowledging the learning styles of diverse student populations: Implications for instructional design. In L. L. Border & N. V.Chism (Eds.), New Directions for Teaching and Learning (pp. 19-33). San Francisco: Jossey-Bass Publishers, Inc. Andrews, J. D. W. (1981). Teaching format and students’ style: Their interactive effects on learning. Research in Higher Education, 14, 161-178. Aziz, Z., Yi, T. X., Alwi, S., & Jet, C. N. (2013). Learning style preferences of pharmacy students. The European Journal of Social and Behavioral Sciences, 4(1), 819-835. Bokhari, M. (2011).Learning styles and personality as factors affecting academic performance among students of different ethnicity: A case study. Journal of Human Capital Development, 4(1), 91-107. Bromley, D. B. (1958).Some effects of age on short-term learning and remembering.Journal of

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Gerontology, 13, 398-406. Dunn, R. (2001).Learning style: State of the science. Theory into Practice, 13(1), 10-19. Dunn, R. S., & Dunn, K. J. (1979). Learning styles/teaching styles: Should they...can they...be matched? Educational Leadership, 36(4), 238-244. Farwell, T. (1983).Visual, auditory, kinesthetic learners. Retrieved from:http://school. familyeducation.com/intelligence/teaching-methods/38519.html Felder, R. M., & Silverman, L. K. (1988).Learning and Teaching Styles in Engineering Education. Engr. Education, 78(7), 674–681. Freeman, C. E. (2004). Trends in educational equity of girls & women.DC: U.S. Government Printing Office. Guild, P.B., &Garger,S. (1985). Marching to differentdrummers.Alexandria, VA: Association for Supervision and Curriculum Development. Grasha, A. F. (1996). Teaching with style. Pittsburgh, PA: Alliance. Hulicka, I. M. (1965). Age differences for intentional and incidental learning and recall scores. Journal of the American Geriatrics Society, 13, 639–649. Huesmann, L. R., & Guerra, N. G. (1997).Children’s normative beliefs about aggression and aggressive behavior.Journal of personality and social psychology, 72(2), 408-419. Ibrahim, W., Morsi, R., & Tuttle, T. (2006). Concept Maps: An active learning and assessment tool in electrical and computer engineering. Proceedings of ASEE ’06: Illinois-Indiana and North Central Joint Section Conference. Fort Wayne, IN: ASEE. Kassaian, Z. (2007). Learning Styles and Lexical Presentation Modes.ELIA, 7, 23-78. Keenan, K., & Shaw, D. (1997). Developmental and social influences onyoung girls’ early problem behavior. Psychological Bulletin, 121, 95-113. Lam-Phoon, S. (1986).A comparative study of the learning styles of Southeast Asian and American Caucasian college students on two Seventh - day Adventist campuses (Unpublished doctoral dissertation).Andrews University, Berrien Springs, MI. Matthews, D. B. (1995). An investigation of the learning styles of students at selected postsecondary and secondary institutions in South Carolina. Research Bulletin, 60, 1-151. Miller, W. R., & Rose, H. C. (1975).Instructors and their jobs. Chicago: American Technical Society. Mortenson, T. (2001). College participation by gender age 18 to 24. Postsecondary Education Opportunity, 109, 1967-2000. Peng, L. L. (2002). Applying learning style in instructional strategies.CDTL Brief, 5 (7), 1-8. Sharp, J. G., Byrne, J., &Bowker, R. (2007).The trouble with VAK.Educational Futures, 1, 76-93. Sissons, P. (2007). Learning styles and strategies: the importance of learning styles for adult Students. Retrieved from: http://continuingeducation.suite101.com/article.cfm/kdjfeifjes Severiens, S., & Ten, D. G. (1998). A multilevel meta-analysis of gender differences in learning orientations.British Journal of Educational Psychology, 68(4), 595-608. Zina, O. (2004). Essential guide to doing research. Thousand Oaks, CA: SAGE. Zoccoiillo, M. (1993). Gender and the development of conduct disorder. Development and Psychopathology, 5, 65-78.

270 EITT 2013, Williamsburg, VA, USA, November, 2013 Huo, J. (2013). Assessing the primary and secondary school PE teachers’ educational technology abilities. Proceedings of International Conference of Educational Innovation through Technology, 271-273.

Assessing the Primary and Secondary School PE Teachers’ Educational Technology Abilities

Jin Huo Inner Mongolia Normal University Email: [email protected]

Abstract: As information technology in education and new curriculum innovation are further implemented in classroom, primary and secondary school physical education (PE) teachers are also required to integrate technologies into their curricular. By utilizing emerging technologies, PE teachers should be able to create and develop a pleasant learning environment for students, which will motivate students’ learning interests, improve teaching efficiency, and provide a solid foundation for students understanding on the content. The purpose of this article is to discuss the assessment of PE teachers’ technology proficiency through the Primary and Secondary School PE Teachers’ Educational Technology Proficiency Test in Inner Mongolia Autonomous Region in China, investigate current situation and challenges of the primary and secondary PE teachers, and provide recommendations for school administrators.

Keywords: physical education (PE), instructional technology, proficiency test, assessment

1. Introduction With the implementation of information technology in education, there are increasingly higher requirements on the qualifications for the primary and secondary school teachers in physical education (PE). In 2004, the Chinese Ministry of Education launched the National Primary and Secondary School Teachers’ Educational Technology Ability Construction Projects, aimed at improving the primary and secondary school PE teachers ‘performances by adopting educational technology skills in curricular. By integrating instructional technology into physical education, this project motivates the professional development of PE teachers, provides advanced teaching models, and eliminates the deficiencies in traditional teaching environment. Besides, it combines the traditional physical teaching media with advanced teaching media, and increases interactions between the teachers and students.

Facing the changes in teaching and learning theories, the contents of physical education, teaching methodologies, and teaching models as well as changes in evaluation, PE teachers should improve their overall performances in teaching process with the help of instructional technology. PE teachers should utilize technology skills effectively and efficiently to create and develop a pleasant and active learning environment, which motivates students’ learning interests, improves instructor’s teaching efficiency, and provides a solid foundation for students’ knowledge development.

Therefore, it is necessary to assess the abilities of primary and secondary school PE teachers’ instructional technology to decide what to do next. As a result, the Primary and Secondary School

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PE Teachers’ Educational Technology Proficiency Test was created and used in the past few years to evaluate teachers’ abilities in using educational technology in their classrooms.

2. Inner Mongolia Autonomous Region Primary and Secondary School PE Teachers’ Educational Technology Proficiency Test Along with the current reforms in school sports and sports teaching system, it is necessary to follow the principles of system, model, and setting of physical education and catch up on the trend of integrating educational technology into PE courses in primary and secondary schools. Meanwhile, educational technology literacy should also be in a harmonious relationship with sports courses to achieve greater effects. Therefore, PE teachers should adopt instructional technology skills reasonably in their curricular, guided by the national educational technology standards and their teaching objectives.

Educational technology proficiency test for the primary and secondary school PE teachers in Inner Mongolia Autonomous Region is not only used for assessing PE teachers’ technology abilities but also used for guiding them in their teaching practices. It focuses on the application of educational technology in sports teaching process, aims at efficiently completing teaching tasks, and provides evidence of instructional technology successfully integrated into physical education. With this proficiency test, we will clearly understand the current level of primary and secondary school PE teachers’ educational technology abilities, the challenges they are faced with, and how to help them overcome these challenges. The following sample proficiency test will be used to demonstrate how it is used to examine PE teachers’ technology abilities and how it guides their teaching.

3. Sample Test and Test Analysis The sample test is derived from the unit Full 50 Meters, in the standard curriculum experiment textbook Primary School Sports for third grade (level 2), which examines PE teachers’ abilities to integrate educational technology into their teaching plan through a real lesson plan. The three components of the test: course design, course implementation, and course evaluation, will be discussed in the following sections.

3.1. Course Design The first part of the test is course design, which includes five questions covering the steps for getting to know the students, content, and learning environment, setting goals and objectives, and designing class activities, teaching strategies, and evaluation strategies. Question 1 focuses on how to evaluate students’ background knowledge and their technology skills. Questions 2 asks about how to set learning objectives based on the learning goals; teachers should consider the learning environment and resources available such as multimedia classroom, gym, textbook, and multimedia equipment. The remaining questions describe the teaching steps. Question 3 asks teachers to demonstrate how they choose an appropriate video clip to show the knowledge to be taught and then ask students to practice what was taught. Question 4 asks about the strategies a teacher can use to assess student learning outcomes such as group discussion, practice in the gym, and observations. Question 5 asks how a teacher can summarize and review what was taught and provide extra activities if necessary.

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Through the process of identifying of teaching goals and strategies, PE teachers obtain a comprehensive understanding of students’ background, characteristics, physical and mental health situations, and their previous knowledge of Full 50meters. This understanding will facilitate the implementation of teaching activities. In addition, PE teachers are able to identify the teaching environment and resources in the teaching process, which includes multimedia network classroom, the playground, nine-year compulsory education textbook, video recorders, and video resources.

3.2. Course Implementation After the course is designed, teachers will implement the lesson plan in a classroom. During the classroom teaching, teachers may encounter various problems such as where to locate the multimedia resources, if the necessary hardware and software are available, whether the activity can be completed within the timeline and so on. Question 6 asks a specific technical problem a teacher may encounter when playing video on the computer. Question 7 shows a few mistakes that could arise when using multimedia in class and asks teachers to recognize them. Question 8 explains that PE teachers should play and playback the specific videos for students. When playing videos, teachers should provide instant guidance, explanations, and inspirations for students; they should also limit and control the rational of videos in classroom to train students with their cognitive skills.

3.3. Teaching Assessment After defining the teaching objectives, preparing the teaching resources, and implementing the course, comes the evaluation phase, which is the teaching assessment of the entire teaching activity. The assessment of the entire teaching process evaluates the efficiency and effectiveness of the integration of instructional technology skills into physical education. Question 9 to Question 11 help PE teachers find out and analyze the problems existing in their teaching process, and provide instant guidance for evaluation. Formative assessment and summative assessment will be applied to obtain an accurate evaluation of the integration. PE teachers should be able to explain and demonstrate the required sporting skills on-site; they should also use theory test to observe and evaluate students’ learning processes and results. With formative assessment and summative assessment, PE teachers can acquire a comprehensive understanding of their students’ performances, and modify their teaching objectives and strategies as necessary.

The process of planning, implementing, and evaluating teaching with instructional technology skills in physical education clarifies the process of PE teaching, reflects the characteristics of courses, and facilitates the integration of instructional technology skills in physical education, which results in teaching with higher efficiency and more effectiveness. In addition, the appropriate integration of teaching skills helps learners obtain a proficiency in sporting skills. With the assessment of teaching process, it motivates learners’ learning interest, triggers their potential in sports, and helps students form healthy physical and psychological habits.

4. Current Situation of PE Teachers in Technology Integration Currently, the twelve unions in Inner Mongolia Autonomous Region have formed a normative system of training, testing, and evaluating primary and secondary school PE teachers’ educational technology abilities. Only by passing the Primary and Secondary School PE Teachers’ Educational Technology Proficiency Test, can PE teachers be eligible to get professional promotions. Teachers

EITT 2013, Williamsburg, VA, USA, November, 2013 273 Proceedings of International Conference of Educational Innovation through Technology are allowed to retake the test if they did not pass it the first time. Data shows that 70% of the participants pass the test, which means that most PE teachers have been integrating or at least understand how to integrate educational technologies into PE classes. However, the real situation is not quite the same as what was expected. Quite a number of PE teachers who passed the test do not apply the instructional technology skills to their classroom teaching; they are still using the traditional teaching methods. Therefore, there is a disconnection between the proficiency test and classroom teaching, which might be caused by different reasons. Some PE teachers are so used to their previous teaching methodologies, they refused to make any changes; whereas, some teachers want to change but have limited hardware or software to support the application of technological skills in teaching. Some schools have all the necessary hardware and software but encounter many technical problems when using them in class. Without support from the school district, it would be difficult for PE teachers to apply their educational technology skills toothed physical education field.

5. Recommendations and Conclusion Based on the current situation of integrating instructional technology skills into physical education, the author suggests that a classroom observation and student survey should be conducted along with the proficiency test to determine how a PE teacher utilizes instructional technologies in the curriculum. The proficiency tests reveal the level of understanding of technology integration of a PE teacher; classroom observations show how the teacher implements it in his or her teaching plan; and student surveys tell about the effectiveness of the teaching results after integrating technologies into the classroom. For the hardware and software problems, schools will need special budget for purchasing the necessary hardware and software for PE teachers. In addition, schools should assign special technicians for PE teachers so that they can get immediate support when they encounter technical problems.

Instructional technology plays an important role in design, development, utilization, management, and evaluation of PE teaching and learning. It influences the innovations and developments in physical education. The interactions between instructional technology and physical education highlight the modernization of physical education in the future. It is necessary for PE teachers to explore the best ways to integrate instructional technology into the curricular, have a better understanding of the current situations, create effective incentive mechanism, and implement sustainable development in education.

274 EITT 2013, Williamsburg, VA, USA, November, 2013 Li, C. & Ma, J. (2013).Research on optimization of online education service based on analysis of visiting data to LMS. Proceedings of International Conference of Educational Innovation through Technology, 275-278.

Research on Optimization of Online Education Service based on Analysis of Visiting Data to LMS

Caiqiang Li, Junming Ma Southwest University Email: [email protected]; [email protected]

Abstract: The paper analyses the current conditions of online education services, and points out 3 shortcomings of the online education services: weak personalization, adjusting slowly to service policy, mono-source during policy making. The paper proposes a model named MOOESBAVDLMS to solve these problems.

Keywords: online education service, optimization, web analysis, LMS

1. Introduction With the rapid development of online education, China currently has 69 colleges and universities engaged in online education. Online students in 2011 were up to 4,924,833 people (Ministry of Education, P.R.C., 2011). Online education itself is not only a personalized educational process, but also a personalized service process. Service awareness should always exist throughout the process of teaching and learning. Personalized service covers both an individual learner and a particular group of learners of the same kind (Dong, 2002). Online education grows from platform- centeredness to resource-centeredness, and then to service-centeredness now (Chen, 2005). Education services are becoming increasingly important. Online education agencies have been investing more effort to improve education services.

Online education services includes services provided to students, services to teachers, and services to administrators of all levels. This study mainly explores the educational services for students. Currently online educational institutions mainly provide to students such services as high- quality curriculum resources, unobstructed network access and timely solutions to problems.

2. Shortcomings of Current Online Education Service Currently online education services provided by online educational institutions is formulated before an academic year or a term, and implemented during the semester, like providing teaching resources, arrange online students answering service, increasing functions of teaching system. The services mostly are formulated once-for-all, which leads to the following problems when implemented over a longer period of time:

2.1. Weak Personalization Students from different regions use the same service model, or students of different majors use the same model regardless of different learning levels and learning needs. Learners from the eastern regions like Shanghai, and learners from the western regions like Xinjiang use the same model though they may have different needs in learning time and forms. It also holds true for learners of different majors, such as math major and English language major, for they may differ in the presentation of resources and learning styles.

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2.2. Slow at Service Strategy Adjustment Once the rules of online education services are laid down, they are often in effect for a term, a year or even longer. If problems occur in the process, the formulation will not change until next formulation of education services. Service strategy is slow at adjustment, which can hardly meet user demand for services.

2.3. Single Service Policy Makers Educational services are often formulated on the basis of ideas of the administrators or questionnaires, taking no account of data of users’ visiting and using the services.

The problems of online education services mentioned above are created by untimely adaptation according to the data from learners. To solve these problems, the paper proposes a Model of Optimization of Online Education Service Based on the Analysis of Visiting Data to the LMS (MOOESBAVDLMS).

3. MOOESBAVDLMS The following is a structure of MOOESBAVDLMS:

Students Teachers

visiting Tracking Analytical Tools LMS (Google Analytics, CNZZ,… )

Optimization Traffic Content Audience … Administrator resource

Behavior Site Landing … Location Technology … SEO … flow content page

Figure 1. MOOESBAVDLMS The administrator uses web analytical tools such as Google Analytics (http://www.google.com/ analytics) and CNZZ (http://www.cnzz.com) etc. in MOOESBAVDLMS by inserting in the LMS website pages user access tracking codes to record the user’s use of online education services. These tracking codes will run automatically and quietly when students or teachers visit the LMS.

With the continuous run of these tracking codes, the administrator can obtain the information about content, audience, traffic resource at any time. For example, the administrator will get the visitor’s behavior flow information in terms of content— what is visited first, and what is visited later. Such information is very useful to analyze and optimize of study flow. Information like what resources are visited frequently and what resources are visited seldom can also be acquired through web analytics for content, and it will be beneficial to organize and optimize of resources. The geographic information and browser information of visitors can be easily obtained with web analytics of audience, and the LMS can provide more personalized service to the visitors accordingly. The analytical results of traffic resource will benefit network optimization, too.

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4. Practice 4.1. The Modification of LMS: An Example of Google Analytics Google Analytics is considered as a very useful and convenient tool for web analysis (Bhatnagar, 2009; Hasan, Morris, & Probets, 2009; Plaza, 2009, 2011). After a certain number of users visit the Google analytics code embedded LMS, online education administrators can view statistics of various kinds. Figure 2 below presents Pageviews, Unique pageviews and pageviews of the top WebPages. The pageview data shows the number of pages visited by users. If the pageviews of certain courses or the pageviews of certain chapters of a course are too low, the administrators can ask the resource developers to find out the reasons. Is the presentation of resources unreasonable? Or is the navigation of resources unreasonable, etc. Thus administrators can accordingly analyze the underlined reasons and make modifications. So the resources service can be updated and optimized quickly.

Figure 2. Google analytics page

4.2. The Modification of LMS: An Example of CNZZ

Figure 3. CNZZ page

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CNZZ is one of popular web analytical tools in China. After tracking code is embedded in the LMS for a period of time, we can view by means of CNZZ the data like the features of users’ access features. The Figure 3 above shows the approximate proportion of major network carriers used by users. Online education administrators can thus adapt their network access services, and ensure users’ quick access to the LMS.

5. Conclusion Web analytics statistics collect data and analyze them simultaneously when users visit the system. Therefore, managers can get the first-hand data of web analysis and optimize the LMS immediately. Data from web analytics can display the regional distribution of users. The services provided can be personalized according to the number of users in different regions and their habits of visiting the system. The analysis of web data and data from questionnaire can help in service policy making. Thus the problems of slowness at service strategy adjustment, weak personalization and single service policy maker are solved.

References Bhatnagar, A. (2009). Web analytics for business intelligence beyond hits and sessions. Online, 33(6), 32–35. Chen, Q. (2005). Service consciousness of online education. China education info, (7), 65-67. Cui, M., Sun, L. D., etal. (2011). Basic tutorial of web analytics: Secret of flow and value. Beijing: Posts & telecom press. Dong, X. D. (2002). Research on online education service. E-education Research, 115(11), 34-37. Hasan, L., Morris, A., & Probets, S. (2009). Using Google analytics to evaluate the usability of e-commerce sites. IN: Kurosu, M. (ed.). Human Centered Design, HCII 2009, Lecture Notes in Computer Science, (5619), 697–706. Ministry of Education, P.R.C.. (2011). Students of formal education of all types and levels. Retrieved from http://www.moe.edu.cn/publicfiles/business/htmlfiles/moe/s7382/201305/152564.html. Park, J., Kim, J. & Koh, J. (2010). Determinants of continuous usage intention in web analytics services. Electronic Commerce Research and Applications, (9), 61-72. Plaza, B. (2009). Monitoring web traffic source effectiveness with Google Analytics: An experiment with time series. Aslib Proceedings, 61(5), 474–482. Plaza, B. (2011). Google analytics for measuring website performance. Tourism Management, 32(3), 477–481. Wei, S. P. (2013). Learning analytics: mining the value of education data under the big data era. Modern educational technology, 23(2), 5-11. Zhu, Z. T., Shen, D. M. (2013). Learning analytics: Scientific power of intelligent education. E-education research, (9), 5-12.

Acknowledgements The research is supported by “the Fundamental Research Funds for the Central Universities” (No: XDJK2012C030) and Social Science Project of Southwest University (SWU06112).

278 EITT 2013, Williamsburg, VA, USA, November, 2013 Li, X., Liu, L., & Zhao, Z. (2013). The joint live global classroom by the American Alliance for International Education and the University of Science & Technology Beijing. Proceedings of International Conference of Educational Innovation through Technology, 279-282.

The Joint Live Global Classroom by the American Alliance for International Education and the University of Science & Technology Beijing

Xinxin Li, Li Liu, Zhiyi Zhao University of Science and Technology Beijing Email: [email protected]; [email protected]; [email protected]

Abstract: Although it has always been a challenge for instructors and students from different countries and regions to experience live teaching and learning, the trend of globalization in the field of education makes it possible with the use of internet technology. Internationalized e-learning is expected to lead the trend of distance learning, not only in language learning but also in engineer educating in China. This paper provides an example of the live global classroom conducted jointly by the American Alliance for International Education and the University of Science and Technology Beijing, which was aimed at educating undergraduate engineering students over the Internet.

Keywords: Live Global Classroom, AAFIE, Internationalized e-Learning, distance learning

1. Introduction Beginning on Sept. 1 2012, a live global classroom was conducted jointly by the American Alliance for International Education (AAFIE) and the University of Science and Technology Bei- jing (USTB). The class was conducted online and combined two classrooms with a total of 93 students. The online class was offered as an optional major course for undergraduate engineering students who were studying under the “Plan for Training and Educating Outstanding Engineers” in China.

2. Why the Live Global Classroom Is Needed at USTB? 2.1. The Plan for Educating and Training Engineers USTB, as one of the first 61 universities that were chosen to undertake “Plan for Educating and Training Engineers” (2010-2020) issued by the Chinese Ministry of Education in 2010, attaches great importance to the internationalization of their school. USTB is leading its internationalization efforts with its engineering schools, which have long been its strength. In addition, USTB established a brand new school named the “School of Advanced Engineering” (SAE) to educate students under the Plan with flexible curriculums intended for adaptation to international standards.

There were 512 undergraduate engineering students studying at the SAE in spring semester of 2013. It is difficult to offer internationalized engineering courses for these students on a large scale. One reason for this is that the engineering courses need to last the whole semester instead of the length of a simple seminar or lecture. The other reason is that the courses need instructors to have ample experience in the industry and a firm understanding of international practices and standards. Since the foreign teachers at USTB are mostly language teachers, and full-time engineering professors who meet the aforementioned requirements rarely have time to teach for a whole semester, there is an obvious need for a new model of teaching that will benefit both USTB and the instructors.

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2.2. American Alliance for International Education The American Alliance for International Education (AAFIE) attracted USTB’s attention with its strong background and diverse array of approaches to international education, many of which meet the international standards required for the education of engineering students: AAFIE is an organization to bring together educators, schools, colleges, universities, and corporations in the United States to develop sustainable, collaborative, international education programs to meet the challenges of globalization. (http://www.aafie.org)

2.3. Global Cooperation Based on the philosophy of the above two paragraphs, the “AAFIE-USTB International Engineering Education Center” was established at USTB in June 2012 and the first joint course, titled “Fundamentals of International Engineering”, was correspondingly opened. The students who took the course were from the SAE and majored in mining, metallurgy, materials forming and processing as well as mechanics. The course was taught by senior engineers from the United States who works with AAFIE. The objectives were to allow USTB students to gain a better understanding of global issues and skills, by focusing on such topics as global perspectives, intercultural communication, intercultural collaboration, critical thinking, creative thinking as well as giving the students first-hand experience interacting with professionals. With the courses being offered online, the American instructors were able to remain in the US, while teaching students in China, and have their Chinese classes run just as they would in their classrooms at home.

3. Technical Requirements The global classroom environment was comprised of 1 computer, 1 video camera (webcam), 1 set of wireless microphones, 1 speaker and 1 projector (with a white screen). Cable network is preferred.

4. Organizational Challenges

4.1. Time Difference Since there is an approximate 12-hour time difference between Beijing and the time zones of the American instructors, the most sought-after time periods were morning classes that ranged from 9:50am to 11:25am in Beijing.

4.2. Role of the Facilitators There was 1 full-time SAE staff and 2 part-time masters’ students who were prepared to assist the American instructors before, during and after the sessions. The roles of the facilitators were as follows:

4.2.1. Classroom preparation. Normally the virtual classroom opened 30 minutes before the beginning of the session for preparation and testing purposes. Facilitators needed to enter the virtual classroom through the link offered by AAFIE and make sure that everything was ready.

4.2.2. Classroom assistance. Firstly, facilitators needed to check class attendance and fill out attendance sheets. Since the instructor could not physically interact with the students, the facilitators acted as very important link in ensuring smooth communication was carried out.

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Secondly, facilitators needed to help the instructor by organizing quizzes, sending the scanned copies of completed quizzes back to the instructor for marking and then collecting the grades for final evaluation.

4.2.3. Final exam organization. Normally, the final exams in China are closed book exams. However, the instructors of the live global classroom adopted an impromptu group design model for the finals based on the students’ project requirements and their course knowledge. The facilitators needed to prepare all of the materials for the final exam according to the instructor’s requirements and distribute them to the students during the exam. Moreover, they needed to organize the instructions for the groups, arrange the group presentations for the instructor and the class and to record the final exam with cameras. Finally, they needed to send all of the scanned papers, pictures and videos to the instructor to judge for the students’ final marks.

5. Culture Impact 5.1. Different Teaching and Learning Methods Although the huge difference between Chinese and American teaching methods was well known before the class began, certain cultural obstacles did have to be overcome at first in order to have both the teacher and the students to interact comfortably.

5.1.1. Silence vs. free interruption. Chinese students are used to keeping silent at class and allowing teachers to speak most of the time. They are not expected to interrupt the teacher because it is considered a sign of disrespect for teachers. On the contrary, American instructors encourage students to interact with them and rise up to interrupt at any time during the class. Therefore, it was very interesting to find that when instructors first asked for questions there was always silence, despite students having many questions that they would end up asking after class. Since the instructor could only communicate with the students through teaching and answering questions, we found that this cultural difference was obtrusive to successful online live teaching.

5.1.2. Team work spirit. The spirit of teamwork has always been highly cherished by the American education system. Although Chinese education also encourages teamwork, it is seldom emphasized during study and homework and instead during activities and other exercises. American instructors required the students to study and finish homework in groups, which presented a new challenge for the class. Students often needed to make presentations to the class and make group presentations and dissertations for their final exam.The camera and speakers helped the instructor to see and hear live performances of the class and the instructor gave their feedback and comments right away.

5.2. Feedback During the semester, USTB distributed a questionnaire for the online engineering course. 14 questionnaires were answered and returned.

Most of the students successfully completed the instructor’s online course and gave positive feedback on their experience. In order to have more of its students benefit from the online course, USTB will continue to offer the course and produce research on the results of the live global classroom.

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References Some Suggestions by the Ministry of Education on the Implementation of the Plan of Training and Educating Outstanding Engineers. Retrieved from http://www.moe.gov.cn/publicfiles / business/htmlfiles/moe/s3860/201102/115066.html American Alliance for International Education, Mission Statement about AAFIE. Retrieved from http://www.aafie.org/about/org/2011/0927/27.html

Acknowledgements This study would not have been possible without the tremendous support we received from the many senior engineers and professionals who are with the American Alliance for International Education. Above all, our sincerest gratitude goes to G. Mark Stewart who has worked as the instructor of the live global classroom for two semesters, beginning on Sept. 1, 2012. We thank him for teaching 126 of our students at USTB during this time. In addition, we would like to thank Frank Zeng for his efforts acting as a liaison to bring AAFIE and USTB together to conduct this meaningful project. Our sincere thanks also go to Mike Armstrong who arranged the virtual classroom and the coordination for the instructors. The study would also not have been possible without the support of Prof. Xinxin Zhang, Prof. Li Liu, and Prof. Zhiyi Zhao who spared no efforts in pushing the project forward.

282 EITT 2013, Williamsburg, VA, USA, November, 2013 Meng, X., Wang, W., & Shi, L. (2013).Analyzing the distribution of e-learning resources in Chinese educational websites. Proceedings of International Conference of Educational Innovation through Technology, 283-294.

Analyzing the Distribution of E-learning Resources in Chinese Educational Websites

Xiangzeng Meng, Weina Wang, Lin Shi Shandong Normal University Email:{mxz,weina_wang,shilin}@sdnu.edu.cn

Abstract: The 474 Chinese educational websites ranking top base on their counts of visited times in the Chinarank website are classified in 14 types. The 167925 webpages or files linked or embedded in the 474 Chinese educational websites are extracted and analyzed to recognize e-learning resources from them. The e-learning resources recognized are counted up according to the types they are categorized into base on their main contents. The rate of 12 types of e-learning resources and their distributions on 14 types of the Chinese educational websites are shown respectively. The study showed that: the e-learning resources such as website, webpage, document, form, video, audio, slide show, program, compressed file are mainly imported as linking mode, and image, flash movie are mainly imported as embedding mode supplemented by linking mode, the proportion of e-learning resources in documents, forms, videos, audios, slide shows and compressed files is relatively higher, but it is very low in websites, webpages, images, flash movies and programs, the e-learning resource distribution is uneven in 14 types of the Chinese educational websites. There are less network courses and teaching cases, which we should pay attention to in construction of Chinese educational websites.

Keywords: e-learning, educational resource, Chinese educational website

1. Introduction In view of the vast information resources in Internet, how many e-learning resources there are? Where are e-learning resources? It is hard to answer these questions. A kind of natural viewpoint is that e-learning resources are most likely to exist in Chinese educational websites.

The e-learning resources construction is the basics of promoting education informatization, and its rich degree reflect the level of education informatization. In the past twenty years, a great importance is attached to the construction of e-learning resources in China, and a lot of manpower, materials and funds have been invested to carry out a variety of construction engineering of e-learning resources. A large number of e-leaning resources have been built. With the development and the popularization of Internet in China, many e-learning resources are put onto the Internet, and a huge distributed database of network e-learning resources is formed, which provides a great convenience for all of educators and students. However, how many e-learning resources in Internet are there, what form do they exist in, and how are they distributed on the types of Chinese educational websites? To answer these questions, we need to investigate and analyze various the e-learning resources in various types of Chinese educational websites. The answers of these questions are important to the construction, management and effective utilization of the network e-learning resources and environments.

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In fact, the number and distributions of information resources in Internet have always been the problems which the Internet management departments and the vast majority of Internet users concern. China Internet Information Center publishes every half a year the investigation results of information resources such as the number of domain names, websites, webpages, in the Statistical Report on Internet development in China. In the field of Internet advertising, Web Consulting companies home and abroad routinely provide reports and intelligences of online advertising market and the development trend of online ads to the advertisers and network users by using the network survey data. This plays an important role in the development of the network advertising market and the guiding of the network advertising. Similarly, in education as an important field of the application of Internet, the survey, the statistics, the distribution, the sharing and the application analysis of e-learning resources in Internet is an indispensable important work for the development and application of e-learning resources. In the paper, the number and distributions of e-learning resources linked or embedded in 14 types of Chinese educational websites are investigated, and the existing modes, the file types of e-learning resources in Internet and the distribution characteristics in 14 types of Chinese educational website are analyzed, which is helpful for the effective management and applications of the e-learning resources in Internet.

2. Review of Literatures Chinese and foreign scholars have done a lot of research in the construction, optimization, evaluation, sharing, and the application of the network e-learning resources. The author retrieved 14398 research papers published from 2001 to 2013 associated with the keyword “educational resource” or “instructional resource” or “e-learning resource” in title from CNKI, which shows that e-learning resource research is all the way one of the research hotspots in the field of e-education and from the time point of view the number of papers published is in growth trend. The articles also contain 525 papers with the keyword “current situation” or “investigation” in title. The research topics of the articles mainly focused on the investigation, existing circumstance and development trend analysis of e-learning resource construction, sharing and application effects in basic education, network curriculum, college or some subject areas, regional education, and so on. In the articles there are most subjective analysis, however objective investigation is less, especially rarely based on the analysis of a large sample survey. He K. K. (2009) has analyzed the present situation of e-learning resources in China, and proposed the corresponding countermeasure of construction of e-learning resources. Zhang Q., Chen L.(2011) investigated the constructors, service objects, subject distribution, application situation and teacher’s attitude to the basic educational and made attribution analysis by making a questionnaire of 290 primary and secondary school teachers and visiting 53 comprehensive or single basic Chinese educational websites. Li X., & Hu X. Y., & Miao R.(2009) made a survey of China’s basic education resources construction and application through a questionnaire survey of 720 principals, teachers and students of 18 primary and middle schools in China’s East, Middle, West, and found that the general situation of the construction of the basic educational resources in China is good. Huang Q. Z.(2010) investigated the application, attitude and influence factors of e-learning resources in campus network and analyzed the main factors affecting the application of e-learning resources through a survey of 424 college students by questionnaire. Meng X. Z.(2012) discussed initially the distribution of e-learning resources in the Chinese educational websites by investigating the existing forms and the file types of e-learning resources in Internet.

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The author retrieved 1149 research papers published from 2001 to 2012 associated with the keyword “educational resource” or “instructional resource” or “e-learning resource” in title from the Electronic Journal Full-text Database such as EBSCO, Taylor & Francis, and Springer. These articles are mainly focus on the construction and application of e-learning resources of discipline, curriculum or specific fields similar to the Chinese research, with a small amount of papers about the analysis and evaluation of the content and application of network e-learning resources. For example, Trey M., &Ward M. C., & Qian Y. F.(2005) analyzed the 11 category e-learning. Flora M. M., & Ellen I., & Alan W., etc.(2008) studied the application problem of network e-learning resources and digital library in the higher education through the survey of 4678 teaching staffs from 119 higher education institutions. Nowicki S.(2008) evaluated systematically the famous online learning and multimedia e-learning resources website MERLOT. However, there has no research papers about the analysis on distribution of e-learning resources in the retrieved documents.

3. Collection of E-Learning Resources in Chinese Educational Websites 3.1. The Type of e-Learning Resources E-learning resources are multimedia materials which are processed digitally, running in multimedia computer, spreading and sharing in the network. The construction of the e-learning resources is divided into four levels according to the “Technical Specification for Educational Resources Construction” (CELTS-41) issued by the China E-learning Technology Committee: (1) the construction of e-learning resources of material class. And it is mainly divided into eight types: media material, examination questions, examination paper, literature and document, courseware and network courseware, case, FAQ, directory and index; (2) the network curriculum construction; (3) evaluation of resource construction; (4) development of e-learning resources management system. Among them, network course and teaching resource construction of material class are the basis. According to this standard, e-learning resources are divided into 12 types as network curriculum, network courseware, courseware, image, video, audio, animation, literature, examination (question and paper), case, FAQ, index, in which the literature refers to all the literature and document which are relevant to e-learning, including teaching schedule, syllabus, tutorial, lesson plan, form, speech, learning summary, experience exchange, electronic books, academic paper, degree thesis, reports, conference proceedings, journal, standard, document, regulation, etc.

