The Role of Knowledge Channel Television Shows on Students’ Learning

Photo Credit: http://kchonline.ph Lasallian Institute for Development and Educational Research (LIDER) Br. Andrew Gonzalez FSC College of Education (BAGCED) De La Salle University (DLSU) 2401 Taft Avenue, Manila, Philippines Tel. +632-524-4611 local 435 The Role of Knowledge Channel Television Shows on Students’ Learning 1

The Role of Knowledge Channel Shows on Students’ Learning

Final Report

De La Salle University Br. Andrew Gonzalez FSC College of Education Lasallian Institute for Development and Educational Research Room A1608 Br. Andrew Gonzalez Hall, DLSU Manila 2401 Taft Avenue, Manila, Philippines Telefax No. +632 536 0232 Telephone: +632 524 4611 local 435 Website: http://www.dlsu.edu.ph

The Research Team

Project Leader Maricar S. Prudente, PhD

Research Associates 3

Studies 1, 2 and 4 Study 3 Leah Gustilo, PhD Thelma Mingoa, PhD Minie Rose Lapinid, PhD Maria Cequena, PhD Jessie Barrot, PhD Dena Culaba Mari Karen Gabinete Jasper Vincent Alontaga

Research Associate 1 Jovito C. Anito, Jr.

Data Quality Assurance Specialist Abdul Jhariel Osman

This study was funded by the Knowledge Channel Foundation, Inc.

The Role of Knowledge Channel Television Shows on Students’ Learning 2

Contents

Contents ...... 2

List of Figures ...... 3

List of Tables ...... 4

Executive Summary ...... 8

Introduction ...... 15

Study 1 Methods ...... 31

Study 1 Results ...... 34

Study 1 Conclusion ...... 79

Study 2 Methods ...... 80

Study 2 Results ...... 82

Study 2 Conclusion ...... 88

Study 3 Methods ...... 90

Study 3 Results ...... 98

Study 3 Conclusion ...... 103

Study 4 Methods ...... 105

Study 4 Results ...... 109

Study 4 Conclusion ...... 118

References ...... 119

The Role of Knowledge Channel Television Shows on Students’ Learning 3

List of Figures

Figure 1. Percentage of students’ perceptions on competencies in English developed in watching KC shows. 36

Figure 2. Percentage of students’ perceptions on competencies in Math developed in Watching Knowledge Channel Shows. 37

Figure 3. Percentage of students’ perceptions on competencies in Science developed in Watching Knowledge Channel Shows. 38

Figure 4. Percentage of students’ perceptions on competencies in Araling Panlipunan developed in Watching KC Shows...... 38

Figure 5. Students mean scores in the achievement tests for the 5 subject areas for the 2009, 2010 and 2011 sample groups...... 39

Figure 6. Gender differences in the students’ mean scores in 2009 , 2010 and 2011 sample groups in the five subject areas and in the overall score...... 43

Figure 7. Students’ Overall Mean Scores between Recipient and Comparison Schools across regions in 2009...... 44

Figure 8. Line graph illustrating the interaction between the type of respondents and Region in English test using the 2009 sample group...... 48

Figure 9. Line graph illustrating the interaction between the type of respondents and Region in English (E), Science (S), Math (M), Filipino (F), and Araling Panlipunan (AP) tests in the 2009 sample group...... 49

Figure 10. Students’ Overall Mean Scores between Recipient and Comparison Schools across regions in the 2010 sample group...... 51

Figure 11 Line graph illustrating the interaction between the type of respondents and region in Overall Mean scores in 2010...... 54

Figure 12 Students’ Overall Mean Score between Recipient and Comparison Schools across regions in the 2011 sample group...... 57

Figure 13. Line graph illustrating the interaction between the type of respondents and Region in English test in the 2011 sample group...... 60

Figure 14 Profile of the student participants in study 2 in terms of gender, location, and grade level...... 83

Figure 15. Estimated marginal means of post-test scores by learning group and location...... 86

Figure 16. Hypothesized path diagram of the effect of students’ attitude towards Knowledge Channel shows on their academic achievement...... 98

The Role of Knowledge Channel Television Shows on Students’ Learning 4

Figure 17. Students’ achievement scores in the 5 subject areas...... 101

Figure 18. Path diagram when Teacher’s performance is introduced as a mediating variable on the relationship between students’ attitude towards KC shows and students’ achievement. .... 103