3.2. The File Types of e-Learning Resources The file types of e-learning resources in Internet mainly include: website, webpage, document, form, image, video, audio, animation, slide show, program, compressed file, database, virtual reality, etc. A website is the collection of webpages and other files used to show relevant information, therefore it combines all relevant files and webpages together according to certain rules. China Internet Network Information Center defines a website as a site with independent domain name, and the sites with relevant domain names are regarded as the channels of the main website which usually provide special information service, such as news, blog and video, etc. But many individual network users do not have independent web server and domain name, so they often rely on some free web servers or server folders to form their own small personal websites, such as personal blogs, forums, special websites, network courses, etc. Therefore, in the paper a website is defined as a folder including homgpage, webpages, other files and subfolders. A homepage is a special webpage file with the name index or default to identify the door of a website. All the files and

EITT 2013, Williamsburg, VA, USA, November, 2013 285 Proceedings of International Conference of Educational Innovation through Technology subfolders are considered as the contents of the website. So, if a webpage file with the name index or default is extracted from a webpage, the anchor is looked as a link to a website homepage and the folder is considered as the website’s content where the homepage file exists.

E-learning resources in Internet usually use a variety of file types. In this paper, the files are divided into 13 types, such as website, webpage, document, form, image, video, audio, animation, slide show, program, compressed file, database, Virtual reality, etc. Table 1 lists the file formats of 10 file types used commonly in Internet.

Table 1. File formats used commonly in Internet

3.3. Searching the files linked and embedded in Chinese educational websites In Internet, educational websites may contain more e-learning resources. The Chinese site ranking website (http://www.chinarank.org.cn) rank dynamically the Chinese websites visited most often based on the website’s network traffic for the comprehensive ranking and the ranking by category. These websites basically represent the most popular websites in their category. The files linked and embedded in the Chinese educational websites most often visited are searched and analyzed to recognize the e-learning resources, which is to show the features of distribution of e-learning resources in Chinese educational websites. 474 Chinese educational websites top ranked in the Chinese site ranking website are chosen and divided into 14 categories. 2702 relevant channel website addresses linked in the website homepages are extracted and combined with the home website address to construct a set of 3176 webpage addresses which are used as seed webpages for a resource searching program.

With the breadth first search strategy, layer by layer, the resource searching program begins from the seed webpages to counts all of files linked or embedded and to search the webpages with the same domain names with the seed webpages which are used as the wbpages to search in next layer when the URL of the webpage is different from the URLs searched. Until the third layer after

286 EITT 2013, Williamsburg, VA, USA, November, 2013 Analyzing the Distribution of E-learning Resources in Chinese Educational Websites the seed webpages 4865663 webpages are searched and 624196259 files are linked and 96235793 files are embedded. It may be calculated that 128 files are linked and 20 files are embedded in a webpage averagely. In the webpages, the website, webpage, document, table, slide show, program, compressed file is mainly imported by linking, in which the websites , webpages most account for 40.23% and 39.33%, followed by the documents, compressed files, respectively, 0.08% and 0.01%. The tables, audios, videos, slide shows, program files are less with low proportion. Images, animations are most directly embedded into the webpage, and there is a few part imported by linking, in which images most account for 70.21%, but animations accounted for only 0.45% in all the embedded files.

It is found that most of the files linked or embedded in the webpages are repetitive, some of them are not accessed. As an example, in China educational resource site 195726 independent webpages at all are searched in 12 layer traversal search in which there are 29754367 webpages linked containing 17515536 webpages linked in the same site. It is shown that only 1.12% of webpages linked is not duplicated. In addition, 988 of 195726 webpages are not accessed which account for 0.50%.

Table 2. Number and percentage of 11 types of files sampled

Notes: The type of educational website is 1: Instructional resource; 2:Higher education; 3:Courseware and paper; 4:Distance education; 5:Primary and secondary education; 6:Adult education; 7:Professional education; 8:Preprimary education; 9:Language education; 10:University and Institute; 11:Local education and organization; 12:Examination; 13:Training; 14:Others; 15:Total; 16:Percentage.

3.4. Exampling the Files to Recognize e-Learning Resources in Chinese Educational Websites As is shown in the above searching, there are 624196259 files linked and 96235793 files

EITT 2013, Williamsburg, VA, USA, November, 2013 287 Proceedings of International Conference of Educational Innovation through Technology embedded in the 5684862 webpages of 14 types of Chinese educational websites. How many e-learning resources are there in the files linked and embedded? Whether the file belongs to e-learning resources and which kind of e-learning resources it belongs to can be worked out by analyzing its contents. However, it is hard to judge the every file linked or embedded in the Chinese educational websites. Therefore, this paper adopts artificial analysis to carry out sampling analysis, identification and classification of statistics for these massive amounts of information. 129946 websites, webpages, documents, tables, video, audios, slide shows, programs, compressed files are extracted from 624196259 files linked and 37979 images and flash files are extracted from the 96235793 files embedded. There are 167925 samples in total. Table 2 shows the number and the percentage of 11 types of files sampled from 14 types of Chinese educational websites.

Table 3. Number and percentage of e-learning resources

Notes: The type of educational website is the same as in Table 2.

4. Analysis 4.1. Number and Proportion of e-Learning Resources in Chinese Educational Websites The file sampled is judged whether it is e-learning resources according to its main contents which presents by browsing or running playback, and if it belonging to e-learning resource it will be judged to which types of e-learning resources furthermore. Some types of e-learning resources have clear boundaries, such as exercise, test, teaching plan, courseware. But some are difficult to judge because they are e-learning resources in a broad sense but they do not belong to which types of specific learning resource in the narrow sense, such as news, reports, forums, ads, pictures, programs, etc. Therefore, the file is judged as an e-learning resource if the main content the file presents is itself some contents to learn or the file is correctly relation with some learning contents in the webpage, otherwise the file is judged as non learning resources (others). For example, the texts, documents, forms, pictures, video, audios, Flash movies, programs linked or embedded in a webpage which is itself learning content is judged as e-learning resources; the images, tables, Flash movies embedded or linked in learning content region of an educational webpage is judged as e-learning resources because it directly related to the learning content; the images, Flash ads

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embedded or linked in a non educational webpage or non learning content region in a educational webpage does not belong to e-learning resources. The introductions, news, reports, forums, ads, tables related to education, schools, training institutions are thought as e-learning resources in a broad sense and classified to the documents of e-learning resources. If a file contains more than one types of learning elements, such as webpage, documents or Flash, it will be classified according to the main learning content form. For example, the webpage, document or Flash whose main learning content form is image, video or audio it would be classified to image, video or audio of e-learning resources respectively. Table 3 lists the number and the percentage of 12 types of e-learning resources in 14 types of Chinese educational websites.

It is shown from table 3 that the total of 12 types of e-learning resources accounted for 79.23%, non learning resources and not accessed files account for 15.70% and 5.07% respectively. Among 12 types of e-learning resources, documents are the most accounting for 35.01%, which is due to that documents contain a wide range of e-learning resources, not only including the teaching outlines, teaching plans, courses of study, learning summaries, exchanges of learning experience, electronic books, papers, reports, files, laws and regulations, also including some broader documents, such as introductions, reports, forums, ads, forms, etc. related to education, school, training agencies which are referenced and helpful for e-learning. The second is the index of e-learning resources that accounts for 20.28%, which is due to that there are many webpages which contain mainly the index or directory of e-learning resource in Chinese educational websites. There are so many index of e-learning resource that many forms of navigation for e-learning resources are provided and the e-learning resources are searched expediently, but the confusions such as crossing links, excessive references for learning resources are caused. Too many directories or index of e-learning resource are actually redundant and interference information for learners. Strictly speaking, the directories or index of e-learning resources are just the navigation of e-learning resources rather than true e-learning resources. If the directories or index of e-learning resources are discarded, the remained 11 types of e-learning resources account for only 58.95% in the total of files exampled.

Figure 1. Percentage of e-learning resources

Figure 1 shows the proportion of e-learning resources: (a) the proportion of every type of e-learning resources in all files exampled; (b) the relative ratio of 12 types of e-learning resources; (c) the relative ratio 11 types of e-learning resources not including index. The index of e-learning resources accounts for 25.60% in 12 types of e-learning resources. Discarding the index, literature

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accounts for 59.39% in the 11 types of e-learning resource, however network course, network courseware, courseware, animation, case, and FAQ which the educators and learners may be most interested in, accounts for only 5.58% at all. Therefore the construction of network course, network courseware, courseware, teaching case, lesson plans, animation, etc. should be strengthened in the construction of e-learning resources.

4.2. Distribution of e-Learning Resources in 14 Types of Chinese Educational Websites Figure 2 shows the number of the files exampled in 14 types of Chinese educational websites and the number of e-learning resources recognized which contains (a) including index, and (b) not including index. Because there are evidently difference in the number of websites and webpages in 14 types of Chinese educational websites, the numbers of the files exampled from each type of Chinese educational websites are different. Therefore the distribution of e-learning resources in all types of Chinese educational websites is not reflected only on the quantity of e-learning resources. The proportion of e-learning resources in the total files exampled in the Chinese educational websites is used to show the distribution of e-learning resources in Chinese educational websites as shown in figure 3 in which (a) including index and (b) as for not including index.

Figure 2. Number of samples and e-learning resources in 14 types of Chinese educational websites (Notes: The type of educational website is the same as in Table 2)

As can be seen, if the index is accounted the average ratio of e-learning resources amounted to 79.23%. Under these circumstances, some Chinese educational websites such as e-learning resources, course thesis, distance education, adult education, occupation education, examination, provide more e-learning resources relatively, and other types of Chinese educational websites less. The proportion of e-learning resources in distance education websites is relatively small, the main reason of which is that this kind of commercialization websites contain usually a lot of advertising and other non learning resources in the webpage.

If the index is not taken into account, the average ratio of e-learning resources is only 58.94% and the proportion of e-learning resources in 14 types of Chinese educational websites changes obviously. Especially, because the e-learning resource, courseware, preschool education contain too much index or directory, the proportion of e-learning resources decreases significantly in the removal of index. Therefore, in the educational website construction the ads or non learning

290 EITT 2013, Williamsburg, VA, USA, November, 2013 Analyzing the Distribution of E-learning Resources in Chinese Educational Websites resources are minimized and the number of index or directory navigation webpages is appropriate so as to avoid excessive interference or complex navigation directory.

Figure 3. Ratios of e-learning resources in 14 types of Chinese educational websites (Notes: The type of educational website is the same as in Table 2)

Table 4. Number and ratio of e-learning resources in 11 types of files

4.3. Ratio of e-Learning Resources in 11 Types of Files The network information resources are stored as files, so it is relatively simple to manage a large amount of network information resources according to the file types. However, from the user’s perspective, the people want usually to manage the information resources according to their contents. For example, if the e-learning resources are classified to manage, search by type, the users are very easy to find the e-learning resources that they want according to the classification of e-learning resources. Are there some relation between the file types and the types of e-learning

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resources? The answer should be yes. It is very hard to recognize all the e-learning resources from the massive distributed files linked and embedded in webpages of the Chinese educational websites and to classify them accurately base on their contents, because the workload of artificial recognition and classification is huge and almost impossible, and on the other hand it is difficult to ensure the accuracy of automatic recognition and classification by using the computer. Therefore, it is very helpful to searching for specific content of e-learning resources restricted to some file type is of great help find the most common file types used in every type of e-learning resources. Table 4 lists the statistics of the 11 file types used in 12 types of e-learning resources.

Figure 4. Ratio of e-learning resources in 11 file types.

Figure 4 shows the proportion of e-learning resources in 11 file types, wherein (a) for containing index and (b) not containing index. As can be seen, the proportion of e-learning resources in document, form, video, audio, slide show, compressed file is higher, but the ratio of e-learning resources in program, website homepage is very low, only 3.24% and 4.18% respectively. Disregarding index, the ratio of e-learning resources in website homepage and webpage decreases significantly, which is due to the reason that homepage and webpage often contains many directories or index as the navigation of e-learning resources. The homepage is usually the navigation page of website; therefore it contains a lower proportion of pure learning resources than a common webpage. The programs linked in the webpage are mainly the software tools and a small part of them is courseware which are mainly the executable program generated by the PPT or Flash courseware.

According to table 4 we can see the common file types used in every type of e-learning resources in Chinese educational websites. At present, the network information usually searched by using the Internet search engines in which many types of information resources are searched according to the type of files. For example, in the famous Chinese search engine Baidu, webpages, images, videos, audios, documents are searched by file type, and the search of documents may be further constrained by the file format, doc, txt, PPT, pdf and xls. When we search some type of e-learning resources in Internet, we should selectively search the files with the file formats related to the

292 EITT 2013, Williamsburg, VA, USA, November, 2013 Analyzing the Distribution of E-learning Resources in Chinese Educational Websites type of e-learning resources, because the possibility of including e-learning resources in the files with related file format is larger. For example, to search multimedia courseware with thekey word “Pythagorean theorem”, we know that the common file types of multimedia courseware are Flash movie, slide show, compressed file and program according to table 4. We choose searching Flash movie, slide show, compressed file and program by the key words “Pythagorean theorem” rather than searching webpage, document, media material, in this way the possibility of finding “Pythagorean theorem” multimedia courseware is greatly improved. Therefore, it is to know the common file types of every type of e-learning resources very important to searching e-learning resources, which can greatly improve the search accuracy of e-learning resources in Internet.

5. Conclusion Ii is of positive significance to the construction, search and application of educational resources to find the characteristics of the common file types and distribution of e-learning resources in Internet. For example, in the construction of Chinese educational websites, e-learning resources should be imported with the most popular file types and formats, so that they are more easily searched for educators and learners. On the other hand, the search for some types of learning resources can be constrained in the related types of files by using file type or format options or parameters in some search engines, which will increase greatly the possibility of successfully searching e-learning resources and avoid the blindness search.

According to the file type and format, this paper conducts surveys by means of automatic search and classified statistic for the linked and embedded files in 471 Chinese educational websites which have the most visitor volume based on the Chinarank website. These websites basically represent the characteristics of all types of the current popular Chinese educational websites. Statistics and analysis of the linked and embedded of digital learning resources reflect the condition of digital learning resources included in the current Chinese educational websites. As is shown in the analysis, (1) the resources directory index and literature make up a large percentage of network digital learning resources, while the learning resources such as network curriculum, network courseware, courseware, animation and teaching plans which educators and learners may be most interested in is relatively less, so we should strengthen the development of this kind of learning resources in the network learning resource construction. (2) There contains more learning resources in educational resources, courseware paper, and distance education website, while it contains relatively less learning resources in early childhood education, local education, education organization and other education website. (3) From the file type, documents, form, sound, video, slide, compressed file contains more digital learning resources, while in program, image, website and webpage, the digital learning resources proportion is very low.

The deficiency of the paper lies in that the e-learning resources investigated as empirical research are selected only from the part of files linked and embedded in top visiting Chinese educational websites disregarding of the e-learning resources linked and embedded in script file, CSS file, and non Chinese educational websites. The number of the files exampled is relatively small. Therefore some sidedness inevitably exists in the statistical analysis of e-learning resources in Internet. It is the further work to expand the investigating scope of the files related to e-learning resources in various kinds of websites and webpages so as to excavate farthest the potential e-learning resources in Internet for teaching staff and learners.

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References Flora, M.M., Ellen, I., Alan, W., Joshua, M.l, Glenda, M., & Cathryn, M. (2008). The use of online digital resources and educational digital libraries in higher education. International Journal on Digital Libraries, 9(1), 65-79. He, K. K. (2009). Current situation and countermeasures of construction of digital learning resources in China. E-education Research, 198(10), 5-9. Huang, Q. Z. (2010). Investigation and analysis on the utilization status of the campus network e-learning resources in colleges and universities. China Educational Technology, 279(4), 75-80. Li, X., Hu, X.Y., & Miao, R. (2009). Investigation on construction and application of basic educational resources. China Educational Technology, 265(2), 55-58. Meng, X. Z. (2012). Investigation of e-learning resources in educational webs. Journal of distance education, 213(6),66-68. Nowicki, S. (2008). MERLOT: Multimedia educational resource for learning and online teaching. Current Reviews for Academic Libraries,19(6), 963-964 Trey, M., Ward, M.C., & Qian, Y.F.(2005). Analysis of recognized web-based educational resources. Computers in the Schools, 21(3), 101-117 Zhang,Q.,&Chen,L.(2011). Current situation study and attribution analysis of online education resources in basic education. China Educational Technology, 291(4), 77-81.

294 EITT 2013, Williamsburg, VA, USA, November, 2013 Mo, Y., Han. X.,& Liu, Y.(2013). Computer resources and science attitudes: the effects on eighth-grade science achievement. Proceedings of International Conference of Educational Innovation through Technology, 295-302.

Computer Resources and Science Attitudes: The Effects on Eighth-Grade Science Achievement

Yun Mo, Xibin Han, Yingqun Liu Tsinghua University Email: {yunmo, hanxb, liu-yq}@tsinghua.edu.cn

Abstract: This study focused on the relationships between schools’ computer resources, students’ science attitude, and science achievement in middle school level. It used the Trends in International Mathematics and Science Study (TIMSS) data which were analyzed via structural equation modeling. The study first investigated the effect of middle schools’ computer resources on students’ science attitudes and in sequence, on science achievement. Then, it examined the effect of science attitude on students’ achievement. The results found the importance of schools’ computer resources in students’ science attitude and achievement. The results also confirmed the significance of science attitude on science achievement. The study had both theoretical and practical significances, providing valuable insights for the pedagogy of middle school science.

Keywords: science attitude, computer resources, science achievement, middle school

1. Introduction Science achievement in middle school is of critical importance because it not only prepares students for future science course work but also fosters interest and aptitude to pursue science careers in the future. There is a persistent interest in educators, researchers and policy makers in understanding the determinants of science achievement. Past research on science achievement had focused on cognitive factors such as ability, IQ and other measures of innate aptitude. There is also a growing body of literature that examines the relationship of such psychological variables as motivation, science interest, science self concept and science self efficacy on science achievement among secondary students. Non-self factors, such as school/classroom resources, teachers’ instructions were also interested by educational researchers (Duschl, Shouse, & Schweingruber, 2007). But there is a dearth of studies that examine the relationship of classroom science the technology resources and science achievement. Given the huge variability in the technology resources among schools and differential opportunity students get to learn science, there is a need for more empirical studies that examine the role of classroom technology resources in science achievement. There are many differences in the quantity and quality of the technology resources schools provided to science teaching, such as the number of computers, software, and supporting staffs. The present research examined the relationship of science attitude and science achievement to classroom instructional technology resources. The following questions guided the study. The second and third research questions only will be investigated if the significant difference is found in the first research question. 1. Is there any difference in eighth grade science achievement between students who have and have not computers to use in science classroom? 2. What is the effect of classroom computer resources on students’ science attitudes and

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science achievement? 3. What is the relationship between science achievement and students’ science attitudes?

2. Literature Review For more than a decade, educators have emphasized the importance of science literacy (see American Association for the Advancement of Science 1989; National Research Council 1989). Large scale studies such as the National Assessment of Educational Progress (NAEP) and the Trends in International Mathematics and Science Study (TIMSS) have been made to investigate the national and international students’ knowledge and skills. These studies primarily focused on mathematics and science achievement and have collected data on various social, educational and school variables to better understand the relationship of these factors to student learning. Educators have drawn attention to the various factors that affect science achievement of students (Manning, 1998).

Recent research has found that science achievement is related to affective and motivational characteristics of individuals. Researchers have included a number of psychological processes that motivate individuals to engage in and persist in achievement related activities. Individuals’ task- related efficacy, interest and value of the activity all affect their desire and commitment to persist and engage in and put effort in learning activities. Research on science achievement is showing similar results; self-concept and motivational variables are shown to be important predictors of science achievement (Eccles, 1997; Nolen, 2003).

The effectiveness of computer resources in the academic achievement has been tested repeated, but the results are inconsistent. Wen, Barrow, and Alspaugh (2002) have found the quantity of computers significantly and positively affect on student achievement. Moreover, a one-to one laptop program sponsored by Hewlett-Packard was welcomed by students and teachers. “More than 80% of the school’s teachers report that computers are “very important” to them as a teaching tool and the great majority of students report that the laptops have a “very positive” (65%) or “somewhat positive” (29%) impact on how much they learn in school (Zucker, 2009, pp.18).” Most of the students in that program also reported that the computers positively influenced their relationship with classmates and their interests in learning (Zucker, 2009). However, no significant differences in achievement were found among four levels of computer availability groups in Alspaugh’s (1999) research. Future research is needed due to lack of consensus.

Research has shown that student psychological effects and school/classroom technology resources provide the links to increasing student achievement separately (Darling-Hammond, 1997). But only a few studies connect the self-concept, students’ classroom technology resources and their academic achievement together. Even less research is available focused on the study of factors that influence science psychological engagement. This research study presented a conceptual model of science achievement that includes science classroom technology resources and psychological factors in learning. The study also made methodological advances over previous work, using descriptive statistics and structural equation modeling.

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3. Methods 3.1. Data Sources This study uses the Trends in International Mathematics and Science Study (TIMSS) 2003 database. TIMSS is the largest international comparative study of mathematics and science achievement to date. It is a series of studies by the International Association for the Evaluation of Educational Achievement (IEA) to measure trends in students’ math and science achievement. TIMSS conducted on a four-year cycle, the first round of TIMSS was in 1995, the second in 1999, the third in 2003, and the fourth on 2007. For the results could be generalized to China, this study selects the 2003 wave as the computer penetration rate in China is far behind the United States.

3.2. Sample The international sample design for TIMSS is generally referred to as a two stage stratified cluster sample design. The first stage consists of a sample of schools; the second stage consists of a sample of one or more classrooms from the target grade in sampled schools (Martin, 2003). This data set is well suited for studying the relationship among constructs that indicate computer resources, science attitude and science achievement. First, TIMSS data provided a wide array of student level items on science attitude and science achievement. Second, TIMSS data provided teacher level and school level survey to measure school provided computer resources.

Since the United States has a long-term leadership in science and technology, US middle school data were selected for this research. In the United States, TIMSS is supported by the Education’s National Center for Education Statistics (NCES) and the National Science Foundation (NSF). It measured the mathematics and science achievement of fourth and eighth-grade students and collected extensive information from students, teachers, and school principals about mathematics and science curricula, instruction, home contexts, and school characteristics and policies.

The full data include six sections: 1) Students’ responses to each of the mathematics and science items administered in the study; 2) Student achievement scores in mathematics and science;3) Students’ responses to the student questionnaires; 4)Teachers’ responses to the teacher questionnaires; 5) Principals’ responses to the school questionnaires;6) National Research Coordinators’ responses to the curriculum questionnaires. Because this research is focused on US middle school science education, we only used the 8th grade students and science teachers’ questionnaire in the United States. There were a total of 8912 8th grade students and 844 science teachers who finished the surveys from 212 public schools and 20 private schools.

3.3. Item and Constructs Science classroom technology resources: technology resources were measured by computer resources in this study. In the TIMSS teachers’ questionnaire, science teachers were asked “In your view, to what extent do the following limit (shortage of computer hardware/software/support for using computers) how you teach the class? The valid responses were at a 4-point Likert scale, ranging from the scale: 2= not at all; 3= a little; 4= some; and 5= a lot. Descriptive statistics are shown in table 1.

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Another technology resource is measured by the availability of computers to use. Science teachers were asked a dichotomous question “Do students in the TIMSS class have computers available to use during their science lessons?”

Science attitude variables: There were 12 science attitude items in the student questionnaire. Students were asked to indicate their level of agreement on a 4-point Likert scale, ranging from the scale: 1= agree a lot; 2= agree a little; 3= disagree a little; 4= disagree a lot, with the following statements (see table 2 for details). Some items were recoded in order that high score indicated a positive science attitude.

Table 1. Descriptive statistics for technology resources items Items Mean SD 1 Limit to teach\shortage computer hardware 3.32 1.18 2 Limit to teach\shortage computer software 3.25 1.14 3 Limit to teach\support computer use 2.94 1.10

Table 2. Descriptive statistics for science psychological items Items Mean SD 1 I usually do well in science._recoded 3.22 .82 2 I would like to take more science in school._recoded 2.74 1.03 3 Science is more difficult for me than for many of my 2.99 .98 classmates. 4 I enjoy learning science._recoded 2.96 .98 5 Sometimes, when I do not initially understand a new topic in 3.10 .95 science, I know that I will never really understand it. 6 Science is not one of my strengths. 2.75 1.07 7 I learn things quickly in science._recoded 2.95 .930 8 I think learning science will help me in my daily life._recoded 2.99 .88 9 I need science to learn other school subjects._recoded 2.74 .92 10 I need to do well in science to get into the of my 3.18 .91 choice._recoded 11 I would like a job that involved using science._recoded 2.51 1.09 12 I need to do well in science to get the job I want._recoded 2.74 1.08 Note: Some items are recoded in order that high score indicates positive science attitude.

3.4. Analysis An independent-sample t-test was applied to answer the first research question. To answer the second and the third research question, a structural equation model of the hypothesized relationships among observed variables and latent variables was conducted, using LISREL 8.8 computer program (Jöreskog & Sörbom, 2006). Structural equation modeling is an especially appropriate method for analyzing non-experimental data. In addition to parameter estimates, the program provides fit indices to assess how well the model fits the data. Such fit indices make it possible to evaluate the adequacy of the theoretical model in explaining the data (Bollen,

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1988; Schumacker & Lomax, 2004). The fit of the model was tested using maximum likelihood estimation.

In evaluating the overall goodness-of-fit for the SEM model, Schumacker & Lomax’s (2004) criteria were used: (a) the chi-square and p value, which if p > .05 indicates that there are no statistically significant discrepancies between sample variance-covariance matrix and the reproduced implied covariance matrix. As this statistic is very sensitive to sample size and departures from multivariate normality, it may easily reject a well-fitting model (Hatcher, 1994); (b) Goodness-of- fit Index (GFI), Adjusted Goodness-of-fit (AGFI) and Comparative Fit Index (CFI) values close to .95 reflect a good fit and 1.0 indicate a perfect fit. (c) Normed Fit Index (NFI), which defines the null model as a model in which all of the correlations or covariances are zero and the value close to .95 reflects a good model fit. (d) Root-mean-square Error of Approximation (RMSEA) value less than .05 indicates a good model fit; less than .10 is in an acceptable range. Overall, these fit indices indicate how well the data support the model.

The two-step model (James, Mulaik & Brett, 1982; Anderson & Gerbing, 1988) was used in this research. In the first phase of the two-step model building approach, measurement models for all latent variables in the model were estimated. The second step is the structural part of the SEM. This structural part specifies the relationships between the exogenous and endogenous variables.

4. Results 4.1. Independent-Sample t-test Table 3 shows the result of the first research question. A total of 844 science teachers responded the survey. 590 (69.90%) report that their students have computers to use in the science lessons; while 254 (30.10%) report their students don’t have computers to use. The mean science score of the students who have computers to use is 150.44 (SD= 6.37) which is significantly higher than the mean score (M=149.12, SD=6.26) of students who don’t have computers to use in science lessons (t(842) = 2.763, p < .01).

Table 3. Frequency of computer availability Computers Available N Percent Mean SD In Science Lessons (%) Science Rash YES 590 69.90 150.44 6.37 Score NO 254 30.10 149.12 6.26 Total 844 100

4.2. Structural Equation Modeling Measurement model Twelve science attitude items were analyzed by confirmatory factor analysis (CFA), the results indicated that the first 7 items loaded on the first factor and the other 5 items loaded on the second factor. We named the first factor as the interests of science and the second factor as valuing science. The fit indices for the model were good, indicating a well-fitting model in which data fit well to the measurement model, χ2(42) = 1595.63 (p<.05). The goodness-of-fit index (GFI) was 97, and

EITT 2013, Williamsburg, VA, USA, November, 2013 299 Proceedings of International Conference of Educational Innovation through Technology the adjusted goodness-of-fit (AGFI) index was 94. The comparative fit index (CFI) was .98. The standardized root mean square error of approximation was .068.

Structural model Science attitudes factors were hypothesized as mediators between science classroom computer recourses and science achievement. Since not all paths were significant, insignificant paths were deleted one by one sequentially to arrive at a more parsimonious model.

Figure 1: Final structural model

The final structural model was shown in figure 1. The model overall explained 12% of variance in science achievement. The fit indices for this model were good, indicating a well-fitting model in which data fit well to the hypothesized model. χ2(42) = 4789.59. The goodness-of-fit index (GFI) was .91, and the comparative fit index (CFI) was .95. The standardized root mean square error of approximation was .088. Overall, these fit indices indicate a theoretically sound model that explained the data well.

Table 4. Standardized direct, indirect, and total effects of computers resources and science

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Because the overall fit of the model was considered adequate, the structural relations in the model as the effect of one latent variable on the other could be interpreted. The three direct effects on science achievement were from computer resources, Interests of science, and valuing science. The strongest effect was that of the interests of science (γ=.29). Valuing science showed a positive effect on science achievement (γ=.03). The shortage of computer resources had a negative effect on science achievement (β=-.13). The more shortage of computer resources, the lower students’ science achievement was. A direct effect of computer resources on the interests of science (β=-.04) was found, which supported the hypothesis that students’ science attitude was a mediator between computer resources and science achievement. The two science attitudes factors, interests of science and valuing science, were strongly related, the effect of interests of science on valuing science was .52. Although there was no direct effect from computer resources to valuing science, an indirect effect was found through the interests of science (γ=-.02). Overall, the shortage of computer resources had negative effects on students’ science attitudes, and in turn, science achievement. Students’ science attitudes positively affected science achievement (see table 4 for details)

5. Conclusions This study supported some previous research and concluded that students who had computers available to use in science lessons had higher science achievement than students who didn’t have computers to use. The shortage of computer resources could decrease students’ interests in science and their science achievement.

Two of the students’ science attitude factors, interests of science and valuing science had a direct positive effect on science achievement, and these two kinds of attitude factors were strongly related. Students, who were interested in science and considered it important tended to also value it for their future education and occupational aspirations. In turn, students who had positive attitudes in science learning were higher achievers in science. Realizing the importance of science for future education would promote student interest in the subject.

This study corroborates the earlier work by researchers and provides evidence in support of effects of science attitudes, classroom technology resources on science achievement. The results further support that including self and school resource factors improve the explanation of variability in science achievement. The study has both theoretical and practical significance. It presents models of science achievement, and addresses the critical question of availability of computer resources and raises a question about the importance of technology resources for science success.

References American Association for the Advancement of Science Washington DC. (1989). Science for All Americans: Summary, Project 2061: Andrew W. Mellon Foundation, New York, NY.Carnegie Corp. of New York, NY. Alspaugh, J. W. (1999). The relationship between the number of students per computer and educational outcomes. Journal of Educational Computing Research, 21(2), 141-150. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recrecommended two-step approach. Psychological Bulletin, 103, 411–423. Bollen, K. A. (1989). Structural equations with latent variables. New York: John Wiley & Sons. Darling-Hammond, L. (1997). The Right To Learn: A Blueprint for Creating Schools That Work.

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The Jossey-Bass Education Series. Duschl, R. A., Shouse, A. W., & Schweingruber, H. A. (2007). What research days about K-8 science learning and teaching. Principal, 87(2), 16-22. Eccles, J. S., Wigfield, A., & Schiefele, U. (1997). Motivation to Succeed. In W. Damon & N. Eisenberg (Eds.), Handbook of child psychology (5th ed., Vol. 3, pp. 1017-1095). New York. Hatcher (1994). A step-by-step approach to using the SAS System for factor analysis and structural equation modeling. Cary, NC: SAS Institute. James, L. R., Mulaik, S. A., & Brett, J. M. (1982). Causal analysis: assumptions, models and data. Beverly Hills: Sage. Jöreskog, K. G., & Sörbom, D. (2006). LISREL 8.8. Chicago: Scientific Software International. Manning, M. L. (1998). Gender differences in young adolescents’ mathematics and science achievement. Childhood Education, 74(3), 168-171. Martin, M. O. (Ed.). (2005). TIMSS 2003 user guide for the international database. Chestnut Hill: MA: TIMSS & PIRLS International Study Center, Boston College. National Academy of Sciences - National Research Council Washington DC. (1996). National Science Education Standards: Department of Education, Washington, DC.National Aeronautics and Space Administration, Washington, DC.National Science Foundation, Washington, DC.National Institutes of Health (DHEW), Bethesda, MD. Nolen, S. B. (2003), Learning environment, motivation, and achievement in high school science. Journal of Research in Science Teaching, 40, 347–368. Schumacker, R. E., & Lomax, R. G. (2004). A beginner’ guide to structural equation modeling (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates. Sofroniou, N., & Kellaghan, T. (2004). The utility of third international mathematics and science study scales in predicting students’ state examination performance. Journal of Educational Measurement, 41(4), 311-329. Wen, M. L., Barrow, L. H., & Alspaugh, J. (2002). How does computer availability influence science achievement? A paper presented at the Annual Meeting of the National Association for Research in Science Teaching, April 7-10, New Orleans, LA. Zucker, A. A. (2009). Assessment made easy: Students flourish in a one-to-one laptop program. Learning & Leading with Technology, 36(8), 18-21.

AcknowledgementsAcknowledgement This study was supported by China Culture Heritage Foundation by Tsinghua University (Grant No. 2012WHQN016).

302 EITT 2013, Williamsburg, VA, USA, November, 2013 Qu, X. M. & Miao, R. (2013). The enlightenment of teacher professional development based on professional leading on the in-service training of rural teachers. . Proceedings of International Conference of Educational Innovation through Technology, 303-308.

The Enlightenment of Teacher Professional Development Based on Professional Leading on the In-Service Training of Rural Teachers

Ximei Qu, Rong Miao Peking University Email: [email protected];[email protected]

Abstract: The training of rural teachers has an important influence on the reform of basic education. To overcome the drawbacks of teachers’ training today, we can cast a professional eye on the problem from the perspective of teacher professional development, especially from the perspective of teacher professional development based on professional leading. With this idea in mind, through the analysis of the assessment data for in-service training of primary school teachers from five counties, based on the theory of teacher professional development based on professional leading, this paper will discuss the enlightenment of teacher professional development based on professional leading on the in-service training of rural teachers from two aspects: Firstly, attitude of teachers participating in the training to “professional leading”: Teachers participating in the training like “Professional Leading” very much, and they have benefited much from the training. But they hope that experts can make a better balance of the theory and practice, and the content that experts teach should be closer to the actual situation in rural areas. Secondly, combining professional leading with self-reflection: Educational experts can give full play to the advantages of theory and resources to help teachers do the self-reflection by going into practice to improve teachers’ teaching capacity.

Keywords: teacher professional development, professional leading, in-service training

1. Instruction Education is very important for the development of a country, and the construction of teacher ranks is not only prerequisite for the development of education, but also quality assurance of the development of education. Teacher training is one of the most effective ways to improve the teacher quality, especially for the teachers in rural areas with fewer resources, so we should value highly training’s opportunities to improve the quality of rural teachers.

2. Theory Foundation 2.1. Concept of Teacher Professional Development On teacher professional development, domestic and foreign experts have carried out many related research. At the end of 1960s, American scholar Fuller worked out the famous “Teacher Concerns Questionnaire” and opened a prelude to research about teacher

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 303 Proceedings of International Conference of Educational Innovation through Technology development theory. Since then, the theory research about teacher development has become a booming research area.

Since the 1990s, along with the development of society and the implementing of a series of policies on education reform, the teachers’ education and teacher training have made great progress, meanwhile; have also faced a lot of problems (Miao, 2012). “As an important part of teacher education system, teacher in-service training is one important way of teacher professional development (Zhang 2005).” Until now, the issue of teacher professional development has gradually become the hot issue of teacher education research.

Teacher professional development is a process of lifelong learning, a process of constantly problem-solving, and a process of constantly improving and enhancing the career aspirations, professional ethics, occupational emotion and social responsibility. In the past few years, teacher professional development has been considered a long-term process that includes regular opportunities and experiences planned systematically to promote growth and development in the profession (Villegas-Reimers, 2003). Fullan and Hargreaves pointed out that when they referred to teacher professional development, they had two meanings: teachers gain the development in some specific aspects through in-service teacher education or teacher training, or teachers make comprehensive progress in teaching skills and colleagues cooperation ability (Fullan, M. &Hargreaves, A, 1992). Perry analyses the theory of teacher professional development from the perspective of increasing teachers’ confidence, enhancing skills, constantly updating and broadening subject knowledge as well as the reasons for teachers doing so in the classroom(Perry,1980). Lieberman thinks that teachers are seen as “a reflection practitioner” and a person who can constantly reflect and re- evaluate (Lieberman, 1994).

In this paper, teacher professional development means that teachers improve their knowledge, skills and so on, through in-service education or teacher training.

2.2. Professional Leading Teacher professional development has many forms, and professional leading is one of them. The definition of “professional leading” is that personnel with expertise in educational research, through their advanced concepts, ways of thinking and advanced experience, guide and lead the first- line teachers to explore and research education practice, to promote the professional development of teachers, and dynamic study of school content development (Lin, 2011). Professional Leading is a form of the development and utilization of expert resources, a way of getting experts’ guidance and a form of the utilization of human resources (Pan, 2004).

People who implement “Professional Leading” are professional researchers in the education field and expert teachers. The former include educational research staff, university professors, and so on. The latter include special-grade teachers, subject pacemakers, and so on. The strengths of professional researchers in the education field are that they have systemic educational theory and research methods, and they have a broader view and relatively large amount of resources. Expert teachers’ strengths lie mainly in the rich practical experience and have obvious advantages in combining theory with practice.

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In essence, professional leading is the guiding of theory and experience to practice, is the dialogue of theory and practice, and is the reconstruction of the relationship of theory and experience with practice. Professional leading is not a one-way transmission of information from the experts to teachers, but bidirectional information transfer and resonance between experts with teachers. Professional leading is advantage complementation between experts with teachers built on the basis of cooperation, is experts and teachers’ growing together through mutual exchanges and mutual inspiration (Sun, 2008).

In general, the main forms of professional leading are theoretical knowledge instruction, special academic report, conducting teachers on-site (listening to class and evaluating class) and professional consulting about teaching (discussion). All activities are mainly based on the need of leading object (Li, 2011).

Therefore, professional leading has many features such as purposeful, designed, situational and interactive. “Situational” means that “professional leading” is connected to the real situation of teaching, or the leading activities exist in the real situation of teaching. “Interactive” emphasizes the equal interaction between professors and teachers (Xia, 2005). In brief, “professional leading” is a professional guide and technical support based on teachers’ teaching scenes provided by professors, scholars or outstanding teachers, and it is conducive to the professional development of teachers in rural areas.

2.3. Overview of In-Service Training of Teachers in Rural Areas Generally, Teachers’ training includes induction training and in-service training. Induction training is for newly recruited new teachers, who will be supported, monitored, and evaluated. While in-service training is some kind of continuing education in order to further improve teachers’ professional quality or academic qualifications. In “Survey of In-Service Training of Teachers in 1967” published by the British National Education and Science Ministry in 1970, “in-service training” is defined as “teachers participate in any kind of activities linked to their professional work after they are recruited.” and later it is called “In-Service Education and Training of Teachers”, abbreviated as INSET(Lin& Liu, 2003). In-Service training in this paper is referred to as continuing education to improve the quality of teachers, and to promote teachers’ growth.

In addition, “teachers from rural areas” mentioned in this article refers to the primary and secondary school teachers in rural areas. As early as in the 1970s, the British government began to focus on the implementation of a national in-service training of primary and secondary school teachers. In the ranks of primary and secondary school teachers, the quality of primary and secondary school teachers in rural areas has become a bottleneck restricting the level of basic education. They need efficient in-service training to improve their quality. Therefore, I think we can cast a comprehensive eye on the work of teacher training, from the perspective of the theory of teacher professional development, not only considering social value of an individual, but also considering teachers’ personal development. Only in this way, can we achieve the standardized and scientific training of rural teachers sooner and better.

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3. The Enlightenment The revelations below are drawn through both theoretical basis of the foregoing, and the in-service training for rural teachers in west of China I ever participated in (we will call it “training A”).

3.1 Project Description Training A started in April of 2010, primary school teachers from five counties in west of China accepted the training.

In October of 2012, the assessment team including me began to assess the training effectiveness. Our team has been to 15 primary schools in 5 counties. We held 15 discussions with 228 teachers, taking photos, recording videos or recording sound. We interviewed 30 teachers, recording sound. After our field research, we changed from recordings to written language and then analyzed them.

3.2. Inspiration 3.2.1. Attitude of teachers participating in the training to “professional leading”. According to the assessment data of training A, teachers participating in the training like the way of “professional leading” very much. During the process of training, education experts can not only help front-line teachers to enrich the professional knowledge and skills, but also be able to deliver a lot of positive spirits to ignite the first-line teachers’ desire to continue to learn to improve themselves. At the same time, the interaction between experts and teachers participating in the training also greatly inspired the teachers’ enthusiasm for learning and participation enthusiasm. In the process of field research, many teachers mentioned that point, “There is so much knowledge we still need to learn. After hearing experts’ understanding of the lessons, I feel I am some kind of superficial and I need to do more”. “We have learnt a lot from the experts, and they help us enrich our professional knowledge”. “Once a time I made a speech on behalf of our team and I performed very well, then our teacher rewarded everyone in our team a piece of chocolate. This’s a surprise, and also made me encouraging.” One worker of local center for educational technology pointed out that “the training experts have come to our county for 4 times to coach teachers. They help teachers to integrate training content to apply that in the class”.

At the same time, as for “professional lead” in the training, teachers participating in the training hope there are less theory and more practice. “Most time in the training, the teacher speaks, while we listen. We were a little passive. ” In the process of training, the role of teachers participating in the training are also students in a way, and they do not like spoon-feeding way of teaching or overwhelming theory just like normal students. Therefore, teachers participating in the training hope that the experts can balance the theory and practice better.

In addition, teachers participating in the training hope that the training content can “be more suitable for the rural situation” during the process of professional leading. As a teacher mentioned in the interview: The content experts teach is valuable, but it is more applicable to the city’s education than rural education. After we finish our training, I can’t apply the knowledge to our school in rural areas. Just like inquiry learning we learnt, kids here do not have ability to ‘explore’. What is

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more, parents here do not support this kind of learning style. And most families don’t have computers at home, so it is not very convenient for students here to have access to reference materials.（from interview data）

Therefore, we hope that experts can meet the real need of the teachers participating in the training during the process of professional leading to provide them with support and services suitable for local condition.

3.2.2. Combining professional leading with self-reflection. Professor Lin Chongde put forward a formula about teacher growth: Excellent Teacher = Teaching Process + Reflection, which stressed the importance of teachers’ self-reflection in a certain sense (Dou, 2010). Teacher self-reflection is one of the core elements of teachers’ professional development and personal growth, and the inherent requirement for teachers to improve teaching skills. Therefore, experts and teachers should go into practice together, using the way of action research to help teachers to find problems, solve problems and carry out self-reflection in the way of combining experts’ theory advantages with front-line teachers’ teaching practice.

Conducting teachers on-site (listening to class and evaluating class) is one of important forms of “professional leading”, and it also embodies the feature of “situational” of “professional leading”. Of course, there are many ways you can choose to observe the class. First of all, training experts can take excellent teaching case videos into the training class. After playing the video, the experts can conduct teachers participating in the training to do some self-reflection and speak reviews, and then explain the relevant theory; Secondly, experts can have a class on-site. Teachers participating in the training can have their own self-reflection, while they listen to the class. In the process, teachers can get to know experts’ techniques and teaching methods more intuitively. Combined teachers’ own self-reflection and the expert’s reviews, teachers’ own way of thinking and consciousness will be further improved. The third way is to make local teachers participating in the training have a class, and then based on the class, combined with reflection reviews of the teachers, experts explain the relevant theoretical knowledge and practical skills for teachers participating in the training. When we did the field research, many teachers recommended to add the link of “Conducting teachers on-site”, which can promote the teaching methods’ collision in their brains, and guide their own reflection. One teacher said: We teachers feel that the best way of training is to listen to a class and then evaluate it. The techniques and methods apply in the class can lead us to reflect. After class, we can make comments and ask questions based on this class. For example, in an auditorium, special-grade teachers and students have classes on the stage, and we teachers sit in the auditorium. Having a class is some kind of art! This kind of training style is excellent!

4. Conclusions It is a very popular educational research direction to explore in-service training of teachers in rural areas from the point of view of teacher professional development in recent years, while research about teacher professional development based on professional leading is still relatively rare. In this paper, based on the interview and discussion about a training project in west of China, we have two points of Enlightenment: Firstly, rural teachers like the form of professional leading very much. At the same time, they recommend to balance theory and practice; Secondly,

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training effectiveness will be better through combining professional leading with self-reflection.

References Dou, F. L. (2010). Reflection about training of rural teachers from the perspective of teacher professional development. China Adult Education, 84-85. Villegas-Reimers, E. (2003). Teacher professional development: an international review of the literature. International Institute for Educational Planning. Jiang, J. Y. (2004). Teacher professionalization and summarization of teacher professional development. Education Exploration, 104-105. Li, M. S. (2011). An outline of teacher professional development. Changchun Publisher of JiLin. Lin, Y. & Liu, L. (2003). Forms and features of in-service training for primary and secondary school teachers from developed countries. Education of Foreign Primary School and Secondary School, 24-28 Miao, R . (2012). Teachers’ educational technology capacity--standard, development and evaluation. Beijing：Peking University Press, 240-245. Pan, G. Q. (2004). Professional leading in the school education research. Exploring Education Development, (10) Perry, P.(1980). Strength through Wisdom: A Critique of U.S. Capability. MLJ. Sun, G. F. (2008). The research of "depth-involved style" professional leading promoting teacher professional development--taking teacher development school “Z” as an Example. Nanjing: Nanjing Normal University. Xia, X. G. (2005). School-based teaching and teacher’s professional development in rural areas. Journal of Guizhou Normal University (Natural Sciences), 102-105. Zhang, J. P. (2005). Tactics research of middle and primary school teacher training based on teacher professional development. Qufu: Qufu Normal University.

308 EITT 2013, Williamsburg, VA, USA, November, 2013 Shen, X., Chen, L & Li, Y. (2013).The construction of quality assurance system for distance education based on ecological view. Proceedings of International Conference of Educational Innovation through Technology, 309-316.

The Construction of Quality Assurance System for Distance Education Based on Ecological View

Xinyi Shen, Li Chen, Ying Li Beijing Normal University Email: [email protected]; [email protected]; [email protected]

Abstract: With Chinese modern distance education developing, it produces many outcomes. However, the quality is queried by society, and the degree of social acceptance of students graduated from distance education is not high. This article considers the reason of quality problem is that there is no sound quality assurance system. This article summarizes the status of Chinese modern distance educational quality assurance, and analyzes its problem from the perspective of ecological view, such as lack of ambient energy, single species, and poor information flows. Lastly, we establish a quality assurance system based on ecological view, which includes ecological main body and environment, in order to provide the growth of distance education quality assurance with suggestion and promote the further development of distance education.

Keywords: distance education, quality assurance, ecological view, system

1. Introduction With Chinese modern distance education developing, it has gone through more than a dozen years. Chinese modern distance education has sped up the construction of information technology in experimental colleges, promoted educational equity and balanced development. Although the successes are indeed gratifying, the problems cannot be avoided. The quality of Chinese modern distance education has been queried by society all the time, and the degree of social acceptance of students graduated from distance education is not very high. So the work of quality management in agencies receives wide attention, and the agencies themselves have made a lot of efforts. Some of them introduced ISO9000. Others developed the rules and regulations for student management, teacher management and examination management. The government also tried their best to promote the development of distance educational quality assurance. The Ministry of Education promulgated more than 100 policy documents in turn about approval and management, recruitment and employment, certificates and electronic registration, examination, annual inspection, assessment and teaching norms of the Network Education College, public service system and learning center. Furthermore, it established information quality monitor platforms and mechanisms for online education. However, the quality view isn’t unified, the standards of quality assurance are lacking, and the implementation model for quality assurance is unsound. We can’t even mention the internal benign adaptive and self-development.

According to the literature survey, the problem about distance educational quality attracts much attention from distance educational experts who make good suggestions for system construction from their own research experience and objective practical research. Of course, there are also many articles about the construction of distance educational quality system. While the number of articles that examine Chinese distance educational quality assurance system from ecological perspective

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 309 Proceedings of International Conference of Educational Innovation through Technology is not too much. From an ecological point of view, there are no live organisms can exist alone. An organism must rely on surrounding and exchange material energy and information with it in order to survive (Ai, 2011). Similarly, the smooth development of network distance education ecosystem cannot leave environment for its survival and development. Consequently, based on the reality and truth of Chinese distance education, this article devotes to construct distance educational quality assurance system from an ecological point of view.

2. Ecological View for Quality Assurance in Distance Education The definition of ecological view in “Dictionary of Environmental Science” is the views on ecosystem, which is regarded as the fundamental viewpoints to treat the relationship between man and nature (Community of environmental sciences dictionary, 1991). But in “Encyclopedia of Marxism philosophy” edited by Huaichun Li, ecosystem is a dynamic equilibrium system composed by biomes and their environment (Li, 1996). Ecosystem is an organic whole constituted by general contact and interaction among various ecological factors including biological and environmental factors. A change of any one ecological factor, namely whether it is a biological factors change or an environmental factors change, will have an effect on all other ecological factors, and even cause changes in the whole system; Similarly, any one factor in the system changes depending on all the other factors(Community of environmental sciences dictionary, 1991).

Ecological view from a perspective of social development indicates that it is human overall understandings and views on ecological issues. With the continuous development of ecology, mankind also proposed centralized ecological view about individual organisms, populations, communities and systems theory successively. Since the 1960s, the ecological research priorities have changed from focusing on biosphere to concentrating on human society. And the trend of combining ecology and social science began. Thus, mankind gradually gained a new series of ecological conception, such as ecological economy outlook, ecological ethics outlook, ecological law outlook, ecological philosophy outlook, ecological aesthetics outlook and ecological education outlook and so on. The formation of these emerging ecological views is all caused by the trend of ecological construction and sustainable.

1976, Cremin, L. A. who is the former dean in normal academy of American Georgia university formally proposed the term of ecology of education in “Public Education” (Fan, 1995). Ecology of education is that apply the ecological principles, especially the ecosystem, ecological balance, co-evolution and other principles and mechanisms, to study a variety of educational phenomenon and its causes, then grasp the law of educational development, and reveal the trends and directions of educational development (Wu, 1998). The theoretical framework of educational ecology was constituted by three factors including educational structure (educational institutions), social and individual learners. In this theoretical framework, there was also a relationship of interaction among three factors (Cui, 2012). The flows of these substances, energy and information promoted or restricted each other and then promoted the ecological succession of education, so that the level of education would transform from junior to senior.

The ecological view of distance educational quality assurance has the following characteristics:

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Diversity (Sun, 2012). The diversity of distance educational quality assurance ecology emphasizes that there are multiple elements in the system, which contact and influence each other. The diversity fusion like this is based on the state of harmony and unity among various elements.

Openness. As same as other ecosystems, distance educational quality assurance exchanges substances, energy and information constantly while it is conducting an orderly flow of substance flow, energy flow and information flow, which makes itself to adapt to the external social environment in order to survive and develop.

Coevolution (Zeng, 2011).The evolution of species will inevitably change the selection pressure on other organisms, which will cause the changes of other organisms. And these changes will lead to further changes of related species. This relationship of co-evolution that is mutually adapted and interactive is called coevolution. There is also the coevolution function in distance educational quality assurance system. Distance education institutions, assessment agencies, and academic institutions in the system complement each other for common development.

3. The Current Situation and Issues of Quality Assurance Since distance education pilot project in 1999, Chinese distance education has made tremendous progress, which has also contributed to Chinese education. A variety of educational tools and educational models have formed to promote the fairness of Chinese education. However, distance education faced the quality issues in the development. What’s more, Collective cheating scandal occurred at the preliminary stage of distance education. We have to admit that the reputation of distance education in the society is not ideal. Therefore, as a expert or a staff in the field of distance education, we have responsibilities to work hard for enhancing and maintaining the reputation of distance education.

At this stage, Chinese distance education mainly adopts the government-led quality assurance model that government uniformly controls and manages the quality of distance education institutions. There are three measures of quality management mainly adopted, one is exam, one is annual report and inspection, and another one is that the third-party agencies assist educational institutions to improve the quality. These three forms the body of Chinese distance educational quality management together.

Examination system Ministry of education started to implement unified national exam for some public basic course online, including university language, mathematics, English, computer application foundation and so on. It is national unified outline, unified examination questions and unified standards implemented in the examination.

The system of annual report and inspection Ministry of education launched the system of annual report and inspection from 2001, and implemented regulation, including four steps that introspection, annual reports, sampling and annual inspection, Foronline College of ordinary university, the pilot projects of the Central Open Education and public service system. And provincial education administrative departments inspected and evaluated the learning center outside campus.

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The third-party agencies assist educational institutions Most of network colleges established the system of teaching inspection. They organized regular teaching examination, held the conference of off-campus learning center, as well as assessed and monitored the teaching process. In addition, some network colleges also established an internal quality assurance system to strengthen self-discipline. There are four network colleges have passed the ISO90001 quality management system certification at least, including the network educational college of Peking University Health Science Center, the network educational college in Northeastern University of Finance and Economics, the distance and continuing educational college in China University of Petroleum (east China) and the distance educational college in China University of Petroleum (Beijing). It is worth mentioning that the national collaborative group of distance education, composed by competent principals, instructional leaders and technical directors from the universities that participated in the modern distance education whose main purpose is promoting the exchange of experience in distance education among colleges and universities, solving the problems encountered together, and promoting the development of Chinese distance education.

Collectively, although we have taken a number of measures to ensure the quality, the measures are piecemeal and fragmented. And there is no independent institution to carry out quality assurance work, which is lack of systematic. As for distance educational quality assurance ecosystem, if we want the system to achieve dynamic equilibrium, we must ensure that the energy can continuously input. The distance education energy flow, substances flow and information flow orderly flow and operate, which ensure the virtuous circle and dynamic equilibrium of educational ecosystem (Sun, 2012). From the perspective of ecological view, there are some problems in the quality assurance system of Chinese distance education, such as ambient energy loss and single species.

The ack of ambient energy (Shang, 2013). In the natural ecosystem, energy flow is a process of input, transmission and dissipation for energy. Every ecosystem needs energy input, which is necessary to maintain the balance of ecosystem. The same as other ecosystems, the normal operation and sustainable development of open and distance education also depend on the input and transmission of energy flows (Sun, 2012). So far, the quality assurance systems lack institutional quality positioning, direction and the level that quality needs to achieve, which are provided by the national level. That means they lack quality assurance standards, indicators, models and other policy guidance on a macro level.

Single species. In the distance educational quality assurance ecosystems, there are only distance education institutions, governments and so on. But it lacks specialized assessment agencies and it also ignores the important role of academic institutions played in quality assurance system. Besides, the quality feedback from society is overlooked. In the existing ecology, the population of distance education institutions rapidly expands, while other populations are lack of development. This phenomenon leads to extreme imbalance of ecosystem and hamper the sustainable development of the entire system. Ecological threshold refers to a maximum quantity of biological population allowed by an environmental condition (Zeng, 2011). Considering ecological threshold, we can’t expand the number of distance education institutions without limit, and we can’t enroll students within the institutions without restraint, either. However, once the ecological threshold is damaged, it will suffer greater destruction.

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The transmission of information exits problems. The balance of educational ecosystem is mainly to investigate the functional performance situation of material flow, energy flow and information flow in the system. According to the “natural law” in Darwin’s theory of evolution, any form of living things must constantly receive information from the changing environment in order to adapt to changes of the external environment and survive without being eliminated (Bao, 203). And the poor transmission of information will lead to elimination. In distance educational quality assurance system, the evaluation results of distance education didn’t present openly to society and students. Consequently, students can’t choose institutions according to the evaluation results, and society cannot provide institutions with objective and fair assessment.

4. The construction of distance educational quality assurance system based on ecological view Ecosystem is a unified whole formed by all biological factor and abiotic factor whichis associated and interacted with each other in the scope of a certain space, through the process of energy flow and material cycle. Inorganic environment is the foundation of an ecosystem, it effects on biological communities and get reaction of it. Biological communities in the ecosystem is not only adapting the environment, and also changing the face of surrounding environment. A variety of basic matters closely combine the biological communities and inorganic environment. The close connection between various components of the ecosystem makes the ecosystem be a organic whole with certain function. Biology and environment is an integral whole, which we call the ecosystem (Shang, 2013).

The ecosystem of distance education quality assurance mainly includes ecological subject and ecological environment. There are multiple population the ecological subject, between which exists a ecological chain to process the exchange of energy, knowledge and information. The ecological chain is the basic way of the positive cycle of the ecosystem. This ecological environment system is based on the distance education, and is a multivariate environment playing a role to restrict and control the formation and development of distance education. It’s the carrier of ecosystem to exist and develop.

In the ecological subject of distance education, there are three middle populations, distance education provider, academic institution and accreditation institution (Figure 1). Accreditation institution will regularly evaluate the educational institution, monitoring its operation and quality. Distance education institution provides periodic reports to the assessment institution according to the regulation. Assessment will encounter all sorts of problems in the process of their work, and then they need the consultation of academic institution. Academic institution provides the solution according to the practice research and theory study. Distance educational provider is the research basis of academic institution to carry out the study. Academic institution regularly publishes research result, consult the education institution and help them to improve the quality.

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Figure 1 ecological subject

Figure 2 ecological quality assurance system for distance education

Ecological environment, the equivalent of inorganic environment, mainly refers to the policies and quality feedback from various stakeholders. To analyze from the perspective of ecology, there is not a living organisms can exist in isolation. To survive, every organism must rely on the surrounding

314 EITT 2013, Williamsburg, VA, USA, November, 2013 The Construction of Quality Assurance System for Distance Education Based on Ecological View environment and exchange energy and information with it. Also, the distance education could not leave the surrounding environment, including the policies, the regulation and the feedback of stakeholders, to assure the development of ecosystem (Ai, 2011). Policies include the construction of credit system, standards and the establishment of third party institutions, etc. Policies effect on the three institutions, and the development and challenge of the three institutions stimulate the further improvement of policies. Besides the policy support, the ecological subject publishes the evaluation results, and receives the quality feedback from students, teachers, employers and other members of the community. The structures and functions of any ecosystem depends and complete each other, to make the various parts of ecosystem be the best coordination state, by the constraining, transformation, compensation and feedback, showing the high productivity. The ecological balance of the ecosystem is the guarantee of sustainable development of the ecosystem. Maintaining the balance between organisms and between environment and organisms and keep the ecosystem to be in a relatively stable state, and make the ecosystem be sustainable (Zeng, 2011). In the system of distance education quality assurance, The institutions exchange energy, material and information, restrain and promote each other, form a virtuous circle, reflected the ecological stability and self-adjusting ability.(Figure 2)

In fact, the three main populations form an ecological cycle in this ecosystem. The institutions connect and restrict each other, and improve themselves in the interaction between each other. The three institutions develop spiral upward, the development of one institution will stimulate others. (Figure 3)

Figure 3. ecological development of the three institutions

5.Conclusion Improving the quality and its reputation is the direction of joint efforts of distance education practitioners and researchers, and how to reach the other shore is still a long way to go. In the biology perspective, the distance education quality assurance makes us use biology view to study the relationship between the internal and external environment of modern distance education, and use the concept of sustainable development to analyze and solve practical problems, make the modern distance education in balance and sustainable, in order to achieve the balance of internal and external education system, and promote people’s learning and development more efficiently (Qian, 2012).

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The sustainable development of distance education is based on a sound and harmonious quality assurance system, which can be based on biology (Zhang & Zhang, 2006). So, only to build the quality assurance system from the perspective of ecology can make the distance education develop sustainably and serve the society by playing the role improving social and individual development.

References Ai, Y. X. (2011). The composition and construction of web-based distance education ecosystem. Journal of Shandong Radio and TV University, 4. Li, H. C. (1996). Encyclopedia of Marxism philosophy. Beijing: China Renmin University Press, 607. Editorial Board of “Dictionary of Environmental Science” (1991). Dictionary of Environmental Science. Beijing: China Environmental Science Press. Fan, G. R. (1995). The commentary of Lawrence•Cremin thoughts about educational ecosystem. Journal of Sichuan College of Education, 2, 25. Wu, D. F. & Chu, W.W. (1998). Educational ecology. Jiangsu Education Press. Cui, G. P. (2012). The classical application of educational ecology theory - the study of “The tradition of American education” written by Lawrence•Arthur•Cremin. Higher Education Management, 11, 83. Sun, W. X. (2012). Study on sustainable development of distance education in the ecological environment. Journal of Xiamen Radio and TV University, 2. Zeng, X. Y. (2011). Characteristic analysis of web-based distance education ecosystem. Journal of Guangzhou Radio and TV University, 6. Shang, X. S. (2013). Imbalance and construction of modern distance educational ecology based on educational ecology. Adult Education, 5. Bao, J. C. (2013). New thinking of distance higher education development in Qinghai province. Continue Education Research, 8. Qian, M. H. (2012). The teaching strategies research of modern distance education based on ecological sight. Journal of Nanjing Radio and TV University, 4. Zhang, J. L. & Zhang, K. M. (2006). Ecological imbalance and countermeasure in modern distance education. Distance Education Journal, 5.

316 EITT 2013, Williamsburg, VA, USA, November, 2013 Su, F., & Chen, Y. (2013). Improving Digital Literacy through Self-study to Promote Continuing Professional De- velopment. Proceedings of International Conference of Educational Innovation through Technology, 317-320.

Improving Digital Literacy through Self-study to Promote Continuing Professional Development

Fang Su, Yajie Chen Inner Mongolia University of Technology Email: [email protected]; [email protected]

Abstract: The web and current digital tools offer greater opportunities for information seeking and knowledge creation, but they also pose challenges. Therefore, there is an increasing emphasis on EFL teachers’ digital literacy. How to improve EFL teachers’ digital literacy is a frequently asked question, especially by frontline teachers who are busy with their teaching tasks. This paper first addresses the issue of digital literacy. Then it goes on to discuss how to improve teacher’s digital literacy to further promote teachers’ continuing professional development (CPD). The self-study research method is proposed as a way to improve teachers’ digital literacy. The study is designed to find whether teachers’ awareness of using modern digital resources is raised and competence in using digital resources in classroom is improved. And the result shows that the teacher can benefit from self-study to improve the awareness and competence of using technology.

Keywords: digital literacy, self-study, continuing professional development

1. Introduction Technological innovation is changing the way we teach, and is creating new methods of education, expanding access and democratizing knowledge at a great pace. The web and current digital tools offer greater opportunities for information seeking and knowledge creation, but they also pose challenges. The literature on digital literacy focuses on developing critical and discerning abilities in the students and providing up-skilling for the teachers (Milton & Vozzo, 2013). Therefore, there is an increasing emphasis on teachers’ digital literacy. Andema, Kendrick & Norton (2013) suggest that ICT policy should address teacher educators’ use of digital technology across diverse sites, and that innovations such as the eGranary portable digital library might be particularly useful in poorly resourced educational institutions. Jeffrey (2013) suggests in their study that collaboration reduced obstacles of digital literacy development and enabled participants to develop new approaches to learning and experienced personal growth. Watson & Preston (2003) propose a networked learning community approach to sustain teacher ICT professional development. As in the field of language education research on how teachers can improve their digital literacy to better student’s language learning is few. This article is about how a language teacher improves her digital literacy to better facilitate her students.

2. Defining Digital Literacy Among twenty-first century skills, the ability to engage with digital technologies, is considered to be at the heart (Dudeney, Hockly & Pegrum, 2013). Paul Gilster ook a broad approach to digital literacy defining it as‘ the ability to understand and use information in multiple formats from a wide range of sources when it is presented via computers’ (Gilster, 1997). In literature, the definition of digital literacy is complex and is greatly influenced by the technological development. The Joint

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Information System Committee (JISC) defines digital literacy as “those capabilities which fit an individual for living, learning and working in a digital society” (JISC, 2011). While the European Commission describes that “ Digital Competence can be broadly defined as the confident, critical and creative use of Information Communication Technology (ICT) to achieve goals related to work, employability, learning, leisure, inclusion and/or participation in society. (European Commission 2003). Digital literacy is an ambiguous term, and it is more appropriate to talk of digital literacy (Belshaw, 2011). DigEuLit project conceived of digital literacy as ‘the ability to plan, executeand evaluate digital actions in the solution of life tasks’ and ‘the ability to reflect on one’s own digital literacy development’ (Marton,2003) as being an important aspect of digital Literacy, propelling the term into a level much higher than mere competence (Lankshear & Knoble, 2006).

In this article the researcher understands digital literacy in the field of EFL education as awareness of using modern technologies and the specific skills of searching, editing, creating and evaluating proper digital information to be used in EFL classroom.

3. Research Methods This is a self-study research that sought to document how the researcher, a frontline English teacher in a low-tech environment, raised her awareness and improved her competence of using technology to improve her students’ listening proficiency and experience professional development. It adopts a developmental portfolio self-study method. The context of this study is this: 39 English majors in a listening class; the classroom is equipped with computers and a projector; the Internet is accessible, though sometimes very slow; after few weeks, the teacher found herself “burnt out” and pondered “how can I make the class more active and enjoyable”. Then Su worked with a critical friend Jeanna, an American, who would like to help. They together began to establish their portfolios which include journals, evaluations from critical friend, students’ feedback, lesson plans and class videotapes. The data were collected at the beginning of the school year 2012.

The investigations were guided by the research question “how can the teacher use digital technology to make the class enjoyable?” All data were classified into internal and external imperatives. Internal imperatives include two subcategories: attitudes and awareness. External imperatives include five subcategories: competence of searching, which is about the content, the searching tools, and the strategies used to find what you need; competence of evaluating, which is about the reliability and relevance of the information; competence of creating, which is about the creative use of these digital information and to create new ones; and ethical use of digital information which is about giving credit to the author and the sources.

4. Research Findings This study found that the teacher’ digital literacy is improved through self-study. First, her attitude of using technology is changed, and her awareness of using modern technology in the classroom is strengthened. Second, the overall competence of using digital technology is improved.

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4.1. Attitude and Awareness of Using Digital Technology as Internal Imperatives The data show the two teachers’ attitude of using technology is changed. As Su states in her journal: “ I need to change my view of using technology. It is not as what I thought before. Using technology in my class is great. The students showed greater interest in watching a TED talk that I downloaded from the internet”. Jeanna’s comments on Su’s attitude of using technology in classroom: “I am very glad that you finally changed your mind, and don’t believe it time wasting or distracting students”; “I am amazing that you are so keen now to use the Internet for materials.”

4.2. Competence of Using Digital Technology as External Imperatives Their overall competence of using technology is improved. Su wrote in her journal “Today we are going to talk about reduced sound. And I am happy that I found a talk by Kelly from TED.com in which she uses so many reduced sounds. goggle search engine does not work today. But I finally find a piece of News on ‘China’s stock market had a bad day’ which can be used as a warming up exercise.” “Today I joined Cambridge Teacher Community, which provide English teachers resource. I love this website. It is of great help.” “It’s a pity that we can not open Youtube here in China”. Through her journal, there are quit a lot such statements which show her improvement on the competence of searching and evaluation. Jeanna’s comments also indicate the improvement, like “... and the piece of news you use in class is great.” All the pictures, videos, pieces of news, and other materials Su used in her class, were marked with its sources. Her ppts, lesson plan material wherever there is quotation or things from others, she gives credit to the source or the author. This shows her ethical use of digital information.

Her competence of searching, evaluating and ethical use of digital has greatly improved. But the competence of creating is not obvious, as what Su notes “Scroop it provides some tools of creating videos, such as Jing and Snag it. But I hate to create new ones. I am not a technology expert. I am slow in technology”. This shows her fear of creating new videos using digital tools.

To sum up, through self-study, they understand themselves better, their teaching better, and their students’ learning better; They investigate their own questions situated in their particular context; They develop their practical knowledge of using technology in their classrooms; And they become more confident in using technology in teaching; They even flip the classroom and improve the transmission of knowledge in the new era. The findings show that their digital literacy in terms of awareness and competence is improved through self-study. This, in turn, is a sign of improvement in professional development.