Figure 19. Profile of teacher participants included in Study 4 (N=30)...... 106

Figure 20. Screenshot of the MaxQDA10 project illustrating the document, browser and code system...... 109

Figure 21. Screenshot of the MaxQDA10 document browser showing the coded segments in the active transcript...... 110

List of Tables

Table 1 Summary of the number of schools involved in Study 1 ...... 31

Table 2 Summary of the number of student respondents included in Study 1 ...... 32

Table 3 Reliability of Test Instruments used in study 1 ...... 33

Table 4 Mean ratings on how frequent students watch KC shows in three different platforms...... 35

Table 5 Students’ mean responses on the benefits of Knowledge Channel Shows ...... 36

Table 6 Mean percent scores of respondents from recipient schools (RS) and comparison schools (CS) across the 2009, 2010 and 2011 sample groups...... 40

Table 7 Mean percent scores between male and female students across the 2009, 2010 and 2011 sample groups ...... 42

Table 8 Overall Mean Achievement Score per region between RS and CS in the 2009 sample group. .. 44

Table 9 Summary of Regions where RS performed better, and have more convergent scores than CS in the 2009 sample based on their descriptive statistics...... 45

The Role of Knowledge Channel Television Shows on Students’ Learning 5

Table 10 Two-way ANOVA test of between Subjects Effects using the 2009 sample group...... 46

Table 11 Summary of regions where recipient schools performed significantly better than the students in the comparison schools in the 2009 sample group...... 50

Table 12 Overall Mean Achievement Score per region between recipient and comparison schools in the 2010 sample group...... 51

Table 13 Summary of Regions where RS performed better, and have more convergent scores than CS in the 2010 sample group based on their descriptive statistics...... 52

Table 14 Two-way ANOVA Test of between Subjects Effects using the 2010 sample group...... 53

Table 15 Summary of Regions where students in recipient schools performed significantly better than those in the comparison schools in the 2010 sample group...... 55

Table 16 Overall Mean Achievement Score per region between recipient and comparison schools in the 2011 sample group...... 56

Table 17 Summary of Regions where RS performed better, and have more convergent scores than CS based solely on their descriptive statistics in the 2011 sample group...... 57

Table 18 Two-way ANOVA Test of between Subjects Effects in the 2011 sample group...... 58

Table 19 Summary of Regions where students in recipient schools performed significantly better than those in the comparison schools in the 2011 sample group...... 61

Table 20 Urban-Rural Classification of Provinces and Cities in the 2009 sample group...... 62

Table 21 Differences in mean percent scores between urban and rural respondents in the 2009 sample group...... 63

Table 22 Urban-Rural Classification of Provinces and Cities in the 2010 sample group...... 64

The Role of Knowledge Channel Television Shows on Students’ Learning 6

Table 23 Differences in percent mean scores between urban and rural respondents in the 2010 sample group...... 65

Table 24 Urban-Rural Classification of Provinces and Cities in the 2011 sample group...... 66

Table 25 Differences in percent mean scores between urban and rural respondents in the 2011 sample group...... 67

Table 26 Distribution of participants per type and per grade level in the 2009 sample group...... 68

Table 27 Mean achievement percent score per grade level between RS and CS in the 2009 sample group...... 69

Table 28 Two-way ANOVA test of between subjects effects in the 2009 sample group...... 70

Table 29 Summary of the test performance of student participants in the Recipient Schools in the different Grade levels for the 2009 sample group...... 71

Table 30 Distribution of Participants per Type and per Grade Level in 2010 sample group...... 72

Table 31 Overall mean achievement percent score in the 2010 sample group...... 72

Table 32 Two-way ANOVA Test of between Subjects Effects in the 2009 sample group...... 73

Table 33 Summary of performance in achievement tests across grade levels for recipient schools in the 2010 sample group...... 75

Table 34 Distribution of Participants per type and per grade Level in the 2011 sample group...... 76

Table 35 Overall Mean Achievement Score per grade level between RS and CS in the 2011 sample group...... 76

Table 36 Two-way ANOVA Test of between Subjects Effects for the 2011 sample group...... 77