Improving digital literacy and promoting continuing professional development is like the process of building up a pyramid. It is changing all the time with the innovation of technology and development of society. So there is no one-fit-all policy. But self-study does provide teachers a new and practical paradigm, especially for frontline EFL teachers to solve their own practical problems in their particular context. But self-study research itself is changing and developing. EFL teachers should be sensitive to change and keep pace with change to become a life long learner and to educate life long learners.

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Reference: Andema, S., Kendrick, M.& Norton, B.(2013). Digital literacy in Ugandan teacher education: Insights from a case study, Reading & Writing 4(1), Art. #27, 8 pages. http://dx.doi.org/10.4102/ rw.v4i1.27 Belshaw, A.J. Donglas. (2011). What is digital literacy? A pragmatic investigation.A thesis submitted in 2011 to the Department of Education at Durham University by Douglas Alan Jonathan Belshaw for the degree of Doctor of Education (Ed.D.). http://creativecommons.org/ publicdomain/zero/1.0/ Dudeny, G., Hockly, N. & Pegrum, M. (2013). Digital Literacies. Research and Resources in Language Teaching at www.Pearson-books.com European Commission. (2003). eLearning: better eLearning for Europe. Luxembourg. Gilster, P. (1997). Digital Literacy. New York: Wiley. JISC. (2011). ALT: Developing Digital Literacies. Retrieved from http://www.jisc.ac.uk/whatwedo/ programmes/elearning/developingdigitalliteracies/alt.aspx. Lankshear, C. & Knobel, M. (2006) New Literacies: Everyday Practices and Classroom Learning Maidenhead: Open University Press. Martin, A. (2005). ‘DigEuLit-a European framework for digital literacy: A progress report’. Journal of eLiteracy, 2(2). Milton, M. & Vozzo, L. (2013). Digital literacy and digital pedagogies for teaching literacy: pre- service teachers’ experience on teaching rounds. Journal of Literacy and Technology, 14(1), 72-97. ONU-ITU (2004) .Report on the Geneva phase of the World Summit on the Information Society Geneva-Palexpo.World Summit on the information Society. Geneva 2003-Tunis 2005, p. 4. Watson, G. & Preston, S. (2003). A networked learning community approach to sustain teacher ICT professional development. Australian Journal of Educational Technology, 19(2), 227-240.

320 EITT 2013, Williamsburg, VA, USA, November, 2013 Tao, C., Yan, Y., Zhang, J., & Yang, Juan. (2013). TrackVis: track and visualize learners’ activities in an online learning rnvironment. Proceedings of International Conference of Educational Innovation through Technology, 321-330.

TrackVis: Track and Visualize Learners’ Activities in an Online Learning Environment

Congwu Tao Virginia Tech Email: [email protected]

Yu Yan Pennsylvania State University Email: [email protected]

Jianqiang Zhang Virginia Tech Email: [email protected]

Juan Yang Tsinghua University Email: [email protected]

Guoqiang Cui Yantai University Email: [email protected]

Abstract: Tracking and visualizing learners’ activities in an online learning environment is of importance to the instructors, learners and educational researchers. The purpose of this study is to design and develop a plugin tool that tracks learners’ activities and create visualizations of those activities based on clickstream data in an online learning environment. The goals of the plugin tool include: 1) provide instructors with a means to see the patterns of learners’ interact ion with different learning materials and peers; 2) offer learners a tool to show how progression they make compared with their peers during the process of study in the online learning environment; and 3) supply the educational researchers a tool to see the learners’ interaction patterns through an online learning environment. In this study, the design and development approach will be employed and a prototype of the plugin tool will be designed and developed. This paper just focuses on the first phase of the project—the design and development of the tool—“TrackVis”, and does not cover the second phase, which is a case study conducted in a large research university.

Keywords: learners’ activity, track, visualize, online learning, online learning environment

1. Introduction Learning management systems (LMS) such as Moodle and Sakai have been used widely throughout the world. The learners’ activities like asking questions, getting involved in a forum, communicating with peers, etc. are very important for researchers who study online environment (Hardless & Nulden, 1999; Helic, Maurer, & Scherbackov, 2000). Although generic LMS are

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 321 Proceedings of International Conference of Educational Innovation through Technology very effective in delivering online courses, they provide very limited help for instructors to gain understating of the cognitive and social processes in the online course. For example, questions like “Did the students access the whole course materials and if they did, when?” or “Does a student participate in the online discussion regularly and how?” are very difficult to answer appropriately (Mazza & Botturi, 2007).

In fact, most of the LMS lacked comprehensive functions to track, analyze and report students’ online learning activities (Zhang, Almeroth, et al., 2007). Hijon & Carlos (2006) also claimed that the built-in student tracking functionality in the LMS is far from satisfactory. Of course, there are several similar projects focusing on visualizing certain kinds of students’ activities data in LMS such as CourseVis (Mazza & Dimitrova, 2004), Moodog (Zhang, H., K. Almeroth, et al., 2007, 2010): CourseVis utilized information visualization and graphical representation techniques to display log files data from WebCT, and its main goal was to raise teachers’ awareness of the social behavior and cognitive aspects of online learners; Moodog used the logs from Moodle website and was integrated into Moodle as a plugin, and its goal was to provide graphic interface to help instructors to get important insight into how students were accessing online course materials. In addition, The TrAvis tool (May, George, at.el., 2011), which was designed to enhance online tutoring and learning activities, particularly dedicated to assist both tutors and students in the task of exploiting tracking data of communication activities throughout the web-based learning process. Jyothi, McAvinia, et al. (2012) did a research about designing a visualization tool to aid the analysis of online communication based on a day-to-day dialog by teachers or forum moderators to review the development of a discussion from Moodle. Wang, Wu, et al. (2013) developed visualization tool to make thinking and learning in a problem context visible and to connect problem-solving and knowledge-construction activities throughout the learning process.

However, all of the related researches just focus on log file data, and few researches made use of the clickstreams data(includes server log data and client data) to track and visualize learners’ activities from instructor, learner and educational researchers’ perspectives in an online learning environment based on the literature review. In fact, the clickstreams data are very signification representing students’ behaviors in LMS, and it is also significant to combine the multiple perspectives from students, instructors and educational researchers on learners’ activities to improve LMS.

Our hypothesis is that the visualization based on clickstream data can better offer instructors and educational researchers a comprehensive understanding on how learners interact with different learning resources and peers, and how they make progress compared with their peers during the process of study in an online learning environment, to what extent is the students’ academic performance related to their learning activities online.

2. Research Context and Related Work Clickstream is described as visitors’ paths through one or more websites, and the clickstream data is usually collecting sessions in a website (A session is a series of WebPages requested by a visitor in a single visit) ( Lee, Podlaseck, et al. ,2001). From Lee’s perspective (2001), clickstream data could be derived from raw page requests and the associated information like timestamp, IP address, URL, status and cookie data. Clickstream data could be considered as a very rich source

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of information, because they contain behavioral information of the web site visitors. Tracking the clickstream data could provide information about the sequence of pages or the path viewed by users as they navigate a website, and the path data may contain information about a user’s goals, knowledge, and interests (Montgomery, et al., 2004), as well as help to understand client’s behavior, and enhance web page usability by personalizing thawed page toward a specific user experience (Al-Lawati, Al-Hosni, et al., 2011).

In other words, a click stream is the recording of the parts of the screen which a computer user clicks on while browsing the website or using another software application, and click stream data could record the interaction between clients and the elements in the visited WebPages such as recording the name, value webpage elements and spent time on them. As a user clicks one webpage, the action is logged on a client or a web server. However, the server logs are restricted to a limited number of attributes like the IP address of the host, the date and the time of the request, and the request type. Most client interactions happening at the client side like typing in a textbox, selecting or unselecting radio button, checking or upchucking a checkbox, and hovering over a textbox are not recorded in the server logs (Khasawneh, Al-Salman, et al., 2012).Therefore, just tracking the data from the server logs is not enough, although the server logs covering the users’ action records come from the clickstreamdata; one server log does not include all of the front-end users’ data, and may record some issues of the server itself which are unrelated to the users’ browsing.

Based on the literature review, there are some studies which investigates server logs data, but few combine the client data and server log data together to track students’ activity (Hijon, Carlos, 2006; Mazza, & Dimitrova, 2004; Zhang, Almeroth, et al., 2007; Jyothi, McAvinia, et al., 2012).The client data can be session-level data and click-by-click data, some researches focus on web-browsing behavior with session-level data, but these aggregate data are quite different from the page-level clickstream data since the sequential information could be lost in session- level while the data in the click-by-click level is retained (Montgomery, et al., 2004), especially in the LMS, the sequencing data interacting with users dynamically are crucial (Dimitracopou- lou, 2005; May & George, 2011). Some third-party tools like Google Analytics and SAS Web Analytics tool are used to help analyze and visualize the clickstream data in some e-commerce companies. But these tools are not easy to be integrated into a LMS, and privacy is also an issue when trying to employ these tools for most students and instructors in the name of instructional purposes (May & George, 2011).

As we can see from the above table, in the online-educational field, most of the current tools focus on using the server log data to visualize for teachers, only a few are accessible by students or students just receive very limited support in visualizing and analyzing their own online activities. In this research, session-level data and click-by-click data, including the client side and server side will be combined to carry out a tentative research tracking the students’ online activities and visualizing the data indicator at a conceptual level, not only for teachers, but also for students.

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Table 1. The typically exiting tools for tracking users’ activities online Name Data Target Main characteristics source users CourseVis (Mazza & Server Log Teacher Visualize log files data from WebCT, and raise teachers’ Dimitrova, 2004) awareness of the social behavior and cognitive aspects of online learners ARGUNAUTTool Server Log Teacher Display the links of discussions between users in a tree- (2007, De Groot et al.) form Moodog (Zhang, Server Log Teacher, Use the logs from Moodle website and provide graphic Almeroth, et al., 2007, Student interface to help instructors to get important insight into 2010) how students were accessing online course materials TrAvis tool (May, Server Log Teacher, Track and visualize the data of students’ communication George, at.el., 2011) Student activities throughout the web-based learning process VTool (Jyothi, McAv- Server Log Teacher Visualize the students’ online communication based on a inia, et al., 2012) day-to-day dialog from Moodle V-PBLE (Wang, Wu, et Server Log, Teacher Use a dual-mapping cognitive tool to visualize and al., 2013) Survey integrate problem-solving and knowledge-construction processes

3. TrackVis: Design and Development 3.1. Design Approach An iterative approach has been used during the design of the tool. As a technological tool, TrackVis enables teachers and students to directly access the visualization of the tracking data of online students’ activity via a graphical interface. For teachers, TrackVis provides tools to monitor an individual or a group of students via their online activities. For students, TrackVis works as a “reflective tool” to assist them in gaining insights on their online activities compared with their peers through tracking and visualizing their online activity data. Another aspect needing to be considered is that the users might have different backgrounds and experiences, it is crucial for us to consider a guideline for that in the process of design, so as to make the tool more accessible, flexible and customizable to users with limited technical skills.

Two important aspects we will focus on: 1) the design of data indicators; and 2) types of visualization. In fact, on the one hand, we want to extract more useful data on students’ online activities to track and visualize; on the other hand, we also want to make the visualization of data indicators more conceptual for the users. For the conceptual purpose of visualization, we will integrate Mangenot’s research efforts (2008), who proposed four levels of user interactions: aggregations, discussion, cooperation and collaboration in a learning situation. The aggregation level refers to the activities of an individual user, and the collaboration level refers to the collaborative activities of a small group of users. For the data indicator visualization, we will allow the users to choose different variables like time, browsing courses, reading or replying messages to show different visualizing results based on data that are more interesting to them.

3.2. The Components and Procedure of TrackVis Figure 1 displays a simple version of the components of TrackVis, which contains the different parts like data collections, data process, data analysis and data visualization. Figure 1.The components of TrackVis

324 EITT 2013, Williamsburg, VA, USA, November, 2013 TrackVis: Track and Visualize Learners’ Activities in an Online Learning Environment

In the phase of data collection, we will record any URL and clicking events. The data will be classified into categories for database storage: clickstream-based and time-based. For instance (Figure 2): the following URL data can be divided into different parts before being stored in the database (Figure 3).

41521390 2013-09-01 00:25:42 2.111.94.18 Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_5; en-us) AppleWebKit/533.19.4 (KHTML, like Gecko) Version/5.0.3 Safari/533.19.4 “http://www.vt.edu/welcome/” “https://www.google.com/#sclient=psy-ab&hl=en&source=hp&q=va+state&pbx=1&oq Figure 2. The URL data

Variables Information Visitor Identification 41521390 Number Date and time of visit 2013-09-01 00:25:13

IP Address of the system 2.111.94.18

Page URL “http://www.vt.edu/welcome/” Referral Page Informa- https://www.google.com/#sclient=psyab&hl=en&source=hp&q=va+ tion state&pbx=1”

Browser and device Mozilla/5.0 (iPad; U; CPU OS 4_2_1 like Mac OS X; en-us) information AppleWebKit/533.17.9 (KHTML, like Gecko) Version/5.0.2 Mobile/8C148 Safari/6533.18.5 Figure 3. The different elements of the URL data

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For the click-based data collection, all buttons on the webpage will have a unique id number, and the unique button id will be stored into database when clicked by users.

The data processing component will access and manipulate the data based on the users’ input data parameters. The data analysis component focuses on classifying and mining data according to the input data variables, and the visualization component is responsible for showing various data visualization.

4. Analyze and Visualize Data This section will provide some data examples of data indicators which promote both quantitative and qualitative information regarding the users’ online activities. We would like to show how TrackVis offers a new experience in visualizing and analyzing the tracking data, and we would also like to emphasize the potential benefits of the proposed data indicators to both teachers and students in the online learning environment.

4.1. Visualize an Individual User Activity For an individual user’ online activity, three different data visualizations will be presented as follows: time-based and course materials-based activities (Figure 4 and Figure 5), and visiting path-based activities (Figure 6).

Figure 4. The total report of students online activity

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Figure 5. The Course Material-based Online Activity

As we can see from Figure 4 and Figure 5, these information have been visualized: the times of logging in, the total counts of viewing, the total sessions, the total online time, the total post counts; for specific learning resources like calendar, announcements, syllabus, assignments, drop- box, forum, wiki and gradebook, the viewing counts and viewing time will be visualized by bar char and bubbles. The students’ learning activity path will be presented with a coordinate axis and a line of bubbles based on time and clicking events (Figure 6).

Figure 6. The student activity path

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4.2. Visualize a Group Work Activity For a user’s online group activities, we will focus on forum, wiki, and chatting. There can be five actions: browsing, reading, posting, replying and uploading when student using these tools. We plan to visualize the different counts of the students’ five actions in a forum, wiki and chatting, which can reflect the Mangenot’s four levels of user interactions like aggregations, discussion, cooperation and collaboration in a learning situation (2008)(Figure 7). In addition, we will visualize some content like different keywords in their posting or replying messages (word cloud visualization) which might show the users’ state of mind when they type the messages (Figure 8).

Figure 7. The Student Group Activity-Action Counts

Figure 8. The Student Group Activity-Word Cloud

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5. A Pilot Study Since this tool is not completely developed before the new semester and we also do not have a semester-long time to do an experiment to get the entire experiment data to analyze and visualize, we asked three volunteers—two students and one instructor to help do a pilot study for our current version of prototype to help us improve the usability and the utility of the “TrackVis” tool.

Based on the result of the pilot study, we get important feedback on the issues related to “TrackVis” they encountered during the experiment. For instance, one student mentioned that some visual forms of data indicators do not interpret the information clearly like “the students activity path” with a little longer time interval in the coordinate axis. One student also had a concern about the privacy online, although it might help students to discipline and improve their study by monitoring or comparing themselves with their peers. The instructor made positive comments about the tool and suggested to provide an email alerting function for late work or new posting message which the online students can subscribe to; also for instructors, an “early warning” email notification reporting with graph which flag at-risk students can allow instructors to develop early intervention strategies for the students easier.

6. Limitation and Future Work This paper just focuses on the first phase of the “TrackVis” project, and we just provide a prototype of the tool based on a design and development approach. Although we have three volunteers to do a pilot study regarding the evaluation of the function-level of the tool from the points of view of students and instructors, we do not implement an experiment to study the impact of “TrackVis” in an authentic online learning environment. In the future, we will continue to improve the tool and plan to integrate it into Sakai or Moodle, and to do a semester-long experiment to evaluate the effect of the tool on instructors and students in a real online learning environment.

References Al-Lawati, H. R., A. Al-Hosni, et al. (2011). Discovery of popular structural properties in a website for personalization and adaptation. Journal of Emerging Technologies in Web Intelligence, 3(3), 253-260. Al-Salman, R. S. (2011). Mining client side para-data for adaptive webpages, Jordan University of Science and Technology. Hardless, C. & Nulden, U. (1999).Visualizing learning activities to support tutors. CHI’99 Extended Abstracts on Human Factors in Computing Systems, ACM. Hijon, R., & Carlos, R. (2006). E-learning platforms analysis and development of students tracking functionality, in Proceedings of the 18th World Conference on Educational Multimedia, Hypermedia & Telecommunications, pp. 2823-2828. Jyothi, S., McAvinia, C. et al. (2012). A visualization tool to aid exploration of students’ interactions in asynchronous online communication. Computers & Education, 58(1), 30-42. Khasawneh, N., Al-Salman, R. et al. (2012). A generic framework for collecting and mining client paradata for web applications. Journal of Emerging Technologies in Web Intelligence, 4(4), 324-332 Lee, J., Podlaseck, M., et al. (2001). Visualization and analysis of clickstream data of online stores for understanding web merchandising. Applications of Data Mining to Electronic Commerce, Springer: 59-84.

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Mazza, R. & Botturi, L. (2007). Monitoring an online course with the GISMO tool: a case study. Journal of Interactive Learning Research, 18(2), 251-265. May, M., George, S., & Prevot, P. (2011). TrAvis to enhance online tutoring and learning activities: Real-time visualization of students tracking data. Interactive Technology and Smart Education, 8(1), 52-69. May, M. & George, S. (2011). Using Learning Tracking Data to Support Students’ Self-monitoring. CSEDU (1). Mazza R., & Dimitrova, V. (2004). Visualising student tracking data to support instructors in web- based distance education. NewYork, NY: ACM Press, 2004, pp. 154-161. Mazza, R. & Botturi, L. (2007). Monitoring an online course with the GISMO tool: A case study. Journal of Interactive Learning Research, 18(2), 251-265. Montgomery, A. L., S. Li, et al. (2004). Modeling online browsing and path analysis using clickstream data. Marketing Science, 23(4), 579-595. May, M., & George, S. (2011). Using students’ tracking data in E-learning: Are we always aware of security and privacy concerns? 10-14. doi:10.1109/ICCSN.2011.6013764 Zhang, H., K. Almeroth, et al. (2007). Moodog: Tracking students’ online learning activities. World Conference on Educational Multimedia, Hypermedia and Telecommunications. Zhang, H. & Almeroth, K. (2010). Moodog: Tracking student activity in online course management systems. Journal of Interactive Learning Research, 21(3), 407-429.

330 EITT 2013, Williamsburg, VA, USA, November, 2013 Xu, W. & Zhang, J. P. (2013). Information technology used in environmental education in China and its cases study. Proceedings of International Conference of Educational Innovation through Technology, 331-342.

Information Technology Used in Environmental Education in China and Its Cases Study

Wei Xu, Jianping Zhang Zhejiang University Email: [email protected], [email protected]

Abstract: Environmental education aims to cultivate environmental awareness, exalt environmental moral realm, and improve behavior patterns of citizens. We are expecting to ease environmental stress through joint efforts by all walks of life, thus to promote the harmonious development between human society and natural environment. Recently, integrating information technology into the curriculum in China has made an encouraging progress, especially in improving learners’ learning efficiency and knowledge integration. This paper claims that deeply integration between information technology and environmental education can not only benefit the popularization of environmental education, but also set up a network platform for effective teaching with much more collaborative and asynchronous. By use of information technology, we can form various learning communities across regions and nations, and carry out theme-based teaching activities. Therefore, it will effectively promote to reach our goals. This study is based on case study method, classifies three integration formats between information technology and environmental education: subject-based learning website, online learning platform, and the virtual-actual fusion collaborative environment. With concrete cases introduced in China, this paper will represent the present implementation situation of environmental education in China, analyze advantages and disadvantages among them, and then indicate research directions of environmental education in the information society.

Keywords: information technology, environmental education, subject-based learning website, online learning platform, the virtual-actual fusion collaborative environment

With rapid development of modern society, people’s life-style has been changed a lot, meanwhile, it has brought unprecedented pressure on the natural environment. Because some people were lacking of environmental awareness, lots of human behavior have caused certain pollution and damage on environment. As a result, the increasing environmental problems are doing harm for human survival and sustainable development. The first nationwide “Public environmental awareness survey results” in China was launched in 1998. It revealed that attention degree toward environmental protection、view of nature and environmental behaviors among youngsters are a little better than adults, and their 70.3% of environmental protection knowledge were learnt from school, environmental education in school has been their first way to acquire knowledge. Therefore, environmental education in school has important effect in cultivating environmental awareness, exalting environmental moral realm, and improving behavior patterns of citizens, then it is the key to solve environmental problems (Fang, 2001).

Our society has come into 21 century. With a wide range of internet popularization, mass media has greatly changed the mode of human knowledge acquisition. Statistics of “The Chinese public

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 331 Proceedings of International Conference of Educational Innovation through Technology environmental awareness survey” in 2007 has indicated that 81.8% of the public channels to get environmental knowledge are mass media, such like broadcast and TV. Otherwise, environmental education in school has only 10.7%. And now, knowledge dissemination is mainly depended on internet, information technology is replacing broadcast and TV and playing the main role in environmental education. However, the quickly information update online may mislead youngsters while lacking of right guidance. How can we quickly find and identify the right one which is authoritative and reliable in the massive information?

In China, environmental education should be popularized among youngsters and adults. On the other side, the massive online resources may lack of effective guidance. According to the current situation in China, we consider that environmental education should still follow the control of formal education in school, in order to reach our goals effectively. In addition, instructors should also make full use of information technology, bridging the knowledge in books and online, and form widespread learner communities. By this way, integrating information technology into environmental education can carry out various teaching activities, which are much more comprehensive, independent, and always learner-centered.

1. Overview The concept of “environmental education” was firstly proposed at “Human Environment Conference” at Stockholm in 1972 (Cui, 2007). The Tbilisi Conference in 1977 has defined “environmental education” as an interdisciplinary curriculum belongs to education field, directly aimed to problem solving and local environmental reality. There are kinds of educational process including formal, professional and in and out school (Wang, 2003). Since then, International environmentalists and organizations have frequently promoted international conferences and topic seminars. Proposals and implement compendiums of environmental education are well developed. And the ideas, framework and system of environmental education are gradually formed ( Liu, 2000).

Environmental education all around the world was rapidly expansion in that time. For example, in Japan, environmental education was derived from “Nuisance Education” in early stage, and the policy was made by MEXT (Ministry of Education, Culture, Sports, Science and Technology), which has organized a good number of primary and secondary schools to develop environmental education from top to bottom through interaction among curriculums, which was paying close attention to promote subject studies with activity surveys based on students’ direct experience. In order to popularize among different social groups, environmental education in Japan is not only taken in schools, but also among enterprise, communities and medium publicity (Cao, 2010). The United Kingdom as the pioneer in environmental education around the world, has seen environmental education as an important approach to develop moral education, and paid more attention to synthetically practice among students. In the 1970s, there have built more than 350 teaching bases for environmental education Scotland and wales which are for students to learn outside and conduct practice activities (Feng & Dong, 2010). Germany which is one of the best environmental quality countries has partly benefited from successfully implementation of environmental education. Almost all of the curriculums in primary and secondary schools have been penetrated environmental education. There are fixed teaching time outside every week, in order to guarantee the effective implementation of environmental education. Otherwise, several

332 EITT 2013, Williamsburg, VA, USA, November, 2013 Information Technology Used in Environmental Education in China and Its Cases Study organizations such like Museum of Natural History, colleges and universities and national park, are working closely with schools. They are jointly carrying out teaching activities, attracting much more students to participate in (Li & Chai, 2011).

Environmental education in China has been started in 1973, firstly proposed in the National Environmental Protection Conference. “The National Environmental Publicity Education Executive Summary (from 1996 to 2010)”, which was printed by State Bureau of Environmental Protection, Central Propaganda Department and State Education Commission in 1996, has embodied the basic environmental education (non-environmental specialty), professional education (environmental specialty), training among Party and enterprise into the environmental education system. In addition, Project GLOBE between China and Unite States is enrolled in the international partnership programs which are the key implementation. The first Executive Summary has preliminary planned an objective of the environmental education system, but it didn’t make full use of social resources, or integrate with practice in our lives. Environmental education was limited in books, and relied mainly on propaganda and education by the Broadcast and TV. Furthermore, the level of informatization in China is far less than international level in the beginning of 21st century. For example, there was not effective cooperation in project GLOBE and other international partnership programs. Because of some factors such as lacking of the government funding and consideration, imbalance development of environmental education system, and regional difference, the implementation situation of environmental education in China is not too optimistic. Fifteen years later, in the second Executive Summary, there is paying much more attention on public participation, universal coverage and connection with international organizations, environmental institutes and research institutes in the second Executive Summary. On the other hand, a series of propaganda projects for environmental education is promoting to develop environmental education activities based on practical issues with new theories and innovative approaches. Teaching and learning in classroom are extended into our real lives.

With the guidance of the Chinese government, successful experiences abroad also have afforded lessons for environmental education in China. Three development tendencies of the future environmental education can be given as follows according to the current situation of educational system in school and implementation of information technology.

• Construction by all people, practicing and sharing together; Once upon a time, the responsibility of environmental education was mainly belonged to schools. Teachers have integrated environmental education into their curriculums. For example, students were taught with the composition of sulfur dioxide in chemistry. And then teachers may take acid rain for example. In future, construction of environmental education will be depended on all people; anybody can freely get environmental knowledge, and participate in the process of environmental education. In the construction process, people may exalt their environmental moral through knowledge integration and practice activities.

• Deeply cooperative, stimulating the enthusiasm of communication; In the second Executive Summary, it has emphasized the connection among international organizations, institution and universities. Cooperative inquiry based on themes is the best way to form learning community, which involving students, teachers, researchers and scholars in

EITT 2013, Williamsburg, VA, USA, November, 2013 333 Proceedings of International Conference of Educational Innovation through Technology universities. Learning community can promote to carry out inquiry learning based on the same theme, and always problem-oriented. People with different special skills or knowledge can mutually make up. Learners will be under the right direction for problem-solving. Teachers also can ask for professional knowledge from researchers. Scholars also can guide the whole activity with advanced theories. It is a mutual interaction that can benefit for each other.

• Building a learning resource portal organized by nodes, and filtering massive information In the network era, an excellent instructional designation should be by use of network resources. However, massive information online has always misled learners, as a result of reducing learning efficiency. George Simons, a Canada scholar, have proposed the connectives theory in 2004. He said that learning online was actually the connection process through knowledge nodes represented by people. One person is the collection of professional knowledge. When we are searching for some professional knowledge, we should just need to find the person who has possessed this knowledge among knowledge nodes. The “Six Degrees of Separation” has confirmed the fact that any two persons can be connected by six links. Therefore, learning resource organized by knowledge nodes can promote the formation of learning community. In the web-like relationship, people can extend communications with much more “nodes”, and also improve their searching efficiency. It will be the bases of adaptive learning with efficiency learning.

2. Conjunction between Information Technology and Environmental Education Education of information technology in China has started with the experimental study of Computer Assisted Instruction in the early 1980s. It has experienced separate curriculum period and curriculum integration period in different time. In the recent years, information technology represented by internet technology is rapidly developed, led to the much more attention on instructional usage of hypermedia and rich media. Information technology as a separate curriculum has broken the bulwark of different curriculums, and been integrated into these curriculums. It has greatly changed traditional teaching methods. As a result, the deeply integration between information technology and the curriculum will be the inevitable tendency in future (He, 2005). Scholars in Beijing Normal University have divided the integration modes into three stages and ten levels. The three stages are respectively claimed as closed, knowledge-centered integration; opened, resource-centered integration and all-direction integration. The third stage includes revolutions among curriculum content, instructional objectivity and teaching organizational structure (Ma & Yu, 2002). Informational technology has constructed a new teaching & learning environment which is characteristic of interactive, hypertext present and asynchronous. In this environment, multiple teaching and learning methods such as creation context, thinking inspiration, information acquisition, resource sharing, mutually interactive, independence investigation, and cooperative learning can be realized. The new instruction & learning method can not only help teachers to play a leading role, but also reflect the students’ dominant position, and be characterized with autonomous learning, collaborating learning and inquiry learning (He, 2005).

As mentioned above, environmental education and education of information technology have some similarities. Firstly, both were experienced separate curriculum period and curriculum integration period. Deeply integration will be the future development tendency between both of them. Secondly, the knowledge structures both are cross-disciplinary. For example, environmental education needs knowledge of chemistry, biology and history. Meanwhile, education of information

334 EITT 2013, Williamsburg, VA, USA, November, 2013 Information Technology Used in Environmental Education in China and Its Cases Study technology should be under the help of mathematics and computer science. Last but not the least, both educational objectives are development in all-round including understanding, emotion, willpower, and action. The environmental education is finally expected to alleviate the pressure of social environment, and cultivate problem solving ability. Then we will effectively avoid environmental pollution. The objective of information technology education is to foster life-long learning ability. In the future, we will live in a learning society. It is much more important for us to use information technology adequately to solve real problems in our life and works.

Just because of these similarities of development tendency, knowledge structure and educational objectives, this paper claims that the integration between information technology and environmental education not only benefits for the popularization of environmental education, but also builds the platform to form learning community with carrying out inquiry activities. Finally, the goal of environmental education can be effectively reached.

3. Case Study As mentioned above, the integration between information technology and curriculum has three stages, which are knowledge-centered, resource-centered and revolution-centered. This paper will base on the three development tendencies analyzed above, which are respectively all people involvement, deeply cooperation and resource website organized by nodes, and classifying three integration modes between information technology and environmental education. In the following, with some specific cases, we will introduce these modes in detail.

3.1. Subjects-Based Learning Website Subject-based learning website was identified as a kind of resource portal online centering on some specific subjects, which is expected to support the extensive inquiry learning. With the help of subject-based learning website, students’ innovation ability and practice ability can be well developed, and the comprehensive quality of collecting, analyzing and processing information in the information era will also be promoted (Zheng, 2002). Professor Li Kongdong in China has firstly proposed the learning mode of “thematic exploration and website development” in 2001. It was fully reflected the advantage of integration between information technology and the curriculum, promoting students’ learning attitude, practice ability and knowledge acquisition (Xie, Yu, & Yin, 2004).

It is the first stage to build themed learning website on environmental protection. Professional staffs are organized to collect and classify knowledge on environmental protection, and build reliable and authoritative resource center, in order to support learning activities among students and social learners. On the one side, it can offer authoritative information for students in school. On the other side, it can popularize environmental knowledge in the social scope by use of the opening internet, and then improve citizens’ environmental awareness.

The Chinese Public Science and Technology Network was officially opened in 1996, which is sponsored by China Society and Technology Association. It is reviewed by authoritative experts, providing high-quality navigation and recommendation service for the public. And there are 36 domestic environmental navigations. For example, the website of China Popularization of Science (http://www.kepu.gov.cn/index.htm) is sponsored by the National Science and Technology

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Department Policies and Regulations and System Reform Department, whose main targets are teenagers, aiming to publish and popularize scientific and technical information to the whole society. “The Science Squirrels” (http://songshuhui.net/), a non-profit organization with the slogan “Let’s peel nuts of science”, is composed of excellent Chinese science communicators both home and abroad, who are devoting themselves to communicate science in the mass culture level. The EarthView (http://www.earthview.org), which aims at promoting sharing building of environmental education resource, is an environmental film database including international excellent environmental education films which are imported by scientific research institutions.

This paper takes the environment library in the Chinese Science Expo for example (seen in figure 1), which is a virtual museum used to spread scientific knowledge. It will introduce the knowledge structure and some features to carry out environmental education.

Figure 1. The Chinese Science Figure 2. Knowledge structure of Expo: environment library the environment library

The Chinese Science Expo is a large science website which the basic information database is mainly from scientific databases of Chinese Academy of Sciences. Environment is only a theme in it. Because of the cross-disciplinary feature and closely connecting with real life, knowledge structure of the library adopts the organization model from bottom to up, seen in figure 2.

Firstly, it introduces several basic environmental concepts referring to different subjects, such as environmental elements, biologic chain and earth resources. These concepts will help learners form a basic framework, and clarify the relationship among these concepts. Secondly, there are some columns to introduce the reason of environmental problems, something like the excessive discharge after the industrial revolution. Thirdly, by presenting typical environmental problems in the world, it focus on the situation in China, respectively analyzing the urban environment, rural environment and tourist area environment which is drawing much more attention. At last, environmental protection is elevated to sustainable development, aiming at cultivating citizens’ environmental awareness; and even involving their philosophy, world view, and values.

And mentioned above, students and learners in society can all use this subject-based website to extend their vision, and improve their own knowledge structure. As a result, we can finally reach our environmental education objectives. Students in school will follow the navigation of website, learn the basic concepts to practice problem, and improve their own knowledge structure. And learners in society can choose what they are interesting, to explore and extend vision.

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The building of environment-themed website is the aggregation process of resource; meanwhile, it is the way to popularize knowledge in a large scope. It is impossible to guarantee the reliable and authoritative of information resource. On the other hand, instructional strategy used to promote effectively learning is also the necessary supplementary. For example, the bottom- up mode for knowledge organization can improve students’ knowledge structure step by step. However, subject-based learning website doesn’t possess complete function for integration with curriculums.

3.2. Online Learning Platform The rapid development of web technology has caused great change in education field. Carrying out online learning based on some open-source platform such as Blackboard and Sakai is becoming very popular. With the perfect function components and the idea of open sharing, a great number of scholars and instructors are paying attention on it. In recent years, most universities and schools have brought these learning platforms in, and carried out kinds of online learning in a new network learning environment. Some research suggest that by using of these perfect function system and mature online platform to implement online learning, can not only create advantageous condition for teachers to design inquiry learning, but also enhance the guidance of teachers in online activities. For students, it can inspire their learning interest, improve their enthusiasm, and have positive effect to cultivate their spirit of innovation, self -designed capacity and autonomous learning awareness (Cen, 2009; Li & Shan, 2010).

Professor Li Yan in college of education of Zhejiang University has promoted an online learning project on environmental-themed which was cooperated with some scholars of Italian media association. The Italian scholars have recommended an online learning platform named EduLife, and transformed it for Chinese using. With the help of EduLife, professor Li has carried out series learning activities in the ICT course on environmental-theme in three to five grades of four elementary schools in Zhejiang province. EduLife is an online learning platform which is similar to course management system, involving of five function modules. The platform interface is seen in figure3.

Figure 3, The platform Figure 4, Teaching activities interface of EudLfie

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• Course Module: designed for presenting content of courses, in PPT of FLV; • Deepening Module: designed for providing students with extra multimedia materials or Internet resources; • Dialogue Module: designed for promoting synchronous or asynchronous communication, and can upload the video or audio which are real-time recorded; • Online Activity Module: designed for learning interaction and uploading learning products; • Reflection Module: designed for reflecting or evaluating students’ learning process and outcome.

These simple modules are enough for us to develop online learning. With the closely collaboration between researchers and instructors, blending learning environment of online communication platform and open instructional resource is well constructed. These online learning activities are designed for cultivating students’ abilities of using information technology to solve problems. And they were almost launched among different classes, regions and schools. For example, some autonomous learning activities like drawing digital painting, reading advertisement online and searching for relevant news, students can collect information of environment accurately and effectively with the guidance of instructors. Above that, students can be fully understanding of environmental protection, further creating their own products. And the module for “I can offer suggestions for environmental protection” has employed Webquest which is an inquiry model designed for learning online. Throughout these autonomous learning activities with internet resource, students will propose some solutions, which is benefit for enhancing their problem solving ability in the process of presenting, presentation and modifying. “Environmental Got Talent” is organized to do brainstorms in groups. With the collective intelligence, students are making digital stories telling us how to protect our environment. In the exhibition area, they express their own understanding and awareness in the form of products. It will further enhance students’ environmental awareness and internalize it into values.

Developing learning activities based on learning platform is the main formation to adapt the tendency of e-learning. It enriches instruction models, and inspires students’ motivation in some degree. Practical research have found that this kind of inquiry learning which is under the guidance of teachers and self-directed learning by students can effectively improve students’ self- efficiency, and promote the internalization process into their own behavior and values. Finally, purpose of environmental education which is improving moral realm can be well reached. However, because of overall level of computer network and educational informationization, popularization of online learning platform should be engaged largely both in time and financial. Digital divide among regions in China is also the obstacle for importing and absorbing informational technology effectively.

3.3. Virtual-Actual Fusion Cooperative Environment Evolution in technology has caused great transformation in learning environment. In the traditional classroom environment, teaching activities are all face-to-face and always real-time interaction. Dissemination of knowledge is mainly depended on teachers. When internet was introduced to educational field, virtual learning environment based on internet was appeared, where communications between teachers and students are not face-to-face and real-time. In this virtual

338 EITT 2013, Williamsburg, VA, USA, November, 2013 Information Technology Used in Environmental Education in China and Its Cases Study environment, we can carry out cooperative learning with support of massive internet resource. The critical thinking and innovation ability of students’ can be greatly stimulated.

In recent years, there is a debate concerning on the accuracy and effectiveness of information online. And then, the “Internet of Things” technology and wireless sensor network are developing rapidly. The new technology will realize seamless connection of things, which is drawing much more attention from scholars in e-learning. Professor Zhang Jianping of Zhejiang University is proposing a concept of “Virtual-Actual Fusion Cooperative Environment” based on the IOT (Internet of Things) application. It is identifies as blending the sensors, front-end equipment in real life into the virtual environment which is consisted of network and multimedia, thus to construct a virtual-actual fusion cooperative environment that is benefit to inquiry learning carried out by learners.

In this environment, inquiry learning can satisfy students for true feelings, and take full use of massive digital resource in virtual environment, thus developing learning and teaching. In addition, the data acquired from front-end equipment is always authentic and unpredictable. The changeable information will be in favor of cultivating students’ analytical ability in changing circumstances, and enhancing their practical ability of applying knowledge.

In response to that, the research team of professor Zhang has designed and manufactured the CEIS system, with full title of Campus Environmental Information System. The system composition is showed in figure 5.

Figure 5. The system composition Figure 6． The environmental of CEIS information portal of CEIS

• Data acquisition and data analysis: designed for acquire information data of real environment. Front-end equipment are used to receive and transfer information of environmental elements (including temperature, humidity, wind speed, wind direction, air pressure and solar radiation, noise, air quality and so on), then put them into website database for querying in the portal; • Environmental information portal: showed in figure 6, designed for presenting environmental information, service information, environmental popularization, 3D environment exhibition hall and relevant hyperlinks. The environmental information includes real-time

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information, summarized information and data analysis. There can be generated intuitive chart according to the real-time information in database, and all the chart and data can be openly downloaded in excel. • Teaching activities on environmental-themed: people can register in the management system used to carry out environmental-themed teaching. An open-source platform named Sakai is used to construct the learning environment, which is an open, shared and cooperative environment. We can develop kinds of inquiry learning activities on environmental- themed closely related with our real life.

The new-style information technology represented by IOT has constructed a virtual-actual fusion cooperative environment. It takes the real environmental situation as object, and blends it with virtual learning environment. Starting with the real information, there can be carrying out much more scientific inquiry learning which would exactly reflect practice problems. Moreover, the flexibility and innovative thinking of students will be further trained in the changing circumstance and finally attributing to cultivate problem solving ability. The virtual learning platform has provided relevant learning resource though aggregation of subject resource, resulting in improving learning efficiency. In addition, the Sakai which owns the ideal of cooperation, open and sharing can promote cooperative learning across regions with strongly supporting. Teachers who are playing the role of directors in teaching should rational utilize functional modules to benefit for their own learning and teaching. For example, the chatting room in Sakai can connect special experts, in order to answer students’ questions, providing authoritative guidance for them. The virtual-actual fusion cooperative environment possesses abundant resources which are effective and scientific, tools which are individualized and cooperative, and intelligent learning context. There will be significant advantages for implementing environmental education effectively.

4. Summary and Prospect Information technology integrated with environmental education will play much more important role in future. The cases studied in this paper are promoted by numerous scholars in different subjects, and has been developing in some degree. However, there are also disadvantages. (1)These cases are carried out in form of projects, and then promoted in a short while. They were always experienced in a certain limited scope, so the results and methods may be hardly promoted in different place and larger scope. (2) The revolution of information technology will make the environmental education much more diversity, and the focus is mainly laid on the innovation of teaching methods, representing less on the attention of basic concepts and knowledge about environment. (3) There may be lack of international cooperation because of language barriers. Environmental problem is a global topic needed to solve by all people. International dialogue may gradually enrich the form and content of environmental education.

In future, environmental education will be evolution to the education of sustainable development. The role that information technology is playing on will be more important and diversity. Teachers, experts and researchers, even with communities should all participate in it, to form the broadest learning community. Cooperative learning crossing the national frontier may be the best way to realize the goal. It needs to break multiple barriers and the joint effort among scholars in relevant subjects.

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References Cao, J. (2010). Environmental education in Japan society and its enlightenment, Journal of Hebei Normal University (education science edition), (7), 50-53. Cen, J. J. (2009). Research of blending instructional mode based on Sakai, E-education Research, (9), 52-55. Cui, J. X. (2007). Environmental education: origin, content and objective, Shandong University Journals: Philosophy and Social Science Edition, (4), 147-153. Fang, H. Y. (2001). Environmental problem and environmental education, Tangdu Journal, (S1), 229-231. Feng, Y. G., & Dong, H. X. (2010). Environmental education: the important way of moral education in Britain, Foreign Education Research, (3), 79-84. He, K. K. (2005). The theories and methods of deeply integration information technology into curriculum, E-education Research, (1), 7-15. Li, M. R. & Chai, Y. P. (2011). Overview of environmental education in German, Successful (education), (3), 4-5. Li, W. X. & Shan, Z. P. (2010). Research and practice of inquiry learning based on an online platform named Blackboard, Computer Education, (1), 66-69. Liu, J. H. (2000). History review of international environmental education development - centered on important international environmental education conference, Environmental education, (1), 38-41. Ma, N. & Yu, S. Q. (2002). Levels of integration information technology into curriculum, China Educational Technology, (1), 9-13. Wang, Y. J. (2003). Exploring and analyzing the concept revolution of “Environmental Education”, Comparative Education Review, (1). Xie, Y. R, Yu, H. & Yin, R. (2004). The effecting analysis of developmental learning mode based on project-specific website,China Educational Technology, (12), 41-45. Zheng, Z. Q. (2002). Design strategy of subject-based learning website in elementary and secondary school, E-education Research, (6), 72-74.

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Acknowledgement This paper has been sponsored by two programs as follows: (1) Science and Technology Bureau program in Zhejiang province: “Environmental Information Observation System and Its Application in Education Based on Community/Campus” (2011—2012); (2) Department of Social Cultivation Project in Zhejiang University: “Virtual-Actual Fusion Cooperative Environment and its learning activities research” (2012—2013).

342 EITT 2013, Williamsburg, VA, USA, November, 2013 Wu, F. & Shang, J. (2013). Empirical research of enterprise e-learning in China. Proceedings of International Conference of Educational Innovation through Technology, 343-350.

Empirical Research of Enterprise E-learning in China

Feng Wu, Junjie Shang PeKing University Email: [email protected]; [email protected]

Abstract: At present, enterprise E-learning is developing more and more rapidly in China. In order to understand the state of Chinese enterprise e-learning, the author of this paper investigated 30 large enterprises by a survey in 2012. This paper analyzes and discusses the data collected by the survey and reports findings of the enterprise e-learning from six aspects.

Keywords: enterprise E-learning, human resource development, China

Information technology is the characteristic of our times, which is changing all of our society. Information technology promotes enterprise learning to change, the main feature of which is the massive development and application of e-learning .At present in China; many large enterprises develop e-learning to support network training. In order to know well the state of enterprise e-learning in China, the author selects some enterprises for investigation. This study uses questionnaire and field investigation method. The first step, we collected 30 enterprises’ questionnaire. The Secondly step, we choose 10 representative enterprises for field investigation. This study proceeded from 2010 to 2011, continuing for one year.

1. Introduction of Enterprise e-Learning in China 1.1. The Main Industry That Enterprise E-Learning Grows Well There are four categories of industries which are successful at enterprise e-learning. E-Learning is broadly used in these industries and popularized among the employees. The first category is telecom, insurance and bank industry, such as China Telecom Online University, Industrial and Commercial Bank of China (ICBC), and PingAn Insurance. Their general characteristics are large amounts of employees and branch organizations, having obvious advantage on implementing E-Learning. On one hand, E-Learning saves the cost; on the other hand, it effectively enhances coverage of employees learning. For example, there are 330 thousands employees in China Telecom, and there are 1 million employees in China Post Group, so in these industries, implement of e-learning have natural advantage.

The second category is high and new technology industry, such as Ruijie Network and Huawei. First, due to rapid changing of technology, employees in these enterprises need to learn new technologies continuously, so they have urgency and strong motivation to study by e-learning. Second, Average age of employee in this industry is little, so these employees can master higher level of information technology and have stronger consciousness of online learning.

The category is foreign-funded enterprises, such as Ericsson Academy, Motorola University, Siemens Management Institute, and Novo Nordisk. E-Learning systems in the foreign-funded

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 343 Proceedings of International Conference of Educational Innovation through Technology enterprises are based on their headquarters’ systems, so they don’t need to build new learning systems in China.

The last category is airline business. Flight attendants often need to travel around the world, and should spend their spare time to learn, so that E-Learning is particularly appropriate to them. Recently, more and more airlines are successful at implementing E-Learning program. Many airlines pay attention to mobile learning (M-Learning), so M-Learning may make a breakthrough in airline business first.

Industry cluster E-learning will be one of future trends. The enterprises on the upstream and downstream industry chain or the enterprises in the same industry build enterprise universities or enterprise e-learning together. Either enterprise universities or enterprise e-learning, all of them need to have relatively large scale, so that some small enterprises could be combined to become a scale, consequently the cost of each enterprise may be reduced (Wu, 2010). In the other hand, the enterprises on the upstream and downstream industry chain can create complementary knowledge by building enterprise universities or enterprise e-learning together. Not long before, China Association of communication enterprise universities was founded in China; this is obvious signal for the development of enterprise universities.

1.2. Enterprise E-Learning and Lifelong Learning The goal of Lifelong learning is to promote personal development, social progress and economic growth. In the future, Enterprise e-learning will be the main support of lifelong learning. Research found that the training amount through e-learning may reach 60% -80% of all training amount, and now the amount of E-learning in many companies have reached more than 50%, and this ratio will be increasing by the time. We also found that in the period of financial crisis, the proportion of Enterprises which declined training is 26.6%, unchanged is 33.3%, increased is 40%, but the amount of training by E-learning for all Enterprises is rising. So we can see the importance of e-learning in enterprise training. From 2008 to 2011, The average time of Employees’ online learning grew 27% every year, and the number of online employees grew 65% every year in China. (Wu, Li, & Xiong , 2010). Thus, e-learning must behave great prospects in the future of Enterprise learning. However, compared with the rapid development of e-learning, the staffs who are engaged in e-learning are not enough.

Report of Chinese Government declared that “lifelong learning society” will be built in China. Lifelong learning means all the people learning, personalized learning, anytime and anywhere learning. The characteristics of lifelong learning are very consistent with e-learning. In fact, e-learning will become the main information carrier for life-long learning system, and now, more and more cities in China are building lifelong learning city network, such as Shanghai and Beijing established a leading cadre of online learning Centre. Whether in business or in the community, E-learning will show its potential advantages with rapid development of information society. (Ding, Gong, and Chen, 2008).

Another challenge of Enterprise e-learning is how to change the learner from passive learning to active learning. (van Dam, 2006). Basic information from the research points out, the majority of Enterprises e-learning is policy-driven; For example, some enterprises have clearly defined

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that employees must meet a number of e-learning times and a number of courses. This is typical passive learning. Beijing Cadre online learning center require that every learner must finish 40 hours’ course per year, although this policy is too rigid, but in the initial stage it is necessary. Some Enterprises are temperate, they combine the e-learning with professional career path and job competence, which drive learner’s inner interesting. For example, in education department of Industrial and Commercial Bank of China, online learning and staff professional development path are related. When new employees join in the company, the HR department will tell you about your future career development path, professional qualifications which must be acquired in your future career, and how to get these qualifications. Online learning and online examination are the way to obtain professional qualifications. Certificates valid for only two years, in order to ensure employees continue to renew their knowledge and learn continuously. Some foreign companies such as Motorola University, College of Ericsson, in which learning is real active. In such enterprises, active learning is based on the enterprise sharing culture. Sharing culture will promote the development of e-learning, on the contrary, narrow-minded, conservative enterprise culture will be an obstacle to the development of e-learning. (Business-Education Research Center, 2009).

2. Positive and Negative Factors That Affect Enterprise E-Learning 2.1. Positive Factors That Motivate Enterprise-Learning As a strong tool of Enterprise learning, E-learning has the following characteristics: E-learning provides timely feedback. E-learning has texts, images and sound in one set. E-learning costs low. E-learning is an effective tool for adult training. E-learning offers self-paced, flexible and personalized learning. E-learning provides unlimited and sustainable life-long learning. E-learning helps improve efficiency. (William Horton, 2009). The following factors show the motivation of implementing E-learning in enterprises, according to the choices of Enterprises surveyed ranking. (Business-Education Research Center,2009).

Table 1. Motivation factors of implementing E-learning in Enterprises Factors Proportion Reduce training costs 77% Improve training coverage 77% Promote knowledge management 54% Individualized learning opportunities 46% Anytime, anywhere learning, convenience 31% Flattening the Organization 8% Laythe foundation for building Enterprise University 8%

Reduce training costs. Face to face Learning costs relatively high, especially in the cross- regional Enterprise which has many branches. Using E-learning means a great saving in training costs, Such as Industrial and Commercial Bank of China have 330,000 employees and nearly 10,000 business offices across the country. The cost of E-learning is about 20-30 percentsof the cost of face to face learning.

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• Improve training coverage. In general, face to face training complies with “eighty-twenty Rule”, in other words, 80% of training funds is used for 20% personnel training, who are especially Enterprise manager, employees have little opportunity to learn. The application of E-learning changed this situation greatly, that is, training coverage reached 100%. In internet economy, marginal costs near to zero, e-learning costs of increasing an employee almost unchanged. So E-learning shifted Enterprise learning opportunities from senior staff to the grass-roots employees. • Promote knowledge management. Knowledge management is not only the core of E-learning but also the core of enterprise universities. E-learning will greatly accelerate the speed and validity of Enterprise knowledge arrangement and knowledge dissemination. • Provide employees with more personalized learning opportunities. E-learning prepares a large number of courses, employees have more opportunities to choose, who can select the interesting content, and the superior courseware. Such as the Institute of China Telecom, which have 6000-7000 courses currently, provide Individual employees considerable learning choices. • Anytime, anywhere learning, convenience. This is the basic property of E-learning; employees can learn anywhere and learn outside of the office. And also, employee can take fragments of learning. • Flattening the Organization. Flattening the Organization meet the need of Organizational Change. In some traditional Enterprises, especially state-owned Enterprises, The bureaucracy of management is serious. The Enterprise e-learning provides a platform for learningand communication. All employees including president of the Enterprise are learning and sharing online. For example, the CEO of eLong Network Co., Ltd. invested one million Yuan to purchase their own enterprise e-learning systems, named “KwongFuk on line”, providing online learning to employees. The CEO himself always logs in online system, who communicates his strategy and business development ideas with online learners in the E-learning system. • Lay the foundation for building Enterprise University. More than 80% of the world top 500 Enterprises settled up enterprise universities. Now nearly 300 domestic Enterprises settled up enterprise universities. Enterprise e-learning is a necessary condition for the establishment of enterprise universities. Successful enterprise universities pay more attentions to enterprise e-learning project, such as China Telecom Institute E-learning project, Ericsson University E-learning project are now the most outstanding (Allen, 2009).

2.2. Negative Factors That Hinder Enterprise E-Learning Some Enterprise E-learning development is still in the first stage, while some are in the second stage. According to the selection of investigation, factors that influents Enterprise E - learning development include: • The Degree of Leadership’s emphasis. Most Enterprises believe that leadership is the determinant factor related to the development of Enterprise E-learning. So Indeed, a significant feature of excellent Enterprise E-learning is that leaders pay high attention on it.

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Table 2. Factors which influents Enterprise E - learning development Factors Proportion The Degree of Leadership emphasis 83% Lack of policies which combines e-learning with 73% performance evaluation in human resources Server and network speed 59% Difficult to evaluate learning effects 55% Staff have little awareness of E-learning 49% Low quality of courseware 49% Difficult to cooperate with the business sector 39%

• Lack of policies which combines e-learning with performance evaluation in human resources. If online learning combines with the human resources management, such as performance evaluation, employee’s motivation will certainly be improved. Therefore, the Enterprise training department or Enterprise University should keep close correlation in business with Enterprise human resources management department. • Server and network speed. Online learning needs server and internet, thus server performance is very important. If it takes long time for employee to log in the server, employee will gradually lose interest in learning. Online learning need base on the hardware conditions. • Hard to evaluate the effects of E-Learning. It is a factor that influences follow-up investments and the level of E-Learning’s importance. Leaders emphasize ROI, that is, every input is expected to gain desired returns. However, it is hard to evaluate the returns of learning because measurement of online learning is quiet a difficult thing. • Employee doesn’t have the awareness of E-Learning. Some employees are not skillful at operating computers and network, which block using of E-Learning. Thus, at the first stage of promotion period, mandatory policies should be taken, though it is a passive learning approach. • The coursewares are lack of pertinence and the form is inflexible. Adult Learning is objective. If the content of the coursewares can’t meet the employees’ actual needs or their problems, it will not be welcomed. Some coursewares are inflexible, which have no supportive case and interaction, so it is easy to make employees tired. • There are some difficulties in the cooperation with business units. Generally, enterprise e-learning should be provided by business sectors and implemented by E-Learning sector. Thus, it need two or more sectors work together to finish the program.

3. Characteristics of Enterprise E-Learning Program and Its ROI 3.1. Characteristics of Enterprise E-Learning Program On the basis of comparing and analysis the e-learning program carried out in enterprise, we summarize some characteristics of excellent enterprise e-learning programs. • The objectives of the programs are aligned with business development strategies. If E-Learning programs can’t keep aligned with business development strategies, they are not supported by the executives. So the learning programs are needed to closely combine with business development strategies and business process. • The executives pay attentions to the e-learning programs and take participant in them. It

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is critical to the success of organization learning. The leaders in the organization not only need support learning, but also need take part in the programs, serving as facilitators and lecturers. The executives refer to management team above the position of vice executive. • The programs are linked with human resource. When enterprise e-learning are combined with human resources strategies, it helps to promote the popularization of E-Learning. Combining E-Learning combines with performance assessment, it will drive the employees’ learning initiative. • Clear object analysis and appropriate instructional design. Object analysis is an important part of instructional design. It is important for the program designer to understand the characteristics and needs of the program objects. • Excellent course resources and learning technology support. Coursewares should be abundant. Online learning support and response should be provided in time. • Pay attention on training effects. It need evaluate that whether the program achieved the desired objectives or not. Enterprises often emphasize learning effect very much, especially change in employees’ behaviors that resulted by learning. • Think highly of knowledge accumulation and business cultural construction. After E-Learning, the organization can develop knowledge accumulation in some way. There are several ways to get knowledge accumulation, for example, processing and reorganization of participants’ work and practices, compiling learning materials and so on. Enterprise e-learning programs are helpful for business cultural construction, particularly for the formation of learning culture and oblate organization. Consequently, enterprise learning culture also improves enterprise e-learning.

3.2. ROI of Enterprise e-Learning Return on investment (ROI) is the ratio of investment to income. Enterprise high-level leaders pay more attention to ROI, especially in the first phase of enterprise e-learning implementation. There are two ways to calculate e-learning ROI, narrow and broad approaches. Narrow approach is the ratio of the cost of face-to-face learning to the cost of e-learning on the premise that these two learning methods achieving the same effect. Narrow approach is simple and commonly used currently. Broad approach is relatively complex and refers to the enterprise performance improvement and economic growth by e-learning. The difficulty of calculating ROI by broad approach is that enterprise business growth is often the combined result of multiple factors, so it is hard to separate out the independent e-learning contributes. But some ideal e-learning projects can be calculated ROI by broad method. As the bank loan officers’ e-learning project, loan officers improve the number of receiving customers and reduce the rate of complaints in the unit time through study. The number of receiving customer and complaint rate can be measured for economic value, thus the ROI can be calculated.

4. Summary Although the development of enterprise e-learning is fast in China, there are many challenges must to be faced. In this paper, based on the survey of enterprises, author analyses the main industry that enterprise e-learning grows well. What’s more, the author analyses positive factors that motivate enterprise e-learning and negative factors that hinder enterprise e-learning, characteristics of enterprise e-learning program.

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There are three key words to summarize above. The first key word is learning, the second key word is technology, the third is human development. Learning and technology have brought great changes into human resources after these two factors introduced to human resources. In Elong Co. Ltd., online learning system is the main body of the enterprise learning sector; most of all enterprise learning is done through e-learning. In today’s information society, the application of learning technology, the popularity of Enterprise e-learning, will drive human resources to a higher stage.

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References Horton, W., Translated by Wu, F. (2009). E-learning by design. Beijing: Education Science Publishing House Ding, X., Gong, J.H., Chen, L.Y. (2008).Investigation on the status of e-learning in Enterprises. Open Education Research, 14(2), 100-104. Wu, F., Li, Y.M. & Xiong, C.M. (2010). The case study of activity design and implementation of enterprise e-learning. Modern Distance Education Research, 104(3), 53-57. Dam, N.V. (2006). The e-learning field book. Shanghai: Shanghai Far East Publishers. Wu, F. (2010). The future of enterprise e-learning. Distance Education in China, 115(4), 35-36. Business-Education Research Center of Peking University. (2009). China Telecom Research Institute research report. Business-Education Research Center of Peking University. (2009). Industrial and Commercial Bank of China research report. Wu, F. (2010). Corporate e-learning ten development theme. Modern distance education research. 105(3), p. 58-63. Allen, M., Translated by Wu, F. (2009). The next generation of Enterprise University. Beijing: World Publishing Corporation.

350 EITT 2013, Williamsburg, VA, USA, November, 2013 Wu, Y., & Ding, W. (2013). Comparative studies on the educational technology organizations in Sino-US higher education. Proceedings of International Conference of Educational Innovation through Technology, 351-368.

Comparative Studies on the Educational Technology Organizations in Sino-US Higher Education

Yanhui Wu, Weize Ding Nantong University Email: [email protected]

Abstract: With the improvement of science and the development of higher education, educational technology organizations, as the significant support of educational reform in higher education, are faced with the urgent task of adjusting and reforming their attribute, function, personnel structure, business process etc. According to the online survey upon hundreds of universities in China and ten universities in America, it is found that educational technology organizations in America lay stress on business integration and application of research and management on information technology institutions, and pay attention to the deep integration of information technology with teaching and learning, while in China, the educational technology organizations have diverse functions and the information technology in teaching and learning is used insufficiently. The construction and development of educational technology organizations in American higher education offers some references to the construction of Chinese educational technology organizations in higher education.

Keywords: Chinese universities, American universities, educational technology, organization

Introduction The educational technology organizations in higher education are the important part of educational technology industry. In the past 30 years, our educational technology organizations in higher education have made great accepted achievements in ensuring the daily teaching, promoting the practice of educational technology and other aspects, and contributed significantly to the higher education in modernization and informatization. However, since we stepped into the new century, on the background of the reformation of higher education and the rapid development of information technology, the development of educational technology in higher education has met lots of new problems and there are also some pressures and difficulties in their existence and development. The organization setting, personnel allocation and cooperation will have influence on the development of the educational technology in higher education. This thesis will compare Chinese educational technology organizations in higher education with American in the way of organization name, personnel structure, organization property, department setting, function, etc., and analyze and study the differences, advantages and disadvantages between them in order to make some references and suggestions to the development of Chinese educational technology organizations in higher education.

1. Analysis on the Characteristics of Chinese Educational Technology Organizations in Higher Education 1.1. Current Situation of Chinese Educational Technology Organizations in Higher Education According to the educational statistics published by Ministry of Education in 2012, currently in China, there are 2358 institutions of higher education distributed over different cities and provinces,

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of which 1112 are state-owned. According to their levels and the scope of subjects, we classify those institutions into four categories, that is, universities sponsored by Project 985, universities sponsored by Project 211, local comprehensive universities and incomprehensive universities, among which 100 universities are randomly selected from east coastal areas, central inland areas and western remote areas (the distribution of sampled universities is showed in Table 1 below). By checking those universities’ websites, this thesis collects the relevant data about the educational technology organizations, and analyzes the data in the ways of name, attribute, personnel structure, function and so on.

Table 1. The distribution of sampled universities in China Eastern China Central China Western China Total Universities Sponsored by 9 7 7 23 Project 985 Universities Sponsored by 9 9 9 27 Project 211

Comprehensive Universities 9 8 7 24

Incomprehensive 9 8 9 26 Universities

Total 36 32 32 100

1.1.1. Organization Name. In the 100 investigated universities, there are 95 universities, each of which has one educational technology organization while each of the other 5 has two independent educational technology organizations. These organizations have different names, such as “Modern Educational Technology Center”, “Network and Educational technology Center”, “Network Information Center”, “Information Management Center”, and so on. They can be concluded into the six categories below:

(1) 22 organizations take Educational Technology as the keyword in the name and account for 22% of the total amount of universities. (2) 13 organizations take Educational Technology and Information (Network) Technology as the keywords in the name and account for 13% of the total amount of universities. (3) 55 organizations take Information or Network as the keywords in the name and account for 55% of the total amount of universities. (4) 4 organizations take Management or Office as the keywords in the name to present the administrative function and account for 4% of the total amount of universities. (5) 1 organization takes traditional Audio-Visual Education Center as the keyword in the name and accounts for 1% of the total amount of universities. (6) 5 organizations set two independent educational technology organizations, which is the combination of Modern Educational Technology center and Network & Computer center (information network center, network management center, informatization office and network center).

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Table 2. Category of the names of educational technology organizations in Chinese universities Organization Organization Organization Category Qty Qty Qty Name Name Name Modern Educational Category 1 Modern Educational Educational 19 2 Technology 1 22 Universities Technology Center Technology Center Management Center

Network and Information Modern Educational Educational 7 and Educational 2 Technology and 1 Technology Center Technology Center Information Center Category 2 23 Universities Division of Educational Network and Network and Technology and 1 1 Audio-Visual 1 Educational Network Center Center Technology

Network and Information and Network Center 11 8 6 Information Center Network Center

Information Network and Information Center 5 4 3 Technology Center Information Center

Network and Network Information and 3 Information 2 Information 2 Network Center Technology Center Management Center

Category 3 Information Information Network 55 Universities 2 Network 2 1 Management Center Technology Center Management Center

Campus Computer Network Computer Network 1 1 Network 1 Management Center Management Center Management Center

Informatization Informatization Communication 1 Management and 1 1 Center Network Center Construction Center

Informatization Category 4 Informatization Informatization 1 1 Construction and 2 4 Universities Construction Office Office Management Office

Category 5 Audio-Visual 1 1 University Education Center

Modern Educational Technology Center & Modern Educational Technology Center & Network Computer Center Informatization Network Center

Category 6 Modern Educational Technology Center & Modern Educational Technology Center & 5 Universities Network Management Center Informatization Office Modern Educational Technology Center & Network Center

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There are two factors that are influencing on the naming of the educational technology organizations of most universities. One is the external social environment of these universities, e.g. the development of technology having influences on the education, the development of the theories of the educational technology having influence on the education, the superior administrative authorities having operational guidance and executive orders to these universities, and etc. The other is some internal factors of these universities, e.g. the understandings of universities on the relations between the educational technology and the educational informatization, university leadership’s emphasis on the educational technology, the historical development of the university educational technology work, functions and roles the educational technology having present in universities, and etc.

The historical development of educational technology organizations in colleges and universities shows that, almost every college or university set up the educational technology organizations in 1970s, e.g. audio-visual divisions, audio-visual rooms, audio-visual centers and etc. which offer the audio-visual education by the audio-visual technology. During the 1990s, network information technology developed rapidly as well as the education informatization, so that it is very necessary for colleges or universities to establish the professional organizations to deal with the informatization work which is based on campus network. However, now the audio-visual education work has different development situation in different universities. Because of excellent work of audio- visual education, the audio-visual education has great influence and plays important roles in there universities, moreover, the audio-visual education absorbs some new theories of the education technology and develops with the informatization and then, the traditional audio-visual education organizations successfully transform to the educational technology organizations.(refer to the Category 1 in Table 2). And in some other universities, the audio-visual education work is finished well, but the audio-visual education is only relied on the audio-visual technology, does not absorb the new educational technology theories in time and develop with the information technology, and then, the universities establish other information technology management organizations, e.g. network center, information center and etc, so that the two educational technology organizations exist in these universities. And then, some of these universities maintain the two educational technology organizations (refer to Category 6 in Table 2), some universities combine the two organizations into one (refer to Category 2 in Table 2), and in some universities, because of many reasons, the traditional audio-visual education organizations become worse and worse in the development, or are ended, or are absorbed into the information technology organization (refer to Category 3 & 4 in Table 2).

The development degree of the educational technology in one university can be found according to the name of the educational technology organization. Some universities only pay attention to the construction, management and maintenance of the campus network, so the setting of the educational technology organization is network center. However, some universities pay attention to not only the construction of campus network but also the construction of teaching resources, the training of educational technology, the research of educational technology, the promotion of the educational technology and other parts, so the setting of educational technology organizations is modern educational technology center or the center of the information network and educational technology. And some universities especially emphasis the integrated planning, construction and management of the school’s informatization construction and authorize the educational technology

354 EITT 2013, Williamsburg, VA, USA, November, 2013 Comparative Studies on the Educational Technology Organizations in Sino-US Higher Education organizations with administrative management functions. Here takes Zhejiang University of Finance and Economics for example. The Modern Educational Technology Center and Informatization Office of this university are the departments which are directly managed by the university and in charge of the construction and management of digital campus, laboratories, multi-media, and so on. They are two independent organizations and co-work with each other.

Therefore, the development history of the names of educational technology organizations is actually the history during which the traditional educational technology means that mainly are based on the audio-visual technology competes and integrates with the modern educational technology means that mainly are based on the information technology. It is the reflection that the media educational technology theory is promoted to the systematic educational technology theory in the educational technology practice in universities.

1.1.2. Organization Attribute. 87 of these 100 universities mention the organization attribute in their brief introduction of educational technology organization, but other 13 universities do not. Those 87 universities use different words to describe. The word “Teaching” appears 74 times, and “Assist” appears 27 times, while “Tutoring” appears 50 times, “Research” appears 19 times and “Teaching” appears 16 times. Organizations in many universities have the comprehensive functions of service, management and tutoring. When checking websites from homepage of these universities to the webpage of educational technology organization, it is found that every university has different classifications to attribute the educational technology organization. There are 50 universities classifying the organization as a direct department managed by the university, 6 universities classify it as a sub-division of President’s Office, Party Committee Propaganda Department, Office of Academic Affairs, Educational Technology and Engineering Training Center and other departments, and 31 universities don’t mention the rank. All the figures are showed in Figure 1 below. According to what is stated above, the educational technology organization has various tasks and duties which involve teaching, service, management, research and development and so on. Therefore, it is difficult to define the organization’s attribute. Besides, as there is no specific competent administrative department or setting modes, some universities adjust randomly the attribute, rank, and affiliation of the educational technology organization, which puts the organization in the marginalized place.

Figure 1 The attribute and level of educational technology organizations in universities

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1.1.3. Personnel Structure. 56 of the 100 universities have a description of personnel in the introduction of the Educational technology Organization. Among those 56 universities, 14 universities only introduce the total personnel amount, while the other 42 universities emphasize on introducing the personnel structure in detail.

1.1.3.1. Total Personnel Amount. There is no detailed description on the nature of employees in the statistics of the personnel amount of those 56 universities. Some universities use the name “staff” to introduce, while some use the name “regular employee” to introduce. Because of the differences of the personnel institution in different universities, the employees are mainly classified into regular employee, personnel leasing or labor dispatching personnel (casual laborer), and this thesis includes them all in the personnel amount. There are 5 universities whose total personnel amount is below 10, 38 universities from 11 to 30, 7 university 31 to 40, 2 universities from 61 to 80, and 4 universities from 81 to 100.