The Role of Knowledge Channel Television Shows on Students’ Learning 7

Table 37 Summary of performance in the achievements tests across 6 grade levels...... 78

Table 38 Mean scores across learning groups and locations in study 2...... 84

Table 39 The 3 x 2 contingency table of mean gain scores in study 2...... 85

Table 40 ANOVA test of Between-Subjects Effects for Learning Group and Location...... 87

Table 41 Learning Group Pairwise Comparison...... 87

Table 42 ...... Number of teacher participants by school. 90

Table 43 Profile of teacher participants by grade level and subject taught...... 91

Table 44 Mean scores of the teachers’ ability to Integrate KC Shows...... 91

Table 45 Student respondents’ profile by school, grade level, and age...... 92

Table 46 Reliability of achievement test instruments used...... 93

Table 47 Indicator loadings, average variance extracted, and reliability coefficients of the variables in the study...... 95

Table 48 Average Variance Extracted and correlation coefficients among constructs...... 96

Table 49 Teachers' Mean Ratings in ability to integrate KC shows...... 99

Table 50 Mean ratings of students’ attitude towards KC shows...... 100

Table 51 Estimates for the relationship between Students’ Attitude towards KC shows and Students’ Achievement when Teacher Performance is introduced as mediating variable...... 102

Table 52 Summary of codes and the coder’s memos...... 111

The Role of Knowledge Channel Television Shows on Students’ Learning 8

Executive Summary

Study 1. Effect of Knowledge Channel Shows on Students’ Achievement

Study 1 utilized an exploratory descriptive survey research design to explain whether the exposure of students on Knowledge Channel shows can make a difference in their academic achievement compared to the achievement of students who have no exposure to Knowledge Channel shows.

Student respondents from 267 public schools, which received the Knowledge

Channel package under the 2009, 2010, and 2011 grants, referred to as recipient schools

(RS); and student respondents from 248 public schools, which did not receive the

Knowledge Channels package, referred to as comparison schools (CS) were the participants for Study 1. This translates to a total of 41,550 student respondents, from both RS and CS, who were surveyed Exploratory data analysis, however, necessitated that only those RS respondents who reported that they watch KC shows shall be included in the analysis. Thus, further data analysis included 32,768 students, of whom

13,095 students were from RS and 19,673 students were from CS.

An assessment package was developed covering the subject areas of Science,

Mathematics, English, Filipino, and Araling Panlipunan. The test items were content validated by subject area experts from De La Salle University - Br. Andrew Gonzalez

FSC College of Education (DLSU-BAGCED) and revised based on the experts’ evaluation. The reliability analysis of these tests were conducted and were found to be reliable.

The Role of Knowledge Channel Television Shows on Students’ Learning 9

A team of field researchers trained by Lasallian Institute for Development and

Educational Research (LIDER) administered the tests in their respective regions in coordination with the Schools Division Superintendents (SDS) of the DepEd Divisions where the target schools belong. On the day of test administration, a total of 20 respondents per grade level in every school were randomly selected to participate in the study.

Significant Findings in Study 1:

1. Students from RS have significantly higher scores than those from CS. Further investigation on the effect of exposure to KC shows suggests that the mean scores of

RS students were 33% better than the students in the CS for the 2009 sample group,

31% better for the 2010 sample group and 45% better fo the 2011 sample group. These results corroborated the findings of the 2007 impact evaluation of Knowledge Channel shows on students’ achievement scores (Mapa, 2007). Interestingly, highest effects were noted in English (in 2009 and in 2010) and in Math (in 2011).

2. Across the different regions in the country, students from the RS generally performed better than the students from the CS.

3. Female students in both 2009 and 2010 sample groups generally outperformed the male students. This finding confirms previous findings that females score significantly higher than males (Quimbo, 2003; Wentzel, 1988; Amelink, 2009). In the 2011 sample group, no significant gender difference in the students’ performance was observed.

The Role of Knowledge Channel Television Shows on Students’ Learning 10

4. Overall, students from RS performed better across all subjects in all grade levels compared with students from CS. Interestingly, grade 6 students were found to perform significantly higher than students from other grade levels.