1.1.3.2. Degree Distribution. There are 15 universities referring to the degree in their introduction. Among 385 staff in 15 universities, 17 have doctor’s degree, which accounts for 4%, 153 have master’s degree, which accounts for 40%, and 109 have bachelor’s degree, which accounts for 28%. It shows that the amount of staff with master’s degree is more than that with bachelor’s degree, and those with bachelor’s degree is more than that with doctor’s degree.

Lots of universities introduce that they have a young and impassioned team that is in a higher knowledge level and brave in exploring, progressing and innovating. According to these kinds of introduction and the survey data, it is founded that the personnel structure of educational technology organizations in universities has shown some new characteristics, such as highly educated, youthful, better educated, comprehensive and etc.

1.1.4. Organization Setting. The survey of the setting of internal functional organizations can not explain the development of the educational technology organizations in some related business, but is helpful in realizing the development direction of the educational technology organizations. In the setting of internal functional organizations, most of the universities choose the line structure. This kind of structure has many advantages. It is helpful in the concentration of power, distinguishing the functional authority with duties, convenience of information communication, unity of command and centralized management. Of these 100 universities, there are 72 universities setting the internal functional organizations in the educational technology organizations. These functional organizations involve general offices, network technology department, educational technology department, multimedia courseware making center, examination training center, computer public laboratory and etc. The detailed information is shown in Table 4. The investigation shows the universities that have network technology departments have a largest number which is 88% of the universities investigated. There are 8 universities having 2 or more network departments which separately deal with construction, operation, management and service, e.g. network operation management department, network engineering service department, network information management center, network user service department and etc. And in this thesis, they are all attributed to network technology department. The percentages of general office, educational technology department and information resource department are 70%, 54% and 42% respectively. The percentages of resource & development department, teaching and research office of educational technology, examination

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training center, IC card service center, computer public laboratory and film and TV production center are 26%, 17%, 14%, 13%, 11% and 10% respectively. The percentage of multimedia courseware production center and network education department is 8% and 7% respectively.

1.1.5. Organization Functions. The basic functions and duties of the educational technology organizations cover many areas and are not unified. Of these selected 100 universities, 83 universities have a detailed introduction of their educational technology organizations, as is shown in Table 3 below.

Table 3. Functions and duties of the educational technology organizations in universities The Number of Functions and Duties Percentage Universities

Construction, management and 66 80% maintenance of campus network

Maintenance and management of educational technology equipments and 34 41% facilities

Exploitation, construction and management of digitalized teaching 33 40% resources

Training and evaluation of teachers’ 32 39% educational technology

Production of Multimedia network 19 23% courseware

Network teaching platform 19 23%

Related studies on educational technology 19 23%

Photography and the programming of 16 19% news propaganda

Computer teaching 11 13%

Cultivation of undergraduates and 10 12% postgraduates

The data shows that the educational technology organizations in universities mainly contain the following functions and duties: planning, designing, construction, management, maintenance, service and developing of campus network information infrastructure; maintenance and management of equipments and facilities of educational technology; developing, construction and management of digitalized teaching resources; training and evaluation of educational technology to teachers. And then, the functions or duties also include the making of Multimedia network courseware,

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network teaching platform, related studies on educational technology, and photography and the programming of news propaganda. However, the function in computer teaching and students training is weak.

The orientation of educational technology organization’s function in universities can be explained by the definition of the educational technology. The definition of educational technology made by national experts is that it is a theory and practice which makes use of the modern education theories and information technology to design, develop, use, evaluate and manage the process and resources of teaching and learning to realize the optimization of education. This definition involves the research method, the research object, research contents and research purposes, and emphasizes that teaching is as important as learning and theory is as important as practice. From this definition, the orientation of educational technology organization’s function is turned from instructional media organizations to the media teaching and learning organizations, and then to all-around educational technology organizations, and finally to the center of campus teaching and learning process, and the designing and making of teaching and learning, meanwhile, resource administration center of modern media teaching and learning, Technology instruction center of teaching and learning, and educational technology theory and practice center (Liu, 2000).

1.2. The Characteristics of Chinese Educational Technology Organizations in Universities Based on the comprehensive analysis on the data, there are some main characteristics below:

1.2.1. Diversification of Organization Attribution. Because of the diversification of the tasks and duties of educational technology organizations which includes teaching, service, management, research, development, etc, the organization attribute can not be defined. Moreover, it lacks in operational guidance and administrative intervention of administrative department. Therefore, different universities position the educational technology organizations in different ways and it is not uniform yet.

1.2.2. Diversification of Tasks and Functions.Most of our educational technology organizations in universities preserve traditional function of audio-visual education, e.g. maintenance of hardware equipments, management of audio-visual rooms (current multi-media classroom) and production of audio-video materials. With the development of educational technology, some new business scope is expanded, e.g. the making of courseware and software, the development of long distance education, teachers’ training, etc. Currently, the educational technology organizations play an important role in the teachers’ computer training but a less role in computer teaching and the research and promoting of educational technology (Zheng, 2007).

1.2.3. The Development of Educational Technology Organizations in Different Universities is Out of Balance. The development stage and key points of educational technology organizations in different universities is different. Some are in the primary stage of hardware construction (equipment management), some are in the intermediate stage of software construction (instructional software, courseware making), and some are in a higher stage of underwear construction (educational technology promotion, teaching ability enhancement). Some participate in discipline construction of educational technology and talent cultivation, which provides a platform for construction of educational technology professional team. In every development stage, the economic strength of

358 EITT 2013, Williamsburg, VA, USA, November, 2013 Comparative Studies on the Educational Technology Organizations in Sino-US Higher Education different educational technology organizations is different, which makes the speed of organization construction different. Especially, the research resources are seriously unequal. Some have powerful research strength of educational technology, which can offer master’s degree and possess the educational technology periodicals, while some seldom carry out the educational technology research.

1.2.4. Application of Information Technology in Teaching and Learning Is Insufficient. Currently, the educational technology organizations in Chinese universities pay more attention to the infrastructure construction and network services, but less to how to make use of information technology to support schools’ teaching and learning, scientific research and management. Even for the educational technology training, the organizations only pay attention to the technology itself instead of the application of the technology in teaching and learning.

Table 4. Distribution of educational technology organizations in American universities Name of Educational Institutions Type Location Technology organization

Center for Information Princeton university private Eastern USA Technology Policy

Middle Tennessee State Information Technology public Eastern USA University Division

Information Technology Yale University private Eastern USA Services

University of New Hampshire public Eastern USA Information Technology

Office of Information Technol- Ohio University public Eastern USA ogy

Center for Information Technol- University of Michigan public Eastern USA ogy

University of Southern Information Technology Ser- private Western USA California vices

Center for Instructional Devel- University of Washington public Western USA opment and Research

Center for Instructional Devel- University of Pittsburgh public Eastern USA opment & Distance Education

University of Nebraska at Information Technology Ser- public Central USA Kearney vices

Center for Instructional Tech- Villanova University private Northern USA nologies

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2 Characteristics of Educational Technology Organizations in American Universities The United States is not only the earliest country to develop information and network technology, but also the country with the highest level of educational informatization. Survey on the current situation of educational technology organizations in American universities can make some references and suggestions to us. Through investigation on the general situation of educational technology organization in American universities collected from periodicals, documents and websites, the characteristics of those organizations is analyzed in the Table 4 above.

2.1. Current Situation of Educational Technology Organizations in American Universities 2.1.1. Organization Name. The educational technology organizations in American universities have various appearances in the name, such as “Information Technology Division”, “Information Technology Services”, “Office of Information Technology”, “Center for Instructional Development and Research”, “Center for Instructional Development and Distance Education”, “Center for Instructional Technologies”, and so on. These organizations have different focuses. Some focus on research and management, such as Center for Information Technology at University of Michigan. Some focus on information technology services, such as Information Technology Services at Yale University which is annotated as serving the Yale community with technology. The common ground of these organizations is to provide technology services in teaching, learning and research for staff and students, and to assist teachers to create and implement teaching and learning successfully, in order to promote the teaching and learning of the universities.

2.1.2. Organization Attribute. There are different attributes of these organizations. Some belong to division-level administrative departments leaded by Associate Vice President-Chief Information Officer, such as Center for Information Technology Policy at Princeton University. Some belong to academic departments, such as Center for Instructional Development and Research at University of Washington. Some are parts of university’s information technology office.

2.1.3. Personnel Structure. The orientation of educational technology organizations’ function in American universities mostly focuses on the integration of information technology’s construction and service. To avoid repeated construction and coordination, the staff team construction of educational technology organization is relatively concentrated. Public functional departments basically do not need information technology staff. Information technology services are undertaken by the educational technology departments. In general, there are more than one hundred people in educational technology departments (Liu, 2010). Among the universities surveyed, Center for Instructional Development & Distance Education at University of Pittsburgh has the smallest number of staff, including 60 employees and 22 part-time students. Overall, the amount of staff in educational technology organizations in American universities is larger than that in Chinese universities.

In addition to the large amount of staff, personal information (e-mail, telephone, research direction, duties, etc.) is open, and is described in details on the homepage of departments. Staff and students can call, email, order service or go to the office directly to ask for help when they meet technical problems in teaching or learning.

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2.1.4. Organization Setting. Educational technology organizations in American universities mainly have the following internal sections: Academic Services, Administrative Information Services, Infrastructure Services, Data Management Center, Finance, Administration & Planning, Project Management Office, information Security, Customer Service, and Strategic Initiatives. Each functional section sets several functional centers which are responsible for more specific information technology work, to provide support and services for the school’s teaching, research, public service and administration.

Educational technology organizations set a position for CIO (Chief Information Officer). Usually, Vice-Chancellor who is responsible for campus information serves as CIO. They make information technology plans and policies, manage information technology organizations, and coordinate campus’ IT activities (Li, & Sang, 2009). Information Technology Services at Yale University, Information Technology at University of New Hampshire and Office of Information Technology at Ohio University are the examples of this organizational model, as is shown in Figure 2 below.

Figure 2 Organization chart of Information Technology Services at Yale University

2.1.5. Organization Functions. According to the analysis of functions of educational technology organizations in those American universities mentioned above, the following functions are mainly focused on:

Provide Network Services and Technology Support. The educational technology organizations are primarily responsible for the planning of the campus network construction, the construction operation and maintenance of hardware and software, security monitoring, management services and network information to provide smooth network services for staff and students. Take Yale University and University of New Hampshire for example, Information Technology Services at Yale University provides technical support in the aspects of network ID and password, quick connect, wireless, VPN, and security. Information Technology at University of New Hampshire provide network services including campus Ethernet, WIFI, IT security, network security, Internet, USNH WAN, wide-area networks and non-USNH institutions internet’s expanding, video conferencing services—one-to-many bridging, distance education network in New Hampshire and so on.

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Be Responsible for the Construction and Maintenance of Information Technology Facilities. American University attach great importance to the construction of information technology facilities that students need to use when they study, such as the construction of multimedia classrooms and computer laboratories .which are equipped with computers, scanners, printers and other networked devices. Common software is purchased or provided for free by IT department. Positions of technical consultants and administrators are taken by part-time students in each laboratory (Liu, 2010).

Provide Technical Support and Protection for Management Systems and Databases. Educational technology department is responsible for universities’ management system and database, including electronic identity authentication and rights management, mail system, learning management system, campus card systems and so on. For example, University of Southern California provides reliable technology infrastructure to meet various needs of the university. E-mail and directory services can support about 120,000 pieces of daily information’s exchange from more than 75,000 users. Each year, Customer Support Center deals with about 71,000 computer-related questions from staff, students, and other workers. On an average, www.usc.edu, the web page of the University of Southern California, has been accessed 900,000 times every day.

Offer Network and Communication Services. Network and communication services are uniformly managed by the educational technology department. Communication Support Services, CSS, of Information Technology Division at Middle Tennessee State University is responsible for frontline services in IT department. For example, 24/7 IT platform (in class) is responsible for physical distribution of School Blue ID cards , smooth running of ID, the publishing the publications about how to use information technology in the Middle Tennessee State University for staff and students, and the management of university software site license.

Ensure Information Security and Formulate Information Security Policies. American Universities have high popularization rate of network. Teachers and students and administrators in universities have reliance on the network, which makes information security particularly important. The key point of current informatization infrastructure is to ensure the stable operation of the campus network, the security of the information store, and the avoidance of computer viruses (An, 2010). IT departments in universities have set specialized offices for information security which are led by CISO, such as Information Security at Yale University, Information Technology Security & Preparedness at University of New Hampshire, and Office of Information Security at Ohio University. CISO has responsibility for daily security operations, network monitoring, system compliance and protection of information confidentiality, integrality and validity.

Provide Comprehensive IT Training Courses. American universities provide faculty members with comprehensive and various forms of IT training contents. For example, Information Technology Division at Middle Tennessee State University often hold training and seminars about software, network teaching, the use of multimedia teaching equipments for the staff, to promote campus Information technology (Wang, & Wei, 2011).Education and Outreach Service of The Center for Information Technology Policy at Princeton university have two fixed training programs. One is called Efficient Scholars which focuses on software training, in order to improve thework efficiency of staff and students. The other is called Lunch Learning which offers lectures on the

362 EITT 2013, Williamsburg, VA, USA, November, 2013 Comparative Studies on the Educational Technology Organizations in Sino-US Higher Education latest development of technology at lunchtime. Speakers combine technology with teaching and research to give teachers and students some concept shocks. So they may have initial impression on how to use technology to improve teaching and learning effect. Speakers also tell the audience which services can be offered to promote the change of teaching, learning and research through follow-up services of Teaching Service (Ding, & Sang, 2007). The Center for Instructional Technologies at Villanova University has special workshops and seminars on various technologies’ introduction for teachers.

Offer IT Services on High-performance Scientific Computing and Research. American universities pay more attention to interdisciplinary research. Therefore they construct high- performance computing and communications center to create such academic environment. For example, High-Performance Computing and Communications (HPCC) of Information Technology Services at University of Southern California ,founded in 2000, supports 180 research groups including scientific computing, computer science and communication to have researches on experimental embryology, geophysics, materials science, engineering, natural language translation, health sciences and so on. Its computing and communication resources allow researchers to go beyond the traditional limitations. The new understanding and meaningful results have far-reaching interdisciplinary effect. HPCC expands the scope of the “big computing” by solving problems on social, economic and cultural resources. With its advanced computing and communications resources, it creates immersive virtual organizations and virtual worlds.

Develop the Projects that Promote Teaching and Learning. Educational technology organizations in American universities develop research projects on teaching, learning and assessment. The research fields focus on the problems that can not only help teaching but also enrich the knowledge of this field. The main projects involve improving the environment of courses’ teaching and learning, improving the students’ IT literacy, teaching strategies about enhancing students’ learning experience, promoting students’ learning assessment, popularizing new learning technologies, the application of project materials on teaching and learning technologies in higher education (Wang, 2007).

2.2.The Characteristics of Educational Technology Organizations in American Universities 2.2.1. Lay Stress on the integration of Educational Technology with Teaching and Learning. American universities lay great stress on the application of educational technology in teaching and learning. Especially, the development of network technology has promoted the exploration and application of network teaching platform and network learning resources, which integrates the traditional teaching mode with the new learning mode, and makes them complement each other. The main function of educational technology organizations in American universities is to provide technical support in teaching and learning for the staff and students, and assist teachers to successfully create and implement teaching and learning, in order to promote teaching and learning in universities. Take the Center of Media Initiatives (CMI) of Information Technology Services at Yale University as an example. It is mainly responsible for Yale’s advanced media development plan and network teaching support, including development plans on educational media and courseware. In network teaching, Yale University has imported the open teaching platform from 2005. In addition, the center has a team working on solutions of educational technology. It employs full-time staffs, including curriculum developers, teaching media experts, graphic designers,

EITT 2013, Williamsburg, VA, USA, November, 2013 363 Proceedings of International Conference of Educational Innovation through Technology web producers, and education-supporting administrators that help professors to use educational technology, and design and post product the multimedia teaching materials.

2.2.2. Lay Stress on the Application of Web-based teaching platform in teaching. In the universities surveyed, teachers use Blackboard to assist teaching. Blackboard, which is used to support teaching and learning, is a web-based course management software system. Teachers and students can interact well through this system. Teachers publish teaching plan, course notes, references and homework on Blackboard, and students can download resources, submit assignments, communicate with teachers and other students, and share resources through the Blackboard. Teachers and students can create discussion posts, blogs and logs, announcements to make comments. Students can also check levels, tasks and so on. The Blackboard platform in American universities is also highly integrated and associated with the university’s information management system and the database. If you want to read the references listed by teachers, you can directly get accessed to the library digital resources platform. Students can be informed of teaching information through email or portal site.

2.2.3. Establish Sound Organizational Management System — the CIO System. The CIO system was introduced to American universities in the 1980s. Generally, the CIO is a member of the university board. He/she should take part in university’s senior leadership conferences and give some reasonable suggestions. The CIO should be familiar with the IT construction and application in each department, and make suitable development programs combing with school’s development. According to the survey made by the EDUCAUSE in 2007, there are 28.90% heads of educational technology organizations with the CIO title. In the 11 universities surveyed, 9 leaders of the educational technology organizations have the CIO title. They manage educational technology departments in the whole school, plan the educational technology organizations’ software and hardware construction, ensure the normal use of infrastructure and stable operation of campus network, deploy the staff of educational technology organizations, organize regular training and examination according to actual need, coordinate the relationship among departments, provide service for other departments, know the development of other departments, and give reform opinions in time (An, 2010).

2.2.4. Lay Stress on the Business Integration of IT Departments and Construction of IT Resources. As mentioned before, information technology services in American universities are offered by the departments of educational technology which focus on the integration of IT construction and service and avoid repeated construction and resources waste. For example, the educational administration management system, the campus one-card system, library digital resources are integrated. Each teacher and student has an electronic ID when they entered the university. They can use this ID and password to enter all systems of the university, including the online authentication system, E-mail system, educational administration management system, and so on. Educational technology departments can adjust the ID authority in time according to the change of teachers and students’ status which realizes the integration of identity authentication. On the aspect of resources construction, the American universities construct high qualified IT service platforms in scientific computing and research, computer laboratories, digital education resource database, multimedia courseware, network course production and technology service.

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2.2.5. Keep Up with the Advanced Information Technology, and Promote the Innovation of IT Service. The university campus is covered with wireless network by using wireless technology to create a more flexible learning and teaching environment, and to realize M-learning, so that teachers and students can visit educational resources website anytime and anywhere. The network virtual technology can gradually make services more detailed and humanized, such as campus facilities based on geographic information system, logistics service network system, and classroom online search system based on the electronic map.

3. Suggestions and References 3.1 Assign Adequate Educational Technology Professionals The number of educational technology professionals in Chinese universities is quite small, mostly 10-40. This is out of proportion to the amount, complexity and high standard of work they undertake. Because of this, much relevant work cannot be carried out, such as technological support of network teaching and teaching resource construction. Even the essential information environment security cannot be safeguarded. Take the campus network maintenance as an example. Some universities can only guarantee the main circuit from campus network center to the building rooms, while the maintenance from building rooms to the desktops is worked out by users themselves. The informatization security is at the low level. The modern educational technology center where the author works is a large-scale organization with 100 professionals, which accounts for only 3% of total employees at the university. However, in American universities, the smallest number is up to 60, which accounts for over 3% of total employees. The number at Yale University even reaches 19% (refer to Table 5 below).

Table 5. Teacher’s influence Number of Number of Employees in Number of Percentage (N3 out of Institutions Students Educational Technology Staff (N1) N1) (N2) Organizations (N3)

Villanova university 545 10000 105 19.27﹪

Yale University 2300 11250 417 18.13﹪

Princeton university 1100 7800 134 12.18﹪

Middle Tennessee 800 25000 75 9.37﹪ State University

Ohio University 6696 32359 202 3.01﹪

University of 6682 59000 109 1.63﹪ Michigan

University of 5369 35330 60 1.12﹪ Pittsburgh

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3.2. Broaden the Professional Structure and Optimize the Education Technology Professional Team In china, most of the educational technology specialties major in computer, such as computer science and technology, information management and information system, and so on. Some are major in educational technology. The structure is single. Most of them can only be engaged in some hardware management, such as campus network maintenance, educational technology infrastructure support and so on. They are weak in software development, information system maintenance and data mining. Chinese universities lack professional staff working for teaching instruction, teaching resources construction, teaching resources construction, improving teachers’ professional development and promoting teaching reform. However, in America, the employees in educational technology organizations have various majors. There are network technique maintenance workers, webpage making workers, audio-visual media experts, graphic and animation designers, instructional designers, educational administration experts and so on. To meet educational informatization and educational technological diversification and promote the integration of educational technology into teaching and learning, all kinds of professionals should be brought in, especially the talents that specialize in pedagogy, psychology, software engineering, arts, curriculum theory, communication and so on.

3.3. Improve the Application of the Information Technology in Teaching. Research and Management There is little difference between American universities and Chinese universities in information technology infrastructure. But Chinese universities have a certain gap in the application and popularization of information technology compared with American universities. At present, educational technology organizations in Chinese universities mainly focus on the infrastructure and network services, and pay little attention to how to integrate information technology into teaching, research and management. Some educational technology organizations set educational technology research departments which focus on the application of technology in teaching, but they don’t pay attention to the promotion of research’s productions. We should learn from the IT concepts and application mode of American universities, use information technology to support the innovation teaching, learning and research, and promote the standardization and scientization of university’s management and service work.

3.4. Strengthen the Integration of Educational Technology Organizations’ Services IT services in American universities are undertaken and managed by educational technology departments, which improves the efficiency and effect of the entire university’s IT function. Some universities in China not only have modern educational technology centers, but also set coordinate organizations related to educational technology. They compete for resources because of lacking of understanding and cooperation. Aiming at providing service for teachers and students, it is necessary for Chinese educational technology organizations to strengthen integration of inner business, including overall plan of the digital campus, school network and communication services, academic management system, campus one-card system, library’s digital resources, management and maintenance of the facility, and education technology training, so as to realize centralized construction and management and to avoid repeated construction and resources waste.

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3.5. Reform the Management System of Educational Technology Organizations In the USA, the colleges and universities, both in public and private, have built the perfect educational technology organizations. CIO is not only a position setting, but an innovation of the school’s internal management mechanism, which relates to the school adjustment of various departments. According to the positioning and existing personnel organization pattern in Chinese colleges and universities, the conditions of setting CIO in some colleges and universities are not mature enough, but we can learn from the advantages of CIO system which can provide a model for the management system reform of educational technology organizations in our country. For example, the CIO selection criteria in American universities can be used for references in selecting the directors of the educational technology organizations. In the knowledge requirements, the director should have application and management knowledge of information technology, the knowledge of universities organization and management, and the knowledge of human nature. In the capacity requirements, the director should have the abilities of management and leadership, communication and interpersonal skills, and strategic planning and decision –making ability (Liu, 2011).

3.6. Create the New Service Mode, Improve the Service Quality, and Strengthen the Promotion The service awareness for educational technology organizations in Chinese colleges and universities improves year by year. But still, we should constantly create new service mode, implement the service standards, optimize the service process, improve the service quality, and pay attention to the specialization and refinement of the service. Therefore, we can make the service more efficient and humane. At the same time, we should reinforce the awareness of the service promotion, and promote widely through various ways to make teachers and students know the service provided by university’s educational technical department.

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References An, J. (2010). Inspirations of American university informatization for Chinese universities. Harbin, Heilongjiang University. Ding, Y. & Sang, X. (2007).The role of educational technology American universities - visiting the center for information technology policy of princeton university. China University Teaching, (2), 73-76. Li, F., & Sang, M. (2009) The role of CIO in the application of information technology in higher education institutions. Fudan Education Forum, (l), 25-29. Liu, W. (2000). Educational technology: yesterday, today and tomorrow. E-education research, (5), 13-18. Liu,Y. (2011) .Structure and Training Strategy of CIO Leadership in American Universities. China Educational Technology, (10), 48-53. Liu, Z. (2010). The application and innovation of higher education informatization in the respect of American universities. China eduacation info, (11), 4-6. Wang, J., & Wei,X. (2011). Analysis of the campus information technology development and practice in middle Tennessee State University. China eduacation info, (7), 14-17. Wang,Y. (2007). Research on the orientation of educational technology department’s function in ordinary universities. Nanchang, Nanchang University. Zheng, Q. (2007). M study of m educational technology center. Shanghai, Shanghai International Studies University.

368 EITT 2013, Williamsburg, VA, USA, November, 2013 Xie, Y. & Jian,j. (2013).Empirical research on e-Learning environments for higher-order thinking - based on writing instruction for primary students of grade 5. Proceedings of International Conference of Educational Innovation through Technology, 369-378.

Empirical Research on e-Learning Environments for Higher-Order Thinking — Based on Writing Instruction for Primary Students of Grade 5

Yueguang Xie Northeast Normal University Email:[email protected]

Jie Jian Hunan Normal University Email: [email protected]

Abstract: This paper describes a study on the support digital learning environment to the development of higher-order thinking. The paper commences with a brief introduction to the research, and points out the main research questions and the research hypothesis. The detailed description of the research method and the process forms the next part of the paper, which highlights the design mode of digital learning environments and the chosen measuring tools. In the data analysis that follows, the comparison between pretest and posttest reveals the developed performances of higher-order thinking in writing activities, which includes writing motivation, language learning self-efficacy, the attitude towards computer and the perception of digital learning environment.

Keywords: e-learning environments, higher-order thinking, primary students, writing instruction

1. Introduction In this study, we offered writing instructions with special design to some fifth year students in a primary school. With the purpose of examining the effect of e-learning environments, action research, quasi-experimental research and survey research method were adopted to reveal the relationship between e-learning environments and learners’ higher-order thinking development.

The research contents and basic thought of the research are listed as follow. First, the content framework of e-learning environments is constructed, based on which we can build the descriptive framework of higher-order thinking development in writing activity. Meanwhile, evaluation tools are developed through reform and design. After designing the e-learning environments with “technology drives design” as the guiding ideology, we can implement it in Chinese writing class of a primary school. Finally, through analyzing the data obtained from pretest and posttest, we are able to examine how students’ writing performance is related to higher-order thinking development in the process of teaching intervention.

There is one teaching intervention class per week, which lasts 40min and altogether covers 4 special issues of the content. Design of the class is conducted by the researcher, Chinese teacher of the selected class, together with provincial leading teachers of information technology subject in the school. Chinese teacher mainly contributes knowledge of writing instruction method; teachers of information technology provide help in instruction support for information classroom, while the researcher is responsible for design and establishment of specified learning activity. The instruction

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 369 Proceedings of International Conference of Educational Innovation through Technology is conducted in a computer lab, which accommodates 50 computers with LAN connecting Internet. Teacher’s computer and students’ computers are connected by multimedia classroom management software, with which teachers can control the students’ computer in different ways such as screen shifting, broadcasting, roll-calling, and file sending.

Writing learning contains the following six information technology tools which are familiar and suitable to primary students.

(1) QQ email (2) Baidu search engine (3) youku network video (4) sohu Blog (5) Visual Ranking (6) Showing Evidence

We select Chinese writing class of primary school as research carrier based on the following recognition: Writing is a comprehensive learning activity that needs students to understand knowledge, experience life, express emotion and use words. Given the abundant network information resources, the creation process of the students’ writing could use the support from information technology in various steps, which provides opportunities for information technology to support deeper learning. Both creation process and creation results can directly reveal comprehensive quality of the students, including personality, intelligence and emotion. Moreover, research on primary Chinese writing can provide scientific method for the presentation of evaluation. As noted in some related research, writing motivation, self-efficacy and attitude of learners can be significantly improved under effective teaching intervention.

2. Research Questions and Research Hypothesis 2.1. Research Questions (1) How can e-learning environment be designed to promote the development of higher-order thinking? (Fusion target: development of higher-order thinking) (2) How can higher-order thinking development be evaluated? (3) What reform has information technology brought to the class environment of writing instruction?

2.2. Research Hypothesis

(1) Favorable emotional experience will support higher-order thinking development of learners; (2) Learners’ positive perception of learning environment will support higher-order thinking development of learners; (3) Technology’s impact on learners is realized through the change of thinking style empowered by the environment.

370 EITT 2013, Williamsburg, VA, USA, November, 2013 Empirical Research on e-Learning Environments for Higher-Order Thinking ——Based on Writing Instruction for Primary Students of Grade 5

3. Method 3.1. Participants Nineteen primary school pupils from a class of Grade 5 were chosen as the participants of the study.

Figure 1. The photograph of the classroom 3.2. Research Process We followed the cyclic reinforcing action pattern of ‘plan-act-observe-reflect-plan’ in the research process.

3.3. Design and Implementation of the Teaching Intervention (1) The construction of learning environment based on the proposed design model We first designed each element of learning environment according to the functional features of IT tools and then improved the design after applying them to the learning process. Sample design of cognition tools: VR surface of the special subject of “what to do with a computer”; SE of the special subject of “advantages and disadvantages of using a computer”. (2) Implementation of the teaching intervention in the constructed learning environment: Time of the intervention: 10 weeks; Goal of the intervention: to improve students’ higher- order thinking in writing; Content of the intervention: 4 special issues of writing instruction designed under the e-learning environments (see samples in the appendix).

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Figure 2. Design model of e-learning environment

Features of the intervention: Cooperation between the researcher and the implementer; Improving practice in the authentic context; Reflection on and communication with the context; Circular reinforcing intensity of the intervention.

3.4. Selection, Modification and Compilation of Measuring Tools (1) According to the theoretical analysis on extended manifestation of higher-order thinking in writing, learning outcomes that we expected to improve include writing motivation, self-efficacy in Chinese learning and attitudes towards the computer. Based on these three targets, Writing Motivation Scale, Self-efficacy Scale and Computer Attitudes Scale were selected as measuring tools.

1) Writing Motivation Scale We chose the Writing Motivation Scale for the study. The scale was revised by Liu Jiawen (2007) from Institute of education science and technology, Taiwan National Pingtung University of Education.

The scale contains 26 questions divided into four dimensions, which are importance and utility of writing, expectations of writing, and emotions of writing and interest of writing. The questions adopt four-Likert scale, including strongly disagree , disagree, agree and Strongly agree .The four options are orderly assigned one point ,two points, three points and four points . And the reverse order is applied to negative statements. The reliability and validity have been proved to be high, therefore we decided to apply it to test the motivation of the participants in the study.

372 EITT 2013, Williamsburg, VA, USA, November, 2013 Empirical Research on e-Learning Environments for Higher-Order Thinking ——Based on Writing Instruction for Primary Students of Grade 5

Table 1. Sample of content design: questions about contents

We made three modifications to the scale. Question 8 and 19 were deleted and Question 13 was spited into two questions.

2) Self-efficacy Scale in Chinese learning We chose the Self-efficacy Scale of pupils in Chinese learning as our measuring tool, which was compiled by Chen Yipin (Chen, 2009) from Institute of educational research, Taiwan Ming Chuan University. The scale was divided into six dimensions: persistence, self-verbal persuasion, completion of the homework, willingness to learn, goal achieving, and physiological status. Each question has five options, including fully comply, mostly comply, partly comply, mostly not comply and fully not comply. The five options are orderly assigned five points, four points, three points, two points and one point. And the reverse order is applied to negative statements. Based on the validity analysis of eight experts, altogether 24 questions are presented in the scale

We made four modifications to the scale. Question 12 was deleted .The wordings of Question 5, 11 and 12 were changed.

3)The Scale of Attitudes toward Computer We chose The Scale of Junior High School Students’ Attitudes toward Computer as the measuring tool. The Scale was compiled by Yang Kunyuan (Yang, 2006) from Institute of educational research, Taiwan Chung Yuan Christian University. It was divided into four dimensions, which are the use of computer, the interest of computer, the confidence of computer use and the anxiety of computer use.

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The scale adopts five-Likert system, including strongly agree, agree, neutral, disagree and strongly disagree .The five options are orderly assigned five points, four points, three points ,two points and one point. And the reverse order is applied to negative statements. The reliability and validity have been proven to be high; therefore, it is applied to the tests of the fifth grade in primary school. The higher the total is, the more positive the attitudes towards the computer are.

We made ten modifications to the scale. Some expressions of ninth, eleventh, fourteenth, sixteenth, twenty-third, thirtieth, thirty-eighth, forty-second, forty-eighth and forty-ninth questions were modified or deleted.

(2) We also conducted tests on the three modified scales to ensure their reliability and validity. The data from seventy-eight samples was analyzed by Confirmatory Factor Analysis (CFA) through LISREL8.70 and we obtained construct validity of the modified scales. The results showed that they have good construct validity. Using SPSS17.0, the sample data was examined by internal consistency reliability and we obtained Cronbach of overall and each subscale, which indicated that the reliability of each modified scale is rather high.

(3) According to theoretical research, we put forward an analytic model of e-learning environments. General Learning Environment Scale-Taiwan Version (WIHIC)and Clinical Learning Environment Inventory(CLEI)were properly integrated into an e-learning environment questionnaire. The questionnaire contained ten dimensions, which include student friendliness, teacher support, student involvement, inquiry, task orientation, cooperation, equality, integration, openness and technology appropriateness.

Moreover, we compiled a gauge of trait of thinking in writing.

3.5. The Pre-test and Post Test Researchers selected 20 primary students of Grade 5 on October 12, 2010, to carry out pre - test, which includes writing motivation scale, Chinese learning self-efficacy scale and computer attitude scale. After 10 weeks of teaching intervention, on December 28, 2010 the researchers carried out the post-test, which contains writing motivation scale, Chinese learning self-efficacy scale, computer attitude scale and digital learning environment questionnaire. As one student failed to attend the post-test due to illness in the midway, there are 19 students participating in the post test. Therefore, the data we took into analysis was actually drawn from these 19 students.

4. Data Analysis The data of the research is analyzed through the following approach: we used paired T-test to examine the difference between the means of pre and post tests of the 19 students. In the following tables, total_mean1 stands for mean scores of the pretest, total_mean2 for posttest.

4.1. The Change in Writing Motivation Table 2 presents the basic description of the writing motivation, which includes the number of the sample, means, standard deviations and standard error means. From the means, we can tell

374 EITT 2013, Williamsburg, VA, USA, November, 2013 Empirical Research on e-Learning Environments for Higher-Order Thinking ——Based on Writing Instruction for Primary Students of Grade 5

that change happened to the motivation. As for whether the change can be considered statistically significant, T-test is needed to draw the conclusion.