Study 2. Effect of Knowledge Channel Shows on the Achievement Scores of

Students from Various Learning Groups

Study 2 utilized an experimental research design to investigate whether students from various learning groups (i.e. Passive, Active, Lecture) will have significantly different gains in terms of achievement scores. Students in the passive learning group were simply made to watch Knowledge Channel (KC) videos. Students in the active learning group watched KC videos with the teacher facilitating the processing of the contents of the video. Students in the lecture group were taught using the lecture type of instruction.

The experiment was conducted in four recepient schools located in Luzon and

Mindanao. Each location involved an elementary school and a high school. For each school, five subjects areas (English, Math, Science, Filipino and Araling Panlipunan) were included. A total of 926 students partipated in this study and these students were randomly assigned to each of the three learning groups. A 15-item test for each subject area was developed. For each subject area, the researchers selected three topics with corresponding Knowledge Channel Shows video. A lesson plan was developed for the teachers who were assigned to the Active Group. The contents in the videos were incorporated into the lesson plan. Specific instructions were provided for teachers regarding the processing activities that they should do before, during, and after viewing

The Role of Knowledge Channel Television Shows on Students’ Learning 11 the shows. A similar lesson plan was given to the teachers who were assigned to the

Lecture Group.

To compare the mean scores of students across the three learning groups, independent samples t-test and factorial ANOVA were employed.

Significant Findings in Study 2:

1. The mean gain scores for each of the learning groups yielded significantly

positive results, with posttest scores > pretest scores. Students in the Active

group had the highest gain score, with the use of KC shows with teachers’

processing accounting for the 74.15% increase in the students’ posttest scores.

2. Post-Hoc Analysis of pairwise comparisons show that there is significant

difference between the gain scores of the students in the Active group and the

gain scores of the students in either the Passive or the Lecture group. Results

further revealed that the gain scores of the students in the Passive group is

comparable with the gain scores of the students in the Lecture group.

3. There is enough evidence to support that learning group accounts for the

differences in students’ achievement.

Study 3. Teachers’ Ability to Integrate KC shows, Students Attitude and

Achievement

Study 3 aimed to describe the relationship between teachers’ ability to integrate KC shows and students’ achivement. It also explored whether the students’ attitude towards

KC shows can explain such relationship.

The Role of Knowledge Channel Television Shows on Students’ Learning 12

The participants in study 3 were 143 high school teachers and 950 high school students from 8 public high schools in a province in Luzon. The province was chosen as it had the most number of public high schools that are recipients of Knowledge Channel package.

To gather pertinent data for study 3, an assessment package covering five subject areas such as Science, Math, English, Filipino, and Araling Panlipunan were administered to student respondents along with the checklist on Attitude Towards

Knowledge Channel Shows (ATKCS). Moreover, 8 supervisors from the Department of

Education conducted classroom observations on the 143 teachers. An observation checklist describing the teachers’ proficiency skills was utilized. Path analysis was used to estimate the parameters of the mediation model.

Significant Findings in Study 3:

Analysis of quantitative data using path analysis, specifically the maximum likelihood (ML) estimation method in AMOS, enabled us to depict the hypothesized causal paths of variables in this study and to state the following conclusions:

1) The relatively high mean ratings of students’ attitude scores towards Knowledge

Channel shows indicate a positive attitude.

2) Students’ attitude towards KC shows has a significant direct positive effect on

students’ achievement.

3) Teachers’ ability to integrate KC shows has a direct positive effect on students’

achievement.

4) The mediation model reveals that teachers’ ability to integrate KC shows in

instruction partially mediate students’ attitude on achievement, since attitude

The Role of Knowledge Channel Television Shows on Students’ Learning 13

remained to have a positive significant effect on students’ achievement even

after introducing the mediation variable.

Study 4 Teachers’ Lived Experiences in Integrating Knowledge Channel Videos

in Instruction

Study 4 described the lived experiences of teachers in integrating Knowledge

Channel videos in instruction. Representative schools from Luzon, Visayas and

Mindanao participated in this study. Written questionnaire was used to determine how frequent KC videos are viewed, how the videos are used in the lesson, and how the videos enhance the teaching and learning experience. Focus group discussions (FGDs) were employed to determine the different teaching strategies and methods that the teachers employ when integrating KC videos into their lesson and how they use KC videos in enhancing learning among the students.

For qualitative content analysis of the data from the FGD, the framework method was used. This methodological approach examines the content of the FGD in order to derive meaning and particular implications for describing the lived experiences of the teachers. The approach involved identifying commonalities and differences in the qualitative data, before focusing on relationships between different parts of the data, thereby seeking to draw descriptive and explanatory conclusions clustered around themes. The 3E continuum (Enhance, Extend, Empower) of technology-enhanced learning was used as the framework for analysis. The analysis proceeded with these 3 stages set as primary categories in the coding process. The coding process was conducted utilizing MaxQDA10™.

The Role of Knowledge Channel Television Shows on Students’ Learning 14

Significant Findings in Study 4

Reflecting carefully on the teachers’ lived experiences, the following findings are deemed significant:

1. The use of the 3E framework of technology integration in interpreting and

analyzing the lived experiences of teachers was found to be appropriate.

2. The teachers’ techniques in integrating Knowledge Channel videos fall

primarily within the enhance level of the 3E continuum, suggestive that

teacher training is needed to further develop their pedagogy in integrating

technology in order to achieve the stage where students are self-motivated to

learn.

3. Following the social constructivist lens of the framework, it is maintained

that teachers must be cognizant of their primary role as facilitators of

learning. Through the lived experiences of the teacher participants, the social

constructivist roles of teachers at the enhance level is recognized.

4. There are some activities that the teachers employ in integrating KC videos

in teaching that are reflective of the extend level of technology integration.

5. The lived experiences of the teacher participants reveal that the empower

level manifests in the process of giving assignment questions which calls for

students to watch other KC shows and related learning materials.

The Role of Knowledge Channel Television Shows on Students’ Learning 15

Introduction

Since the 20th century, television (TV) has become the primary source of news and information. As such, it has the potentials to greatly influence the way people live and process information (Albertson & Lawrence, 2009). Debates persist on how, when, and to what extent should children be exposed to TV considering the proliferation of sex, violence, and adult language on advertisements and actual programs (Kunkel, 1998).

However, it cannot be denied that TV has a vast potential as an educational technology

(Greenhill, 1967; Hendrick, 1986; Huston & Wright, 1998; Kaymas, 1999; Moeller,

1996; Schramm, 1962; Seels, Fullerton, Berry, & Horn, 1996)—it educates children and expands knowledge of the world (Huston & Wright, 1998). As a matter of fact, both in

Japan and in Europe, TV was originally conceived as an educational tool (Fuenzalida,

2011).

Benefits of educational TV shows

Many reasons have been advanced as to why TV gained much attention as an educational tool. These include accessibility (Moeller, 1996; Nielson Reports, 1986), positive effects on enhancing the literacy development of both children and adult

(Soudack, 1990), and entertainment value (Bates, 1983). Moreover, watching TV was considered as the second most commonly used self-directed learning strategy among

European students and fourth among Chinese students (Gieve & Clark, 2005). On top of these, learners are more motivated to learn via visual media than printed media

(Chapple & Curtis, 2000).

One of the foremost goals of any literacy programs and the reason why stakeholders integrate educational television in learning is to see gains in viewers’

The Role of Knowledge Channel Television Shows on Students’ Learning 16 academic achievement. Seels et al. (2008) has documented positive and negative results of television utilization projects in the 1950s, 60s, and 70s in the United States. The

Hagerstown, Maryland project, and early demonstration of instructional television saw improvements in standardized test scores in the initial experiment. The most important gain was on students’ improvement in learning by television. A survey of different stakeholders revealed that students preferred television instruction. In the Samoan project conducted between 1964 and 1970 in which researchers administered pre and post tests, it was deduced that the greatest gain was found in the area of Mathematics and slight advantage in reading.

One of the most encouraging findings from recent studies on educational television is the gains found among young children. Baydar et al. (2008) examined the effects of an early childhood television program of 5-year old children in Turkey who belong to the low socioeconomic level and who had limited access to preschool education. The study found significant gains among children with high levels of exposure in arithmetic, syllabication, and vocabulary. Moreover, the study found that instructional television was more beneficial for children with lower school readiness skills prior to the implementation of the program than those who had higher school readiness skills.