Table 2. Descriptive statistics of paired t-test on writing motivation Mean N Std. Deviation Std. Error Mean Pair 1 Total Means 19 .53861 .12357 4.2905 Total Means 19 .49385 .11330 3.7642

Table 3 shows the results of simple correlation T-test. The third column of the table is the correlation coefficient of the teaching intervention to the sample, and the forth column is the ρ value of the coefficient, which is less than 0.05. Thus we can conclude there is, to some extent, liner relationship between the teaching intervention and the motivation of writing.

Table 3. Correlation paired test results of writing motivation N Correlation Sig. Pair 1 total_mean2 & 19 -.499 .030 total_mean1

Table 4 displays the final results of T-test. Column 2 in the table shows the mean difference of writing motivation before and after the teaching. Column 3 and 4 presents the standard deviation and standard error mean respectively. As seen from column 5 and column 6, the confidence interval is between .09535 and .95728, with degree of confidence being 95%.Since 0 falls out of the interval, it can be concluded that the difference of the sample is rather big. The next two columns are the statistical estimates and the degree of freedom. The ρ value in the last column is .019(<0.05) and denies the null hypothesis. This suggests that statistically significant change happened to the writing motivation after the teaching intervention and the intervention has a substantial impact on the writing motivation.

Table 4. Paired t-test results of writing motivation Paired Differences t df Sig. (2 tailed) Mean Std. Std. 95% Confidence Devia- Error Interval of the Dif- tion Mean ferences Lower Upper Pair 1 total_mean 2 .25632 .89416 .20513 .09535 .09728 2.566 8 .019 total_mean 1

4.2. The changes in Chinese learning self-efficacy Table 5 describes the basic statistical information of Chinese self-learning efficacy. From the changes in the means, we could tell changes happened to the efficacy. Table 6 shows the significance of this change.

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Table 5. Descriptive statistics of paired T test on Chinese learning self-efficacy Mean N Std. Deviation Std. Error Mean Pair 1 total_mean2 4.4807 19 .30498 .06997 total_mean1 4.2403 19 .34031 .07807

As shown in Table 6, the ρ value of the pre and post test in Chinese learning self-efficacy is 0.526(>0.05),which means that we can accept the null hypothesis that there is no linear relationship between teaching intervention and Chinese learning self-efficacy.

Table 6. Correlation paired test results of Chinese learning self- efficacy N Correlation Sig Pair 1 total_mean2 & 19 .155 .526 total_mean1

The results of the paired T test in Table 7 show that the difference of means in pre and post test is 0.24943.The confidence interval of the difference is between 0.04687 and 0.45198. With 0 falling out of the interval, we can conclude that the difference in the samples is significant. When confidence level is set as 95%, the 2-tailed ρ value is 0.019(<0.05). Thus the null hypothesis is denied, which means that statistically significant change happened to the Chinese learning self-efficacy after the teaching intervention and the intervention has a substantial impact on the efficacy.

Table 7. Paired T test results of Chinese learning self-efficacy Paired Differences t df Sig. (2 tailed) Mean Std. Std. 95% Confidence Devia- Error Interval of the Dif- tion Mean ferences Lower Upper Pair 1: total_mean 2 .24943 .42025 .09541 .04687 .45198 2.587 8 .019 total_mean 1

4.3. The Change in Computer Attitudes We conducted the same statistical analysis on computer attitudes. From the descriptive results of single T-test, we can see that there is change in students’ attitudes toward computer. T-test shows the teaching intervention is linearly related to the attitudes in pre and post test. Paired sample analysis presents that the difference of the means is 0.38346. The confidence interval of the difference is between 0.11661 and 0.62845. With 0 falling out of the interval, we can conclude that the difference in the samples is significant. When confidence level is set as 95%, the 2-tailed ρ value is 0.004(<0.05). Thus the null hypothesis is denied, which means that statistically significant change happened to students’ computer attitudes after the teaching intervention and the intervention has a substantial impact on the attitudes.

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4.4. Students’ Perception of E-learning Environment Table 8 shows the results of the questionnaire of students’ perception on e-learning environment from 10 different dimensions.

Table 8. Descriptive statistics of students’ perception of e-learning environment

From the table, we can see that total score of students’ perception is 4.467 and the scores of all dimensions range from 4.063 to 4.772, which indicates that the students have rather positive attitudes towards e-learning environment.

5. Findings and Discussion (1) From the data analysis of pre and post tests, we can clearly see that significant improvements happened to the students in their writing motivation, Chinese learning self-efficacy and computer attitude. This suggests that in the e-Learning environments that support Higher-order thinking, the learners will be more willing and able to learn better. Moreover, favorable emotional experience can support the development of the learners’ higher -order thinking.

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(2) The students’ perception of e-Learning environments is positive on both dimensional and overall level. This shows the e-Learning environments constructed in the study are able to provide a positive learning environment for learners, to improve learners’ learning, and to support the development of the learners’ higher-order thinking.

(3) From the perspective of the “technology supports learning” mechanism, we can infer that the application of technology brings a more nourishing environment for higher-order learning and the classroom with technology involved is able to encourage learners’ initiative, cooperative, constructive and the inquiry-based learning; In essence, technology’s promotion of learning represents the support of learning environment to the development of learning under constructivism epistemology; In the process of applying information technology to learning, gradual changes distinguished with technological features will happen to the thinking style of the learners.

References Liu, J. (2007). The effect of teaching method about creative thinking in composition to Grade 5 students in writing motivation and performance. Unpublished master’s thesis, National Pingtung University of Education, Pingtung, Taiwan, China. Chen, Y. (2009). Comparative analysis of the self-efficacy of the mainland and Taiwan pupil in studying Chinese - a primary schools of Matsu and Fuzhou each as an example. Unpublished master’s thesis, Ming Chuan University, Taipei, Taiwan, China. Yang, K. (2006). The development and application of the attitude scale to computer of middle school students. Chinese Journal of Science Education, 14(3), 283-308. Huang, T., Aldridge, J. M., & Fraser, B. (1998). The multinational study of classroom environment between Taiwan and the western of Australia: using qualitative and quantitative research methods. Chinese Journal of Science Education, 6(4), 343-362. Newby, M. & Fisher, D. (1997). The association between computer laboratory environment and student outcomes. Retrieved from https://www.aare.edu.au/98pap/new98037.htm

378 EITT 2013, Williamsburg, VA, USA, November, 2013 Xu, Y., & Chen, M. (2013). Research on the teaching for understanding in information technology curriculum. Proceedings of International Conference of Educational Innovation through Technology, 379-384.

Research on the Teaching for Understanding in Information Technology Curriculum

Yang Xu, Ming-xuan Chen Jiangnan University Email:[email protected]; [email protected]

Abstract: Understanding has been considered to be of great value in the field of education. Only truly understand, the students can flexibly apply the knowledge to new situations outside the books. The current problems of the information technology teaching are that it ignored students’ understanding. Therefore, the promotion of students’ understanding is the essence of teaching characteristics. The instructional design for understanding emphasizes core issues and key skills, and enables students to understand technical operations, rules and laws, the scientific principles in the information technology, and attitudes and values of social issues.

Keywords: understanding, information technology curriculum, instructional design

Since 1980s, the information technology education has undergone several changes. From the programming teaching to the theory of information technology tools, it is gradually developing to cultivate the students’ information literacy as the core. The lacking deep-level knowledge mining restricts the pace of development of information technology education.

1. Understanding and the Teaching for Understanding 1.1. The Multi-dimensional Perspective of Understanding “Understanding” is one of the high frequency words in life and in education teaching. It refers to the process that applying prior knowledge to reveal the connection between the facts and to know new things. It also can be understood as the process of analysis, comparison, generalization and association, perception, logical and non-logical thinking to know the internal relations and the nature of things. There is a wide variety of ways of understanding from different perspective, but “What is the understanding?” It is difficult to have a clear definition.

Bloom said that understanding is not the accumulation of knowledge, unlike mechanical memory, true knowledge needs to apply the knowledge in new situations. Dewey said that what is the progress of true knowledge? One part is found from those understood things, the other is use tools understanding something is unclear and suspicious. In the book of Teaching for Understanding, the definition of understanding is the process of learning from simple to complex. And in the book of Bloom’s Taxonomy of Educational Objectives Amendment, understanding refers to constructing meaning into the teaching content and interpretations in different forms, such as instructions, classification, consolidation or the formation of general inference, comparison, making model to explain.

In this article, the meaning of understanding has three aspects, including migration ability, knowledge analogy and systematized. It not only refers to the accumulation of knowledge, but also

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 379 Proceedings of International Conference of Educational Innovation through Technology constructs the meaning of knowledge with the students’ experience.

1.2. What’s the Teaching for Understanding? The teaching for understanding originated from the United States, has launched a number of practical activities. Harvard University carried out the LTFU program; some scholars have proposed the method of instructional design. The U.S. National Research Council Committee advanced training program for high school students, from multiple perspectives of learning, curriculum, evaluation, they conducted in-depth research in the mathematical understanding and scientific understanding. In the book of the seven habits of highly efficient, Stephen R Carver said that “In order to make your actions not deviate from the correct direction, you must clearly realize that you will eventually where to go in the brain to produce an outcome to a clear understanding of the ultimate purpose.” Instructional design need to change the traditional curriculum design ideas to select the appropriate teaching content, make sure objectives, and organize the teaching activities.

1.3. The Teaching for Understanding in Information Technology Curriculum Understanding is not copy, mechanical knowledge, knowledge accumulation, superficial known, also is not the moment of “Epiphany”. The understanding of information technology means that students not only grasp the knowledge and ability of information and information technology, more should pay attention to the summary its method and law, and realize self construction, form correct concept of value judgment and information literacy. Therefore, information technology teaching should guide the student to understand the importance of the knowledge and skills, attaches great importance to the process and method of information and information technology, as well as the emotional attitude of information literacy, let students know (1) the scientific principle of the information technology; (2) the social issues involved information technology (emotional attitude values); and (3) the method, rules and laws of information technology operations.

2. Instructional Design Strategy of the Teaching for Understanding With relevant theories, in order to promote understanding, this study puts forward the five steps of teaching design model for understanding, including define the understanding objectives, design problem learning situation, make sure the performance of understanding, organize understanding activities , and the continuous evaluation. The instructional design for understanding in information technology curriculum can have a good use of these five steps.

2.1. Constructing the Core Teaching Content In the process of instructional design, the core concept is to help student in-depth understanding of the knowledge. The book” Comprehension Culture with the Curriculum Design” ( Grant • Wiggins and Jay • McTighe) pointed out the relationship between the subject content and the core content, course content is divided into three levels: the content what is worth lasting understanding, the content what is worth to know, the content what is worth to familiar with. The Core concepts are located in the centers of conceptual knowledge, including the important concepts, principles and theories, which are the main part of disciplines. According to students’ cognitive ability and experience, it has great significance in promoting the students’ understanding. At the same time, with the selection criteria of the core concepts, the information technology core concept can be defined as which exist in the surface of the knowledge easily overlooked but have deep mining, can

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reflect the focus of learning and teaching, can be used to build relationships with other knowledge and solve common problem in life situations.

Figure 1 The instructional design model for understanding

2.2. Creating Problem-based Learning Situation B·A·Cyxomjnhcknn said that “If the teacher doesn’t enable students to have high emotional intelligence in inner states, and eager to impart knowledge, then this knowledge can only engender apathy, and bring fatigue. “The practice has proved that positive thinking activity is the key to the success of classroom teaching. In order to improve the students’ learning interest, let students have active thinking, it is very important to create problem situation. Problem situation creation in the classroom is the basic condition of closely linked to students’ daily life, can make the students feel self consciousness and value.

2.3. Making Sure the Performance of Understanding According to the analysis, the information technology course contents include three aspects: the information science, the information technology ability, the information society, contains the basic knowledge and principle of “how to do”, procedural operation content of “does it”, and the ideological nature of the cognitive content “why to do”. From the view of psychology, the operation of the computer is based on procedural knowledge, but declarative knowledge play an important role in this process. With the complexity of the learning contents, learning from concept, action skills, program, learning method, etc., the study of information technology from cultivation to thinking skills, it is more and more emphasis on understanding, focused on practical problem solving ability. Therefore, the understanding performance assessment must be clear about learning outcomes. The description must be clear, operational evaluation.

2.4. Designing Learning Activities Teaching activities design plays an important impact on the learning activities and effects, which need to respond to students’ natural learning styles and prior knowledge to analyze. The motivation is the underlying reason to give a powerful driving force to promote students learning. For example, learning needs, interests, habits, learning objectives, learning motivation are all the

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reflection of the students’ subjective initiative; And learning style combines learning strategies and learning orientation, is the personality learning way. Learning activities is the implementation process of teaching practice, it is necessary for teachers in timely manner scaffolding to give support for students’ understanding. At the same time, according to the core disciplines, it is possible to design different types of learning activities, such as situational experience activities, inquiry-based activities, and problem-solving class learning activities.

2.5 Evaluating the Effectiveness of Learning The Information technology knowledge contains mainly four areas: factual knowledge, theoretical knowledge, procedural knowledge and met-cognitive knowledge, namely, the grasp of knowledge, skills application, the principle method and emotional and moral internalization. With the characteristics of learning for understanding, combined with the information literacy requirements, evaluation can not be generalized divided into understand and do not understand. The teaching for understanding in Information technology curriculum evaluation should adopt comprehensive evaluation methods, focusing on students’ performance in the problem situation and the awareness of team cooperation, emphasizing the various comprehensive surveys.

3. The Experimental Teaching for Understanding Based on strategies of teaching for understanding, this study design and organize the experimental teaching, content and arrangement as shown in following table. Experimental Teaching Contents Arrangement Excel Number Theme Content Information acquisition, data collection and statistics, and 1 About Excel compares the differences between Word and Excel To achieve different types of data entry, understanding the 2 Data input and cell operation relationship between data types with cells Beautify the table, further attributes and skills, understand Table planning, editing and 3 the significance of cell, can produce form in different beautification working table Understand the formula components, data statistics by 4 The formula in Excel formula method Understanding of several commonly used functions, the 5 The function in Excel relationship between the formula method and function method to master data 6 Data analysis Screening, sorting and summary According to the table select the chart, understanding each 7 The chart and data analysis attribute of the chart 8 Data statistics and analysis Comprehensive teaching activity Figure 2 Experimental Teaching Contents Arrangement

In order to verify the effectiveness of the teaching design patterns and strategy, this study adopted quasi-experimental method. We select a class using the method of the teaching for understanding and a comparison class using the method of traditional teaching.

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3.1. Constructing the Core Teaching Content For example (Teaching activities for understanding):”About Excel” is the first lesson of the contents of this unit, according to the course of analysis, the core problem is not let students’ acquisition of Excel software basic operation skill, but to cultivate students’ ability of information acquisition and collection. The teaching goal: 1. Combined with the example, let students to collect life data, master the method of data collection and statistics; 2. Through the method of data collection, analyze the function and advantages; 3. Through the production, speak the basic elements and relations of the tables.

3.2. Creating Problem-based Learning Situations For example (the teaching for understanding): The class are divided into several groups let the students to collect team member’s name, age, gender, height, weight and other information. The problem closed to the students can stimulate interest in learning. Let the students show the information in the paper; guide the students to pay attention to the type and unit data, to think of the relationship between statistics and tables. Then let the students talk about the collection and statistics method for each group.

3.3 Making Sure the Performance of Understanding Knowledge type and understanding

Content What to do? How to do? Why to do ? Try to do and speak To use their own Study habits and Task to someone language to speak expression method Problems, practice Observation, open-ended Performance way Observe, question answer task. questions

Verb Find and show Complete and application Concludes, show

Comprehension Interpretation, Paraphrase, insight Self awareness, empathy Level application Figure 3 Understanding performance 3.4 Designing Learning Activities For example (Teaching activities for understanding): Let the students do it as follows: Data is represented by algebraic expressions, including a total of 1 and a total of 2 is the value of B1-B5, a total of 3 is the address of B1-B5, and press the Enter key, find the differences: Total 1: 147+144+156+148+149 Total 2: =147+144+156++148+149 Total 3: =B1+B2+B3+B4+B5 Please observe the differences of three total column results?

3.5 Evaluating the Effectiveness of Learning For example (Evaluation of teaching for understanding):

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Activity Name: About Excel Evaluation Hierarchy Concept 1 Concept 2 Concept 3 Understanding The characteristics and Explain the differences Explains the concept function of table between Excel and Word of working table, workbook Application Knowledge transfer, Input and modify data simple operation of Excel, such as open, save, create Insight The difference and connection between the workbook and working table Self perception Use the form to solve real The role of Technology life problems Figure4 Learning Evaluation 4. Conclusion According to the data analysis before and after the test, in terms of learning attitude and methods, two groups of students have significant difference. It shows that the experimental group students gradually recognized the value of information technology curriculum through understanding teaching method. Teachers’ teaching method and the student’s study way also have gradually improved. The strategy of Teaching for understanding helps students to understand deeper knowledge, enhance understanding ability.

“To help students understand” is the essence characteristics of teaching. Taylor believes that education objects aimed at identifying the change of students, in order to design a variety of activities and point to the established target. The understanding of the information technology course is not only to acquire knowledge and skills, but also the ability and cogitation. Introducing the idea of instructional design for understanding is conducive to the professional development of teachers, help to change the traditional way of thinking and the inertia of the teachers. And it is also better for students to improve application ability.

References Feng, D. H. & Ma, Y. (2003). The causes of the occurrence and the logical starting point of the teaching the understanding, Guangxi Normal University (Philosophy and Social Sciences). Bloom.(1986). Taxonomy of educational objectives, East China Normal University Press. Lv, L. H. (2005). Research on the teaching and learning for understanding. East China Normal University. Chen, J. G. (2009). The rise of teaching for understanding in the United States and its implication in our education, Modern Education. Sang, X. M.. (2006). Learning science and technology: college students’ learning capacity-building in information age, Higher Education Press, 2006. Driscoll, M. P. (2008). Psychology of learning: teaching-oriented, East China Normal University Press.

384 EITT 2013, Williamsburg, VA, USA, November, 2013 Zhang, Z. C. (2013). Access and use of ICT: an exploratory study of Canadian and Chinese students. Proceedings of International Conference of Educational Innovation through Technology, 385-392.

Access and use of ICT: An exploratory study of Canadian and Chinese students

Zuochen Zhang University of Windsor Email:[email protected]

Abstract: This paper reports preliminary findings of an exploratory study that examined two secondary schools, one from a big city in eastern China, and the other from a middle-sized city in eastern Canada. Data were collected using a paper-based survey questionnaire which included both multiple choice and open-ended questions. Responses indicate that ownership and access to ICT devices were quite similar between Canadian and Chinese participants, but the learning and use of ICT between the two groups of participants differed due to various reasons. It seems the Chinese participants relied more on classroom learning, and teachers of the Chinese participants did not integrate much use of ICT outside of the classroom. With support from the literature and findings of this study, this paper intends to argue that, with ICT access becoming a less critical issue, it may be necessary for Chinese educators to make more efforts to take advantage of ICT, and try to make full use of ICT available to students for teaching and learning purposes.

Keywords: ICT access, ICT use, learning, Canada, China

1. Introduction With the advancement of various types of Information and Communication Technologies (ICT), personal computers, Internet, mobile phones, digital music players, online games, etc. are being used increasingly in educational settings as well as in other fields (Adcock & Bolick, 2011) because of numerous pedagogical benefits (Buechler, 2010).

China has experienced fast developments in recent years, and the increase in the access and availability of ICT, especially Internet-connected computers and mobile phones are dramatic. Nowadays, many elementary and secondary school students, whether they are from cities or the countryside, although to different degrees, can access the Internet from school, home or Internet cafes that are widely available in their communities. Compared with computers, mobile phones are more ubiquitous among secondary school students countrywide. The Chinese government emphasizes the importance of ICT in education and has in recent years started a number of initiatives to promote use of ICT in education, but there are many difficulties with integrating ICT into education due to various reasons (Li, n.d.).

In terms of access to ICT, in 2009, Canada “was tied for second in the G8 with the USA” (Human Resources and Skills Development Canada, 2013), at a ratio of 1.4 15-year-old students for each computer across the country (Statistics Canada, 2012). However, due to factors such as language barrier, gender, geographic location, and especially socio-economic status (SES), digital divide remains an issue in Canada. In order to bridge the divide, besides efforts from the government, charity organizations like Sky’s the Limit Youth Organization (STL) are providing refurbished computers to

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 385 Proceedings of International Conference of Educational Innovation through Technology under–resourced youth across Canada (Government of Canada, 2011). Many teachers view access as one of the top challenges to technology integration (Gao, Choy, Wong & Wu, 2009). In some schools where ICT are available, they are still ineffectively and under-used by most educators (Chen, 2010; Mueller, Wood, Willoughby, Ross & Specht, 2008), as they often fail to use technology in ways that promote students’ knowledge construction. The use of technology as a pedagogical tool cannot be fully realized unless there is adequate technical support and modeling within a school (Teo, Lee, Chai & Choy, 2009), which means the school culture in terms of ICT integration directly effects teachers’ use of ICT in the classroom (Hammond et al., 2009).

The objective of this study was to understand what types of ICT are available for secondary school students in Canadian and Chinese schools, and how they are utilized in and outside of schools, especially participants’ access to ICT, ways they learn and use them, and possible reasons for these phenomena.

2. Literature Review Over the last two decades, the use of Information and Communication Technologies (ICT) has been an important topic in education. Faced with the fact that ICT have penetrated to every corner of our daily lives, scholars have advocated the necessity to develop students’ ICT literacy. Students today belong to the generation that is sometimes referred to as “Net Generation”, who are accustomed to operating in a digital environment for communication, information gathering and analysis (Oblinger, 2004), and it is believed that these people are tech-savvy and their preferable way of learning is represented by ICT (Oblinger & Oblinger, 2005). Studies have indicated that ICT can enhance teaching and learning in different disciplines (Sutherland, et al. 2004). For these reasons, most curriculum documents state the importance of ICT and encourage school teachers to use them. Particularly, ICT implementation becomes a key factor that leads to school curriculum reforms in many regions.

Access to ICT, once identified as one of the major barriers to teachers’ use of technology (Fabry & Higgs, 1997; Lehman, 1994), has become a less critical issue. As various kinds of ICT such as computer hardware and software, Internet, digital camcorders and cameras, digital music players and mobile phones become available and affordable, people from both developed and developing national now at a certain degree have access to one or more kinds of ICT, so nowadays what is expected of educators is to help learners use technologies not only for social purposes, but also for learning purposes (Kennedy & Levy, 2009). Attewell (2004, p. 16) asserts that “Mobile phones and PDAs are no longer just for chatting and organising contacts and diaries, they are now pocket-sized computers and as such have the ability to deliver learning objects and provide access to online systems and services.” Given the fact that mobile phones are widely used among young people, one of the remaining issues about the use of ICT in schools is how it is integrated into the curriculum (Plante & Beattie, 2004), and this integration takes efforts of administrators, educators and students themselves.

In schools, factors that influence the integration of ICT include access, support, and the school culture. People from both developed and developing nations now to a certain degree have access to one or more kinds of ICT, but they are under-used by most educators (Chen, 2010). It is suggested that the use of ICT as a pedagogical tool cannot be fully realized unless there is adequate technical

386 EITT 2013, Williamsburg, VA, USA, November, 2013 Access and use of ICT: An exploratory study of Canadian and Chinese students support and modeling within a school (Teo, Lee, Chai & Choy, 2009), which means the school culture plays an important role in ICT integration (Hammond et al., 2009).

Research shows that although nowadays most secondary school students in Canada have access to ICT at home as well as at school, integrating ICT into the teaching and learning in school is still a challenge (Martinovic & Zhang, 2012; Plante & Beattie, 2004). The Chinese government emphasizes the importance of ICT in education and has in recent years started a number of initiatives to promote use of ICT in education, but there are many difficulties with integrating ICT into education due to various reasons (Li, n.d.). By comparing two schools, this study aimed to investigate the contexts of Canada and China to find similarities and differences in terms of ICT access, learning, and use.

3. Research Methodology In this exploratory study, a survey questionnaire was used to collect participants’ demographic data and their self-report of access, learning, and use of ICT at home and at school, and their perspectives of and attitudes towards ICT use for learning. The purpose of the questionnaire was to collect both qualitative and quantitative data which helped the researcher to understand the research questions about the access, learning, and use of ICT in Canadian and Chinese schools.

The questionnaire was administered at two secondary schools, one in eastern Canada and the other in eastern China and each school had about 100 students participating in the study. The research participants were grade 8 and grade 9 students who represent a diverse population in terms of age, gender and SES.

The frequencies and percentages of close-ended responses were calculated, and frequency tables and bar charts were created using Microsoft Excel. These figures were used to present relationships that existed among certain variables (Creswell, 2005). Text-based and open-ended responses were typed in Microsoft Word and subsequently categorized and colour-coded according to (a) the question itself, and (b) a theme identified with the participant’s response. Where possible, the qualitative data were quantified to present frequencies. Through direct quotations from participants, recurring variables, themes, and frequencies, the qualitative data were used to support the quantitative questionnaire data.

4. Findings A preliminary analysis of research data indicates that most participants had access to a variety of ICT, a phenomenon shared by Canadian and Chinese students. Participants in the two contexts had access to similar amounts of ICT both at home and at school, and using ICT for social and/or entertainment purposes was equally important for both groups of participants. But due to educational systems, their living environments, and their school cultures, Canadian students seemed to be more encouraged to participate in the ICT mediated learning activities while their Chinese counterparts mainly use ICT for resource searching or personal communication.

By examining a few aspects of ICT ownership, access, learning, and use, the following subsections are intended to illustrate similarities and differences between Canadian and Chinese secondary school students who participated in the study.

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4.1. Ownership and Access to ICT Devices at Home 4.1.1. Canadian participants. To the question “What ICT devices do you have access to at home?” almost 40% reported having a cell phone, 57% reported having a smartphone, and about 86% reported having a gaming device. Almost 70% reported having a mobile computer and over 40% reported having a tablet computer, which indicates that there was a great potential for students to access online resources and learning environments if a reliable wifi was provided. These participants reported that they were allowed to bring their ICT devices to school and they would use their wireless devices to access the Internet in and out of the classroom for learning resources and activities.

4.1.2. Chinese participants. In terms of ownership and access to ICT devices at home, it seems that Chinese participants had a higher ratio (cell phone, 50%; smartphone, 95%; mobile computer, 93%, and tablet computer, 78%) except for gaming device (42%). These participants reported that they were not allowed to bring their ICT devices to school, and they did not have much time to use them at home as they reported “having a lot of homework to do after school.”

4.2. Resources for Learning How to Use ICT 4.2.1. Canadian participants. In their response to the question asking from what resources they learned to use ICT, a great majority (79%) said they learned from their friends, 56% said they learned from their teachers, and 73% said “I like to play around”. This could be interpreted that collaborative learning plays an important role in the learning experience of these students, and an interpretation could also be made that, in terms of learning ICT, most of these research participants had the preferred learning style of experiential learning.

4.2.2. Chinese participants. In response to the question asking from what resources they learned to use ICT, a similar percentage (72%) said they learned from their friends, which could be interpreted that collaborative learning also takes please among Chinese students, at least in terms of learning how to use ICT. However, the percentage of responses regarding learning from teachers (79%) and “I like to play around” (57%) was sort of reversed compared to those of the Canadian participants. Maybe this could be interpreted that Chinese students rely more on classroom learning while Canadian students apt to employ more experiential learning, at least in terms of learning ICT.

4.3. Use of School/Teacher Websites for After Class Learning 4.3.1. Canadian participants. When asked how often they accessed the school website/ teacher webpages, 75% reported doing it daily/frequently. Responses to follow-up open-ended questions show that the frequency of the access to such websites positively correlated with the frequency of updates of the content in those spaces. Students checked the school website for announcements and reports, and as some teachers frequently posted assignments and course materials on their webpages, students would often visit the webpages for their learning outside of the classroom. Some students reported making frequent visits to the website/webpages as a venue to learning about events of the school, and also used them as a reminder for school activities and assignments.

4.3.2. Chinese participants. Responses to this question was quite different from those of their Canadian counterparts. Only 10% of the participants reported that they would access their school

388 EITT 2013, Williamsburg, VA, USA, November, 2013 Access and use of ICT: An exploratory study of Canadian and Chinese students website or teachers’ webpages. In response to the follow-up open-ended question about the reason for the response, most stated that the school website was “boring” or “worthless” and their teachers did not have course webpages. This could be interpreted that this group of students did not make much use of the online space of their school or teachers because they believed that they could not find much in the spaces that would be interesting or useful for them.

5. Limitations of the Study The major limitations of this study lie in the areas of data types and participant representation. In terms of data types, although both quantitative and qualitative data were collected with a survey instrument, some more in-depth investigation needs to be carried out to obtain answers to questions such as why the school of the Chinese participants would not allow students to bring their ICT devices to school, what the Chinese participants used their smartphone for, what they would like to see on their school website, etc. Future studies need to be carried out to involve a bigger variety of schools in terms of student population, school culture, and socio-economic status, and include interviews and focus group discussions in order to gather richer data that could be used to strengthen the results of the study.

6. Concluding Remarks With the increasing availability and affordability of ICT in both Canada and China, especially given the fact that, even though there are differences as to what ICT are more widely used depending on geographical locations, Internet connected computers and mobile phones are ubiquitous among the youth. So educators and educational policy makers need to pay attention to this phenomenon and find ways to make best use of the available ICT by developing e-learning programs, and at the same time, encourage teachers and students to take advantage of ICT to enhance teaching and learning. Currently it seems that the ICT, especially mobile phones, are mainly used for social purposes such as daily communication and entertainment, and this may be because there are not enough e-learning programs that have been developed to streamline the connection between the available ICT and students’ in school and out of school learning. Some research has been conducted to find positive results on mobile learning in some developed countries, but as digital devices, especially mobile phones are getting more and more widely used in many developing countries, researchers and practitioners in the domain of education have the responsibility to advocate a better understanding of the advantages of various kinds of e-learning and implement pedagogy aligned learning environment in the technology-rich societies.

Based on the findings, it can be concluded that nowadays ICT access is no longer a crucial issue in some schools (Fabry & Higgs, 1997), but in order for students to take advantage of ICT in their learning, it is highly necessary to encourage and help educational policy makers and teachers to realize the important pedagogical values of ICT as a leaning enhancer, and build a school culture that better meets the learning needs of the “Net generation”, who grew up with ICT, but does not necessarily know how to use them for their learning purposes (Oblinger & Oblinger, 2005).

The wide availability of mobile phones, especially smart phones, among secondary school students in China provides great potential for these students to experience flexible learning. With proper support from different levels of administration, it is very likely that educators in China will

EITT 2013, Williamsburg, VA, USA, November, 2013 389 Proceedings of International Conference of Educational Innovation through Technology be motivated to find ways to make full use of the ICT students have access to by developing learning resources for mobile phones, and design online learning activities that engage their students both in and outside of the classroom.

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References Adcock, L., & Bolick, C. (2011). Web 2.0 tools and the evolving pedagogy of teacher education. Contemporary Issues in Technology and Teacher Education, 11(2), 223-236. Attewell, J. (2004). Mobile technologies and learning: A technology update and m-learning project summary. London, UK: Learning and Skills Development Agency. Buechler, S. (2010). Using Web 2.0 to collaborate. Business Communication Quarterly, 73(4), 439-443. Chen, R. (2010). Investigating models for preservice teachers’ use of technology to support student- centered learning. Computers & Education, 55(1), 32-42. Creswell, J. (2005). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (2nd ed.). Upper Saddle River, New Jersey: Pearson Education. Fabry, D., & Higgs, J. (1997). Barriers to the effective use of technology in education. Journal of Educational Computing, 17(4), 385–395. Gao, P., Choy, D., Wong, A., & Wu, J. (2009). Developing a better understanding of technology based pedagogy. Australasian Journal of Educational Technology, 25(5), 714–730. Government of Canada. (2011). Building digital skills: Increasing computer access to under– resourced youth in Canada. The Digital Economy in Canada. Retrieved from http://www.ic.gc. ca/eic/site/028.nsf/eng/00420.html Hammond, M., Crosson, S., Fragkouli, E., Ingram, J., Johnston-Wilder, P., Johnston-Wilder, S., Kingston, Y., Pope, M., & Wray, D. (2009). Why do some student teachers make very good use of ICT? An exploratory case study. Technology, Pedagogy and Education, 18(1), 59-73. Human Resources and Skills Development Canada. (2013). Indicators of well-being in Canada. Retrieved from http://www4.hrsdc.gc.ca/[email protected]?iid=28 Kennedy, C., & Levy, M. (2009). Sustainability and computer-assisted language learning: Factors for success in a context of change. Computer Assisted Language Learning, 22(5), 445-463. Lehman, J. R. (1994). Secondary science teachers’ use of microcomputers during instruction. School Science and Mathematics, 94(8), 413-420. Li, C. (n.d.). China: ICT use in education. UNESCO Meta-survey on the use of technologies in education. Retrieved Jan. 6, 2010 from http://www.unescobkk.org/fileadmin/user_upload/ict/ Metasurvey/CHINA.PDF Martinovic, D., & Zhang, Z. (2012). Situating ICT in the teacher education program: Overcoming challenges, fulfilling expectations.Teachers and Teacher Education, 28(3), 461-469. Mueller, J., Wood, E., Willoughby, T., Ross, C., & Specht, J. (2008). Identifying discriminating variables between teachers who fully integrate computers and teachers with limited integration. Computers & Education, 51(4), 1523-1537. Oblinger, D. (2004). The next generation of educational engagement. Journal of Interactive Media in Education, 8.Retrieved from http://www-jime.open.ac.uk/article/2004-8-oblinger/199 Oblinger, D. G., & Oblinger, J. L. (Eds.). (2005). Educating the Net Generation. Washington, D.C.: EDUCAUSE. Retrieved from http://net.educause.edu/ir/library/pdf/pub7101.pdf Plante, J., & Beattie, D. (2004). Connectivity and ICT integration in Canadian elementary and secondary schools: First results from the Information and Communications Technologies in Schools Survey, 2003-2004. Retrieved from http://www5.statcan.gc.ca/bsolc/olc-cel/olc- cel?catno=81-595-MIE2004017&lang=eng Statistics Canada. (2012). Education indicators in Canada: Report of the Pan-Canadian Education

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Indicators Program. Ottawa, Statistics Canada, 2012. Sutherland, R., et al. (2004). Transforming teaching and learning: Embedding ICT into everyday classroom practices. Journal of Computer Assisted Learning, 20, 413–425. Teo, T., Lee, C.B., Chai, C.S., & Choy, D. (2009). Modelling pre-service teachers’ perceived usefulness of an ICT-based student-centered learning (SCL) curriculum: A Singapore study. Asia Pacific Education Review, 10(4), 535–545.