Register (2004, as cited in Shoemaker, 2011) tested the reading skills of three groups of

Kindergarten in Florida: (1) music-only exposure, (2) video-only exposure, and (3) music and video combined exposure. Her findings indicated that the test scores of students in the music and video exposure were six times higher than that of the music only group when the former were tested after viewing a children’s television program,

Between the Lions. In a similar study, Linebarger, Kosanic, and Greenwood (2004) investigated the impact of Between the Lions on Kansas’ first grade and kindergarten

The Role of Knowledge Channel Television Shows on Students’ Learning 17 students’ literacy skills. Results of the study showed that the viewers had higher word recognition, reading test scores and phonemic awareness compared with non-viewers.

Great improvements on literacy skills (speech to print, word building, concepts of print) were noted among moderately at-risk to non at-risk kindergarten children who viewed the program than those at-great risk. Pelletier (2011) compared four groups who participated in a 12-week family literacy program: one group participated in the book- making project intervention, the other in television and book making, and the rest in the regular family literacy programming. The study found that children who participated in the television viewing intervention had greater gains in early reading, and children who participated both in the television viewing and alphabet-book making had the greatest gains.

Marshall (2002) presents other evidences that show that educational videos actually help learning: (1) Bryant, Mullikin, McCollym, Ralastin, Raney, Miron et al (1998) said watching Blues Clues has strong effect on the flexible thinking, problem solving, and prosocial behaviors of pre-schoolers; (2) Wilson, et al. (1999) said the Choices and

Consequences program reduced verbal aggression (including teasing, swearing, arguing) among middle school students; (3) Wright, Huston, and Kotler (2001) said viewing Sesame Street was positively associated with subsequent performance in reading, math vocabulary and in school readiness skills of pre-schoolers; and the recontact study by Wright, Linebarger, and Schmitt (2001) on15 to 20-year olds who frequently viewed Sesame Street at age 5 “had significantly better grades in English,

Science, and Math, read more books for pleasure, and had higher motivation to achieve.

From a social cognitive point of view, students learn from watching others. In

Albert Bandura Bobo doll experiment, children watched an adult act aggressively

The Role of Knowledge Channel Television Shows on Students’ Learning 18 towards a Bobo doll and they later imitated the aggressive behaviour during their free play (Bandura, 1965, as cited in Bergin & Bergin, 2012). This brings to point the power of television, in general, to influence behaviour of the viewers, and for educational television, in particular, to facilitate learning of concepts, skills and attitudes of their viewers. Learners construct knowledge from what they view on television in the context of their prior knowledge, their past experiences, their beliefs, biases, and expectations. Thus affects the students’ ability to learn from it (Center for Children and

Technology, 2004).

National policies on educational TV shows

Several countries have already created a law that requires TV networks to broadcast educational programs. One of those countries is the Philippines, which enacted the

Children’s Television Act of 1997. The law requires broadcast networks to allot 15 percent of daily airtime to child-friendly TV programs. Eventually, its implementing rules and regulations have been released to put more teeth into the law (Cruz, 2012).

One of the by-products of Children’s Television Act of 1997 is the Knowledge Channel

Television. It is the first and only educational channel in the Philippines which aims to provide a wide array of curriculum-based and curriculum-relevant yet dynamic and engaging programs for its more than 3 million viewers from both formal schools and alternative learning system. Through its philanthropic support, Knowledge Channel

Foundation, Inc. (KCFI) was able to provide services to almost 2,000 public schools in the Philippines with its educational programs in Science, Math, English, Filipino, and

Araling Panlipunan beamed nationwide daily.

The Role of Knowledge Channel Television Shows on Students’ Learning 19

Previous studies on Knowledge Channel shows

In an impact evaluation of the programs of Knowledge Channel on students’ NAT scores from 101 elementary schools in 10 provinces in the country which was commissioned by Knowledge Channel in 2006, Mapa (2007) claimed that there was a positive and significant relationship between the presence of Knowledge Channel and the improvement of NAT scores and its sub-components from 2004 to 2006 in schools which regularly utilized Knowledge Channel facilities. The increase of at least 2 percentage points per year (average) in the NAT scores and its sub-components

(Science, Mathematics and English), all things being the same, can be attributed to knowledge Channel shows. In addition, Mapa reported that the positive impact of

Knowledge Channel programs was felt most likely in the areas of Science and

Mathematics.

In another commissioned study of the programs of Knowledge Channel on students’ performance reported by Mapa (2009), a test-questionnaire patterned after the

National Achievement Test (NAT) consisting of 60 items divided into three components, namely: Mathematics (20 items), Science (20 items) and English (20 items) was constructed and administered to two groups of Grade 6 pupils. The first group consisted of schools that were visited in the same school year 2007-2008 wherein the same set of 458 pupils took the pre-test and post-test. The second group consisted of schools in which the pre-test was administered in 2008, while the post-test was conducted in 2009 to different sets of grade 6 pupils. Results indicated that the test scores of Grade 6 pupils in Group 1 increased significantly by about 6 percentage points, from 20.20 in the pre-test to 23.81 in the post test after four (4) months of intervention. In addition, the test scores of Grade 6 pupils in Group 2 increased

The Role of Knowledge Channel Television Shows on Students’ Learning 20 significantly after one year of intervention by 11 percentage points, from 20.29 during the pre-test to 26.96 in the post-test.

Given the findings of aforementioned studies as revealed in the literature, study 1 aimed at determining whether students from schools with Knowledge Channel shows

(recipient schools--RS) performed better in their academic achievement tests as compared to students from schools without Knowledge Channel shows (comparison schools--CS).

Mode of integrating educational TV shows in instruction

Moreover, the above review of research suggests that educational television is a great aid in students’ learning and academic achievement. Moeller (1996), however, claims that the use of television, in itself does not guarantee positive gains. Using television alone, without careful consideration of the viewing process and level of interactivity in the instructional environment, will not readily result in learning since educational television is a complex medium whose messages are not easy to decode.

Educational television exemplifies the components of the communication process which comprises of the following: the sender (teacher, script writer, producer, and director); target audience in a particular context, in the case of ETV, students, whose meaning- making process may be influenced by aptitudes, interests, needs, and desires; purpose or coded messages transmitted via satellite; channel or medium by which the coded messages are transmitted or broadcast; and feedback or students’ reactions on the TV programs that are shaped by environmental context (Aghi et al., 1981). With this complex process of meaning making on educational television, it is a combination of

The Role of Knowledge Channel Television Shows on Students’ Learning 21 technology use and teacher’s processing of content which allow students to integrate concepts meaningfully.

For instance, in an experimental study conducted at Sta. Ana Unified School

District (1971, cited in Seels, Fullerton, Berry, & Horn, 2008) that investigated the effectiveness of three methods of instruction: conventional classroom instruction, televised instruction only, and a combination of classroom and televised instruction for teaching science content and vocabulary were investigated. Results of the study show that the combination of televised and classroom instruction returned the greatest achievement. On the other hand, there was no significant difference that was noted in the achievement of the televised and conventional classroom instruction. Likewise,

Hardwood and McMahon (1997) found that video-enhanced curriculum for senior high school students had positive effect on students’ knowledge achievement and attitude toward science subject. Experimental groups that watched video series juxtaposed with teachers’ interactive processing of chemistry concepts shown in videos outperformed the control groups that only received classroom instruction without videos.

Even in e-learning environments, in which direct instruction or processing of concepts by teachers are not provided, the effect of level of interactivity applied in learning still holds true. In Zhang, Zhou, Briggs, and Nunamaker’s (2006) study, they examined the effect of interactive video on learning achievement and learner satisfaction in e-learning environments. They compared four groups of learners in four learning environments—with interactive video, with non-interactive video, without video, and traditional classroom. The 138 undergraduate students were randomly assigned in each group. The subjects were given pre-lecture and post-lecture tests. Zang et al.’s findings supported their hypothesis on the positive effects of interactive video.

The Role of Knowledge Channel Television Shows on Students’ Learning 22

Students in the e-learning setting with interactive video outperformed those in other settings and showed higher levels of learner satisfaction.

Clearly, the available research suggests that educational television has a great potential for enhancing learning. Its effect is contingent upon several variables such as interactivity and type of instructional settings students are exposed to. However, we know very little about instructional television’s effects on the academic performance of students in different learning environments across academic subjects in elementary and secondary education in the local setting.

Study 2 aims at occupying the aforementioned gap in research by investigating the difference in the post-test gains on achievement tests of students in three learning groups: (1) instruction using Knowledge Channel Shows (Passive group), instruction using Knowledge Channel Shows with interactive processing of content by the teacher

(Active group), and traditional instruction (Lecture group).