392 EITT 2013, Williamsburg, VA, USA, November, 2013 Zhao, L. & Zhang, S. (2013). Development of visual philosophy under impact of philosophy of technology. Proceedings of International Conference of Educational Innovation through Technology, 393-402.

Development of Visual Philosophy under Impact of Philosophy of Technology

Li Zhao, Shuyu Zhang Nanjing Normal University Email:[email protected], [email protected]

Abstract: Philosophy focuses on the origin and essence of things, and is the basis and foundation of other superficial research. Technology as a tool and one of thinking methods has penetrated into every field, and deeply affected the study of philosophy. Philosophy of technology asa branch of philosophy has formed. Research on visual philosophy has also been affected by philosophy of technology. Although the formal definition of visual philosophy is not clear, people’s thinking has been affected by the visual phenomena till today. There are plenty of research achievements of revealing laws of visual phenomenon from the view of philosophy. However, it must be realized the impact of the power of technology in the development of visual philosophy. The research on the development history of visual philosophy from the perspective of instrumental and humanistic theory of technology can help us realize the profound meaning and development direction of visual philosophy.

Keywords: development, philosophy of technology, technology, impact, visual philosophy

1. Introduction Philosophy focuses on the origin and essence of things, and is the basis and foundation of other superficial research. If one study wants to make progress, it must go back to philosophy itself. The study on vision, visual, visual literacy, and visual culture also need to return to the “visual philosophy”. In the development process of the visual philosophy, technology plays an important role. It’s a coincidence with what we called “technology shift” today. In modern society, the form of technology has penetrated into every field. The study on vision is no exception. In different historical period of visual philosophy, technology plays an important decisive role. Technology even promotes the development of visual philosophy. Either in the long history of visual philosophy, or in today’s image world, technology is intertwined with vision. Today, technology is no longer the meaning of a representational level. There are a lot of results on the study of the arising and development of technology and philosophy of technology. From the study on technology and philosophy of technology, visual philosophy can help to clarify the logic development of visual philosophy, and realize the significance and value of the research of visual philosophy.

2. Philosophy, Philosophy of Technology, Visual Philosophy Philosophy is the important tool for the human world to know and transform the world. The object of philosophical research is the relationship between human and nature. It gets to the bottom of the matter of the problem for an answer. Philosophy of technology and visual philosophy is about specific research in the field of philosophy. Philosophy of technology already has mature system of research. At present, technology has penetrated into every field and subjects, and also influenced visual philosophy. Although visual philosophy has not been lodged from the history

EITT 2013, Williamsburg, VA, USA, November 4 - 6, 2013 393 Proceedings of International Conference of Educational Innovation through Technology of visual research, it has formed a clear research context. To establish visual philosophy research framework, theories and methods of philosophy and philosophy of technology are helpful for the research of visual philosophy.

2.1. Philosophy and its Universal Values The word philosophy derives from Greek philosophia, formed by Philos and Sophia. Its meaning is “love and wisdom”. Philosophy pursues the world’s origin, nature, common or absolute. Its research content is the scientific methodology of understanding and transforming the world. There has always been controversial for “what philosophy is”. The study of philosophy lasts for along time. This research field evolving along with the development of times has the distinct characteristics. Philosophy has produced different branches of philosophy, such as natural philosophy and philosophy of science, philosophy of technology, etc. The consensus view of philosophy research is that philosophy is a kind of method. Problems which can’t find the answer can be attributed to the study of philosophy. Philosophy also can solve the problem of what things are. Meanwhile it can give things definite descriptions in terms of definition and concept. Research on philosophy is based on rational thinking. It is not a simple description of phenomenon, but is based on the nature of thinking. Objects for philosophical research are the universal laws of nature, society and human minds. Though the description of the philosophy is not the same, from the descriptions above all, you can find the value and significance of the research of philosophy. The reason why philosophy can have a far-reaching effect on other research fields and disciplines is that the philosophy has characteristics of holistic, fundamental and common sense thinking. Therefore, philosophy has universal significance and value for further study of other fields and disciplines with the long-term development.

2.2. Philosophy of Technology: Guidance of Philosophy to Technology and Technical Contribution to Philosophy The development of technology has been the center of attention for a long time. Technology has been considered to be an important tool for human to understand and transform the world. Technological advances usually refer to the technical material force to the high, fine, sharp, forward, and thus recognition and understanding of technology is stuck on the level of tools and media, which belongs to the material level, known as technical natural attributes, “positive value” of humanity to transform nature. However, as the intermediary of man and nature, the value of technology and technology alienation bring us to think the value of technology for people. What is technology cannot be defined only from the viewpoint of the tool or medium. Technology alienation has brought about the negative effects on human, which needs to answer what the nature of technology is, what the value of technology is and the influence of post-modernity to technology. Whether technical rationality means the technology itself has the ability of rational thinking, nor the creation of technology has the ability of reason and thinking, the answers to these questions must be searched from philosophy. Philosophy is thinking about the nature of things. Any essential research should be attributed to the study of philosophy. Philosophy of technology proposes precisely to solve these problems. In the research process of technology, the generation and development of philosophy of technology needs for the enlightenment and guidance of philosophy from the ontological and methodological level.

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Secondly, the study of philosophy of technology has made its due contribution to the study of philosophy. Since the industrial revolution, the influence of technology has penetrated into various fields and disciplines. Technology has developed from a radical improvement inthe level of people’s material needs and to meet the people’s needs for survival, and has challenged people’s rational thinking. Philosophy aims to study the relationship between man and nature, and technology plays an important role in the study of the relationship of man and nature. From the perspective of the significance of the relationship of man and nature, philosophy is divided into three branches: the narrow natural philosophy, natural ontology; philosophy of science, natural epistemology; philosophy of technology, natural transformation theory, which shows that research of philosophy of technology plays an important role in the study of philosophy. The sudden emergence of philosophy of technology is a direct manifestation of the important impact on the study of philosophy; it is also an important contribution to the study of philosophy. The study of technology shift also exerts a profound impact on other areas of philosophy, including visual philosophy. This mingled relationship makes philosophy of technology occupy a very important position in the whole philosophy of research areas. The penetration of technical philosophy in other areas is the important value performance in the study of the relationship between man and nature. Fundamentally speaking, the study of philosophy of technology has opened a window to analyze and solve problems from a technical level, and has improved the system of philosophy.

2.3. The Inevitable Emergence of Visual Philosophy Philosophy is a universal sense of ontological and methodological research. The theory and practice of the visual theory also needs to seek the guidance of methodology from philosophy. In the analysis of vision, which serves as a sensory awareness and understanding of a kind of thinking, the interpretation of what the vision is seems not easy. Then the questions to the principle of vision, visual law and the relationship of vision and thinking will inevitably go to philosophy to find the answer. Visual philosophy is philosophy about visual research. This study has existed in the practical activities of the people in the process of understanding and transforming the world. The philosophers, in the ways of thinking relationship between man and nature, are impossible to ignore the cognitive effect of the eyes, “window of the soul”. Vision and thinking have always been inextricably linked. “More than 70% of the feeling of receiving of the human body is concentrated on the eyes”. To understand the problem of vision is to understand people’s thinking. Turning over the history of the study of philosophy, the study of vision philosophical inquiry can be found everywhere. From great thinkers such as Plato and Aristotle, who are builders of visual centrism, to Cassirer, Benjamin, Heidegger, whose rational understanding and reflection are famous to all. As can be seen, the study of vision does not stay on the superficial surface of visual centrism. In different historical periods, it demonstrates the rich connotation and research to help humans better understand and transform the nature. Visual philosophy has been in progress and it also responds well to the things related. However, it just has not yet established a clear and completely theoretical system. Philosophical research method will guide all kinds of visual research; visual theory and practice research also serve as a contribution to the study of philosophy.

3. Origins of Visual Philosophy From various sources, studies on the philosophical basis of visual culture and the philosophical study on the image culture is not uncommon. But it is quite rare to clearly clarify the term “visual philosophy”, which is not similar to the study of natural philosophy, philosophy of science,

EITT 2013, Williamsburg, VA, USA, November, 2013 395 Proceedings of International Conference of Educational Innovation through Technology philosophy of technology, which has the starting point and certain study contents. Throughout ancient and modern philosophers and thinkers, there arose no such person that was regarded as a clear crown as the representative of the “visual philosopher”. However, whether in the course of the division of the essence of vision, or a reflection of the current visual appearance and essence, study on the philosophy of “visual” essence has never stopped and has always been extended. Countless sages in history have been discussing this topic. From their discussions, two visual clues can be clarified in the philosophical development: the discussion about the “visual centrism”; the shift of philosophy from language to vision.

3.1. Prosperity and Collapse of Visual Centrism Of all the problems, the core of visual philosophy is nature of vision. What is the vision? In the tradition of the western culture, the vision has always been considered to be the noblest of all the senses. Like the soul, vision is like a noble reason existing out of the flesh. The establishment and development of visual centrism can be traced back to ancient Greece, Plato, in the name of Timai Oswald, said: “In my opinion, vision is the source of our most useful things ... God invented vision, and ultimately it is given to us so that we can see the rational process in heaven, and can in turn apply this process to our own rational process.” Aristotle, the founder of the visual centrism said in metaphysical, “the pursuit of knowledge is human nature. We are pleased to feel is a description; Even if there is no practical purpose, people love feeling, and among all feelings, vision matters most.” The status of the visual centrism to ensure the purity of people’s philosophical and rational thinking is critical. Visual centrism in modern times still has a lot of supporters, American phenomenologist Hans Jonas, said in a paper entitled noble vision, “only the vision can provide foundation for feeling, through vision the mind can produce long-lasting concept, or the eternal and the ever-present concept”, “and thus where vision touches, the mind will be able to reach.”

However, with the arrival of the image of the world, structuralism, and post-modern thoughts constantly impact on the status of the visual centrism. The visual rational cognitive has been questioned. Omnipresent seeing and be seen are intertwined, confusing eyes. The link between the visible things and its represented invisible things is not so tight. What you have seen is not the nature of things. Behind the visual representation there’s nothing! Mechanical reproduction in the machine industrial age has created numerous visual impressions, which is dreamy. When the vision sees purely visual representation, there has not been the difference between real and representation, the essence and phenomenon. From Iraq Debord’s “spectacle society” description to Anne Frye Berg interpretation of “the social image value-added”, to Baudrillard’s “Simulacra”, the attention to visual object features which visual centrism advocated for has been overthrown, and visual philosophy research should focus on visual objects and the possibility mechanism of looking behavior. Thousands of years of visual centrism buildings collapsed in the process of human’s understanding and transformation of the world. This understanding is an important breakthrough in the visual study of philosophy. If the study on visual philosophy only focuses on visual object, the audience will be more confusing and fall. At present the important content of studies on visual philosophy is concerning the relationship of seeing and being seen, the mechanisms of looking behavior from “look” to “see” to “read”.

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3.2. Shift of Philosophy of Language to Visual Philosophy The process of visual centrism from the establishment to the collapse is an explicit clue of the historical development of visual philosophy. From the shift of understanding and characterization of human knowledge, there is an invisible clue for the development of visual philosophy. The attention on visual philosophy from two shifts is from the peak to the trough and then rising again, moving forward difficultly. An important trend of the 20th century in Western philosophy is a “linguistic shift”, in which this understanding is based on modern philosophers’ concerning “ideology”. Ancient philosophers are concerned more about the things themselves, what is the look of its own form of things, or visually visible characteristics (i.e. visual centrism). Modern philosophers thinking of an accurate understanding of the things must be described from the “concept”, which is expressed through language. The status of the noble visual sensory capacities is in decline. The precise degree of expression by language is directly linked with rationality, wisdom, logic. To the mid-19th century, however, no prophet can predict the emergence of photography, telephones, movies and their great impact on the language. The concept of “visual culture” during this period, which is the important theoretical results of visual philosophy, was mentioned here. University of Chicago scholars W J • T • Michelle put forward “visual culture is the culture separated from the rational form of language, increasingly turning to the image centrism, especially to the movie- centric sensibility morphology. Visual Culture not only marks changes and formation of one kind of culture, but also means a conversion of the paradigm of the human mind”. Seeing by language is a big step forward in thinking. Language is the spokesperson of wisdom. In picture era, the visual image can express the idea that language cannot explain. In front of the vivid images, language is pale. Image also can be “read out” beyond language to express the unity of a variety of connotations. The shift from “seeing” by language to using these images to “read”, broke the center position of “language”. The visual ration has pushed to the foreground. This shift marks visual philosophy is bound to rise.

Visual image is prevailing today. The status of vision has been highlighted, but the thinking of the nature of vision also puzzles us. Today we don’t need to cheer the success of visual shift, but need to focus on the mutual conversion of language and vision. In the visual image world, can language rationality smoothly shift to visual rationality? Maybe not. Reading the text does not mean the capability of reading the image. The lack of visual literacy is an urgent problem. In the same way, visual philosophy will no longer be easily turned to the philosophy of language. People who used to read images, gradually has poor ability of text reading and express by language. This seems to be helpless, but also it extends the research content for visual literacy. The training of visual literacy should be the awareness, understanding and use of all forms of visual characterization.

4 The Influence of Philosophy of Technology on Visual Philosophy The development of technology which has always focused on the attention of technology function can be roughly summarized as technical tools theory, technology media theory, technical rationality and technological humanistic theory. Technology as an important symbol of human progress has been the main tool of the human conquest of nature. It is the grounds of technical tools theory. From ancient times people are seeking a more high-end, sophisticated and convenient technology to transform nature, so the technology can be seen as a medium of communication between man and nature. In the face of negative effects brought about by the technology, people have deep thinking about the technology. It is worth studying that technical rationality stems from

EITT 2013, Williamsburg, VA, USA, November, 2013 397 Proceedings of International Conference of Educational Innovation through Technology human or technology itself. Philosophy of technology which aims to find the nature of technology has a profound impact on the development of philosophy. Philosophy of technology also influences the development of research on vision and visual philosophy.

4.1. Study on the Impact of Technology to the Development of the Visual Philosophy from the Perspective of Instrumental Theory It is not difficult to see that the two clues “Visual Centrism and “Visual shift” are in parallel in the development history of visual philosophy. The development of visual philosophy has gone through three historical periods: the era of visual centrism, the era of anti-visual centrism, visual literacy training period. There are three different tools appearing in the three different periods: from the mirror to the camera to the computer. In fact, learning from symbol philosophy proposed by German philosopher Ernst Cassirer, you can find the important revelation of philosophy of technology to visual philosophy implicit in the representation of technical morphological changes.

German philosopher Ernst Cassirer has deep thinking and research on “Symbol Philosophy”. He believes that in the course of human evolution, the symbol has also experienced a different evolution. The symbol showed as an icon experiences in the initial stage. Icon is the equivalents of nature, directly facing the nature, reflects real natural attributes. In this case, the symbol function is like a mirror. The first symbolic development stage corresponds to the period of “mirror” morphology of the technology. A mirror faces the characterization of the object as a technical tool. A mirror reflects a true representation of objects. The visual object and characterization of objects is a peer-to-peer relationship. The elegance and authority of vision established the centrality of the vision.

In the second symbol development historical period, the relationship between the reality and vision had changed. The trait between the symbol and the reality was no longer a simple replication relationship, but a causal relationship. There is the complexity of the intermediation process. In this case, the function of a symbol was like a camera. Camera technology principle determines its performance, which no longer simply copies characterized objects. Not only does the lens of a camera have selectivity, but also has a shielding property. Photos only render the tip of the iceberg of things. The reason why the photo presenting to the audience is such a tip of the iceberg, rather than any other part, is the complex causal relationships. Presented characterization does not truly reflect the visual object itself. Getting essential cognition of objects from phenomenon has more obstacles. Looking does not mean seeing, let alone understanding. Pictures of wanton stitching and the use of a variety of technical performance practice, makes the lens show visual objects which are handled and processed artifacts, not natural objects. With the human visual experience and misunderstanding, magic image confuses eyes. Visual centrism begins to be questioned.

The symbol of its true meaning is in the third period of symbolic development. In this period symbol and nature directly separate. If a mirror is the performance of the symbols of nature rendered directly and camera performance is a symbol of natural indirect presentation, “symbol” in this period is not naturally representation, directly or indirectly, but an entirely separate from the raw state of nature, and shows as a presentation of the spirit and thinking. The symbols function like computer. Computer as a technology tool, during this period, is the symbol representatives. The abstract of all the symbolic representation is “0” and “1”, only two figures. Data programming techniques,

398 EITT 2013, Williamsburg, VA, USA, November, 2013 The Development of Visual Philosophy under the Impact of Philosophy of Technology a simple complex combination of the two figures can refer almost all generations of thinking and command and has greatly enhanced the speed of people’s understanding of transformation of nature. Today, in the image world, “images not only affect the process of thinking, but they are the thinking itself”. From a phenomenological point of view, something behind the image represented by computer technology tools is completely shelved. Technological image completely changes the original mechanism of visual communication, and these images are entirely under the control of political rights and media. It has become a consensus that visual literacy training is necessary and urgent during this period. What we need to do is to peel off the external power and politics, facing reality and the nature. These will be important content of studies on visual philosophy in this period.

4.2. Examining the Impact of Philosophy of Technology to the Development of the Visual Philosophy from the Perspective of Technology Humanistic Theory The understanding of technology as tools is an important factor, which causes the historic absence of philosophy of technology. Although the technology serves as tools to help people understand and transform the world, the understanding of technology has not reached the height of philosophy. Until 1877, the German philosopher Ernst • Carp formally proposed the concept of philosophy of technology in his book named “Philosophy of Technology Platform”. In the mid-18th century, the British Watt’s improving the steam engine is seemed as the starting point of the first industrial revolution. A series of technological revolution brought about the shift from manual labor to the production by powered machines. This technology wave was then transmitted to the entire European continent from the UK, and spread to North America in the 19th century. Technology, which has brought revolutionary change to human society, makes people a major shift in attitude toward the technology: from disregard to face up to the reflection of technology humanistic theory. Technology humanistic theory believes the philosophical thinking about the relationship of human and technology, or the value of technology brought to people. As technology advances, in the early stage technology is created and took advantage of by human, playing a great deal of positive value. However, when today technology led to the ecological and natural crisis, people began to reflect on the negative value of the technology.

In the development process of visual philosophy, technology is experiencing from indifference to be faced up squarely, and then to reflect on the process. In the infancy, technology had once dubbed “witchcraft” title. This slightly derogatory description reflected people’s indifferent attitude towards the technology. In this case, the vision was a noble symbol of the thinking. The value of technology to human beings was only one side to reflect reality nature, just like “mirror”. It did not predict that technologies would influence the status of vision. Entering the industrial age, people began to face up to the great strength of technology. Especially technology as a tool to subverted the form and means of visual representation. The technological image makes a mirror-like vision seem superficial. And the image technology makes vision begin to think. Technology has led to challenges to the visual experience. The visual think is often influenced by technology. People cannot discriminate the boundaries of the essence and phenomenon. At this time of the great power of technology, it aims to improve the living conditions of the people, and it also changes the “horizon”. Today, IT has brought an even greater crisis to the human’s visual experience. The robot can replace human to complete the specific tasks that human beings can not complete. Are robots people? Who dare to say that the robots are “Persons” or “Non-

EITT 2013, Williamsburg, VA, USA, November, 2013 399 Proceedings of International Conference of Educational Innovation through Technology persons”. Human beings as the master of the world, have alternatives. It seems that the whole world can be digitized.

Technology was originally created by people as tools to understand and transform the nature. Today technology sometimes can not be in accordance with the established and artificial route which set to transform nature by people, and there has been phenomenon of a breach of human consciousness, the damage to human survival environment and technology alienation. However, the reasons of technology alienation are rooted in the improper values and behavior of human beings who creates and utilizes technology. Based on the understanding, the aim of visual literacy education is to enhance literacy training on the aspects of the creation and production of technology. However the visual representation of the image produced by any technical means, its creators must be human. Human’s rationality has created technical rationality. The correct understanding of the visual audience also depends on the correct understanding of generation mechanism and characterization. Perspective of the technical humanistic theory, examining the relationship among the people - visual - technology relationship and exploring the visual technology is the important enlightenment on visual philosophy.

4.3. Values of Philosophy of Technology to the Development of Visual Philosophy The study of philosophy of technology not only focuses on the technology itself, but also on the reasonable judgment of the value of technology to human. The reflection of visual philosophy is not limited to vision. Technological inventions often seem to make eyes betray the mind. Visual philosophy needs to solve the problems of human beings, technology and technical rationality. The meaning and value of contemporary study of visual philosophy is embodied at this point. The content of visual philosophy, in addition to the exploration of the relationship of the eyes, brain and thinking, also needs to reflect the relationship of human, vision and technology, so as to develop visual literacy education deeply and effectively for the audience and the inventor of visual representations.

Contemporary theoretical value of visual philosophy is to reconstruct a theory building of visual philosophy through historic and comparison methods, and to make up for the deficiency of the overall architecture of the visual philosophy studies. Firstly, sort out the history of visual philosophy studies, from vertical perspective, and clarify the characteristics, the main viewpoints and their practice process of each period of development of the visual philosophy. Though the system of visual philosophy has not yet been established, throughout the history of vision research, many research has dubbed the “visual philosophy” name, thus opens up a precedent for the study of visual philosophy, such as Germany Nietzsche’s perspective “writing instruments which contribute to the formation of ideas” , Cassirer theory symbol Philosophy, Rudolf Arnheim “visual thinking”, Walter • Benjamin concentrates on technology image and its rich achievements of the revolution triggered in the visual field, and so on. We can stand on the shoulders of these sages so as to see farther and higher. Then comparison methods can help us understand the relationship of visual philosophy and its related fields or subjects. In the foundation of rich research results of humanism and phenomenology construct theoretical system of visual philosophy.

The practical value of studies on visual philosophy is to solve the real problem of how to interpret the image of the world. Current theoretical assumptions and study of the vision focus

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on the understanding of the visual mechanism, the way of visual representation, and strategies of visual literacy training. These studies are seemed as the study of visual practice, but its goal is more realistic, in order to better cope with the visual research. However in the final analysis, this is an assumption from the theoretical level. Such proposed research is a “stopgap measure” which does not solve the rooted cause of the problems in the practical study of visual philosophy. Digitization and virtualization are two key words in today’s image era of visual representation. The practical research of visual philosophy should focus on the characteristic features of era and technical rational thinking to make full use of technology to create a better and more beautiful visual representation (such as visual educational resources), so as to carry out the actual social action and specific projects. Finally, people realize the concept and strategies of visual literacy education through their participation in the process of practice.

Since birth, the world’s first touch is the “light of life” through vision. Visual perception accompanies a person’s the whole life. It is important that we have been concerned about the “look” ability and visual experience. Therefore, the understanding of the vision, since ancient times, is an eternal topic. Research on establishment and development of visual philosophy implies in our day-to-day activities. It needs to sort out by the ways of history and comparison. Due to the impact of technology and philosophy of technology, the development of the visual philosophy is endowed with new meanings and value. In terms of “the Then Time”, “the Current Time” and “the Future Time”, the power of technology will continue to affect humans’ all practical activities of understanding and transforming the nature through vision.

References Aristotelian. (1959). Metaphysics. Beijing: Commercial Press. Chen, C. S. (2012). Discuss on philosophy of technology. Beijing: Science Press. Jonas, H. (1954). The nobility of sight. Philosophy and phenomenological research, 14(4), 519. Lacan, J. (2005).The Wonders of visual culture: Visual Culture General. Beijing: China Renmin University Press. Meng, J. (2005). Image era: the visual culture propagation theory interpretation. Shanghai: Fudan University Press. M • Leiceste, P. (2003). Visual communication image contains dynamic information. Beijing: Beijing Broadcasting Institute Press. Zhang, Z. W. (2012). Western philosophy fifteen stresses. Beijing: Peking University Press. Zhou, X. (2002). Interpret blueprints body ideology. Tianjin: Tianjin Academy of Social Sciences Press.

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Acknowledgments This work was funded by the Priority Academic Program Development of Jiangsu Higher Education Institution, and Humanities and Social Sciences Projects of Ministry of education of China under Grant No. 12YJA880161.

402 EITT 2013, Williamsburg, VA, USA, November, 2013 Li, J., & Xia, W. (2013). An analysis of teaching behavior in the open course. Proceedings of International Conference of Educational Innovation through Technology, 403-410.

An Analysis of Teaching Behavior in the Open Course

Jian-Sheng Li Nanjing Normal University, China Email: jianshengli333 @163.com

Wen-Jing Xia Zhejiang University, China Email: xiawenjing1991 @163.com

Abstract: Open class videos taken in prestigious schools are quite popular among the public and received attention by the researchers. The aim of this study was to analysis teachers’ teaching behavior. This study tries to reflect the process of teaching and teaching skills in the open class classroom from the aspect of teachers’ teaching behavior, the teaching process structure, as well as teaching skills and techniques. After analyzing the characteristics of teaching behaviors from the aspect of teacher-student interaction in the class, the use of teaching methods, teaching management, and how did teachers design issues, as well as improve teaching efficiency. This study will give some useful suggestions about the teaching of the open class.

Keywords: teaching behavior, open class, Flanders interaction analysis

1. Introduction Massachusetts Institute of Technology (MIT) was the first to start the Open Courseware project in April 2001. (Dong & Zhang, 2012). In 2011, the top Chinese universities’ Video classes can be available free of charge through the Internet and these online open courses have become a hit among young Chinese.

In this article, the teachers’ teaching behavior in open courses are focused .11 introductory courses of open class videos are chosen through Net ease and a variety of behaviors are recorded, analyzed, discussed and summarized . On the basis of the analysis results, some useful suggestions about the implementation of the open class are put forward.

2. Methodology 2.1. Hypothesis Tang.S.L summarized the validity of the act of teaching behaviors as three aspects in Summary of Effectiveness of Abroad Teaching Behavior. One is the professional performance of teaching behavior. The other is the effective teaching process and structure. The third one is about effective teaching skills and techniques. In this study, we propose the following hypothesis: H1：Teachers Language ratio is stable value in introductory open classes. H2：The proportion of students participating in interactive in the class is associated with the accumulation of knowledge. H3：Proportion of students’ Language will affect classroom atmosphere.

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2.2. Analyze Tools 2.2.1. Flanders interaction analysis. FIAS is a coding system used to record and analyze the teaching-learning situations. The specific steps: Observe and record the corresponding code based on Flanders interaction analysis coding system (See Table 1). These codes reflect a series of events in the classroom in chronological order.

Table 1. Flanders interaction analysis coding system.

2.2.2. Design observation form. According to the requirements of FIAS and the actual observed object, we plan to put data of each lecture into a single table (See Table 2). The form has a total of 20 cells vertically. Each cell represents a 3-second period. It also has 60 grids horizontal marked with the value 1-60.Each cell represents one minute.

Table 2. Observation form 1 2 3 4 … 58 59 60 1 2 … 20

2.2.3. Flanders interaction analysis matrix table. Flanders interactive analysis matrix tables are filled when we watching videos of open class.

2.3. Procedures and Data Analysis Taking classroom discipline into account, examinations, and other things that have nothing to do with subject knowledge in the first lesson, the second lesson of each introductory course is chosen as the observed object. In the actual observation, which having 530 minutes of video in all, 11 classroom records are collected, also, the matrix analysis and ratio analysis for each lesson are completed (See Table 3).

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Table 3. Flanders interaction analysis matrix 1 2 3 4 5 6 7 8 9 10 sum 1 2 2 2 1 1 2 3 0 4 2 2 1 4 9 5 1 6 963 3 5 1 979 6 1 1 7 1 1 8 5 1 6 9 1 1 3 4 9 10 1 1 sum 2 8 0 9 972 1 0 8 9 1 1010

2.3.1. Matrix analysis. The integration of positive cells and defective cell can be gotten in matrix table. Integrated grids in the matrix are the intersection region with row 1 to row 3 and line 1 to line 3.Defective grids in the matrix are the intersection region with row 7 to row 8 and line6 to line7. Based on the rules above, the actively integrated cells and defective cells of each lesson can be summarized (See in Table 4).

2.3.2. Ratio Analysis. 2.3.2.1. Classroom structure. Proportion of Teacher’s Language=Summary of row 1 to row 7 / the total number Proportion of students’ Language= Summary of row 8 to row 9/the total number Proportion of silence in the class=the number of row 10/ the total number Proportion of quiz from teacher= the number of row 4/ the total number

2.3.2.2. Teacher’s influence Proportion of Indirect influence and direct influence = Summary of row 1 to row 4 / Summary of row 5 to row 7. Proportion of positive impact and negative impact = Summary of row 1 to row3 / Summary of row 6 to row 7 Therefore, the effects of different classroom structures and teachers’ behavior can be gotten by the Ratio Analysis. (See Table 5).

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Table 4. Actively integrated cells and defective cells of each lesson Reciprocal second Second lesson lesson School Course Actively Actively Defective Defective integrated integrated cells cells cells cells Yale Introduction to 0 0 0 0 University Psychology Yale Introduction to 0 0 26 0 University Literary Theory Yale Introduction to 0 0 16 0 University Political Philosophy Yale Introduction to the 0 0 6 0 University Old Testament Introduction to MIT 0 0 9 0 Algorithms Introduction to MIT 0 0 0 0 Biology Computer Science MIT and Programming 2 0 0 0 Introduction Introduction to Solid MIT 0 0 0 0 State Chemistry

Huazhong University Introduction to of Science & 0 0 0 0 Philosophy Technology (China) Northwest A & Introduction to Insect 0 0 0 0 F University Taxonomy (China) Shanxi Introduction to 0 0 1 0 University regional social (China) history.

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Table 5.Teacher’s influence

2.3.3 Curve analysis. By using relevant software, recorded data can form a certain graph. Analyzing five lessons which have Non-zero Proportion of students’ Language, we can get graphs as follows (See Graph 1 on the next page).

3. Results 3.1. Classroom atmosphere We found that except MIT’s course: Introduction to Computer science and programming has its actively integrated cell not equal to zero, other cells no matter actively integrated cells or defective cells are all equal to zero. Then, we may draw a conclusion that lessons been watched in this study didn’t have harmonious classroom atmosphere.

3.2. Classroom structure In the progress of watching open class videos, teachers’ behavior has been recorded. In addition to professional issues, some of these teachers initiative to ask students whether have questions to ask during the teaching progress. Again, we compare the proportion of students’ language and the proportion of quiz from teacher. It is not hard to find that in most lessons the proportion of quiz from teacher is bigger than the proportion of students’ language.

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Graph 1.Curve of language behavior

3.3. Teacher’s influence After the stage of analysis, it is not hard to find that in each class, proportion of indirect influence and direct influence is much less than one (See Table 6). In the penultimate section, there are nine teachers observed in the classroom did not appear criticizing behavior, teachers used more encouraging language.

3.4. Students’ behavior While doing Curve analyzing, we list five curves to reflect those lessons with proportion of students’ language not equal to zero in second lessons. From these graphs we can see that the biggest proportion of students’ language in these five lessons is fifteen percent. This shows that no meter ask or answer questions students chose to express their idea in a brief way.

In 11 open class videos that teach Introductory courses, most of the proportion of the teachers’ language decreased, while the proportion of students’ language increased in classroom (Graph 2).

408 EITT 2013, Williamsburg, VA, USA, November, 2013 An Analysis of Teaching Behavior in the Open Course

Graph 2. Change of the proportion of teachers’ and students’ language in the classroom

4. Conclusion and discussion 4.1. Conclusion 4.1.1. Proportion of various types of teaching behaviors is stability. It is observed that lecturing is still the main teaching method. The ratio of teachers Language generally maintained a stable value. It change trend basically consistent with the assumptions made in research hypothesis stage. Teachers’ Language ratio has been a relatively large value.

4.1.2. Variety of teaching methods been used in the classroom to regulate atmosphere. Nine of eleven open class teachers were observed ask questions on the class. However, during the observation process, the frequency of discussion method used by teachers is very low.

In the progress of observing, 72.7% of teachers were recorded use demonstration method in the class. In the process of observing open class video, it is found that students’ questioning behavior is benefit to enhance classroom interaction and can also make the class atmosphere more active.

4.2. Discussion Flanders interaction analysis method was found to reflect classroom activities in a more intuitive way. Researchers can summary and reflect classroom behavior by referencing recorded data. This data is also very valuable for the teachers being observed. They can use these data to reflect the actual situation of the lectures and try to find the gap between the actual situation of the lecture and expected situation. In this way, teaching strategies can be adjusted by teachers on time to improve teaching efficiency effectively.

However, Flanders interaction analysis method has also exposed some deficiencies. Firstly, in the perspective of analyzing teaching behavior, it can hardly accurately reflect the variety of classroom situations because the classroom teacher-student interaction behaviors are simply divided into 10 categories.

Meanwhile, it is found that teachers still play an important role in the excellent open class teaching introductory courses. The teaching arrangements of these lessons are worth learning. However, considering the following factors, teaching arrangements cannot be copied directly.

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Courses types. Each course type has its own characteristics, which means teachers cannot only copy outstanding teaching methods in their teaching progress. Courses nature. For example, in introductory course, the new knowledge is introduced and students attended to these classes without accumulating basic knowledge. However, it is still can’t be directly determined that classroom atmosphere is serious and oppressive.

All in all, lecturing is still the main teaching method in these open classes. Proportion of Teacher’s Language of these eleven classes maintain a stable value overall and teachers have used appropriate teaching methods, appropriate examples and appropriate quoted articles.

References Abelson, H. (2007) .The creation of open courseware at MIT. Journal of Science Education and Technology, 17(2), 164–174. Cormier ,D.& Siemens ,G. (2010) .Through the open door: open courses as research, learning, and engagement. EDUCAUSE Review, 45 (4), 30-39. Dong, R. Xu, W. & Zhang, J. P. (2012). Construction and thoughts about open class video in universities. Modern educational technology, 22(2), 54-59. Li, S. L. (2005) Introduction of analyzing classroom teaching behavior. Educational theory and practice, (7). Baldi, S., Heier, H.& Mehler-Bicher ,A. (2003). Open courseware and open source software, COMMUNICATIONS OF THE ACM, 46(9). Carson ,S.(2009) The unwalled garden: growth of the open courseware consortium, Open learning, 24(1), ,23–29

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