Given the findings from previous research that television improves learning, we hypothesized that Knowledge Channel shows in videos will improve learning outcomes.

Specifically, the following hypotheses inspired this study:

1. Students from the active learning group who watch Knowledge Shows with interactive processing of content will achieve better post-test scores than do students from passive learning group who view Knowledge Shows without interactive processing.

The Role of Knowledge Channel Television Shows on Students’ Learning 23

2. Students who watch Knowledge Shows with interactive processing of content from the active learning group will achieve better post-test scores than do students from lecture group, who merely utilized the traditional instruction.

In addition, based on the results of our study 1, which suggest that student achievement varies across regions, study 2 proposed the third hypothesis (study 2 was conducted after data of study 1 had been analyzed):

3. Student achievement in various learning groups is moderated by the area variable which would result in the differences of student achievement across experimental areas.

Educational TV shows vs. classroom teachers

Literature posits that educational TV shows make a difference with other methods of teaching (see Ayers, 1972; Jones, 1962). Furthermore, it also shows that instruction which covers the ability of the teacher to use television as a teaching tool makes a difference on how students learn and achieve inside the classroom (Savenye, Davidson,

& Smith, 1991). Hence, about 50 years ago, the notion that instructional television could replace the traditional classroom teacher was proven false (Hendry, 2001). Up until now, the teacher still remains to be the major in-school influence to student learning outcomes (Hattie, 2011) and educational television shows simply enhance the learning that the teacher provides.

Educational videos can engage student interest with dramatization, animation, and application portions, which is covered in detail during class discussions and class activities that would ensure comprehension (Hendry, 2001). Findings in this study show that educational television stimulates class discussion, reinforces lectures and reading, provides a common base of knowledge among students, and helps teachers

The Role of Knowledge Channel Television Shows on Students’ Learning 24

teach more effectively. As a result, the teachers revealed that their use of technology in

the classroom enhanced student comprehension and discussion of content, better

accommodation of students with diverse learning styles, and an increase in student

motivation to learn.

Chen and Hodder (1997) underscored the elements of effective classroom

television. The study examined a ten-year track of formative and summative research

conducted by the Foundation for Advancements in Science and Education (FASE), the

creator of Futures and The Eddie Files, and other ITV programs (FASE, 1997). The

study found that shorter programming was of higher value and had greater impact, and

that video was “most useful when used to support, rather than replace, the teacher”.

Educational television plays the supporting role, catching the interest of students,

helping them focus on particular subjects, and emphasizing key points (Hendry, 2001).

Teachers’ ability to integrate technology (videos) in their lessons

The literature has established that educational television plays a significant role to

enhance classroom instruction. However, the ability of the teachers to integrate

technology using educational TV shows in teaching to student learning must also be

studied. Teachers’ effectiveness in enhancing student achievement with the use of

educational videos or television shows lies in their ability to integrate technology in

their lessons. The national teacher training institute (n.d.) presents some guidelines on

how teachers can use educational television videos as an enhancing and enriching

resource that matches curriculum area. These guidelines cover the following areas (1)

prior to the video-based lesson (teacher and student preparation), (2) a focus on media

interaction while students view the video (like watching specific information or asking

The Role of Knowledge Channel Television Shows on Students’ Learning 25 the students to complete a task during or after a video segment is shown), (3) viewing activities, and (4) post-viewing activities (discussion, recognizing reactions, connecting the program to class work, introducing extension activities).

A survey of teachers’ use of television in the classroom (Center for Children and

Technology, 2004) show some best practices. These (1) Planning ahead (“spark interest or inspire, demonstrate something you can’t do any other way, enrich curricular content, practice a skill, reinforce or review a topic”), and (2) Promoting

Active Viewing (in three steps). The recommended steps in promoting active viewing include: a) Preparing – previewing the program for alignment to lesson goals; determining the setting and length of the video; setting clear expectations for students

(what you want them to gain and what activities will be done); and practicing the equipment; b) Participating – while keeping the lights on, the teacher will preface or introduce the video lesson with a few key questions or learning objectives; use the pause button once in while, to allow for some questions; or break students into small groups for discussion and share their thoughts to the bigger class; and (c) Connecting – where the teacher will choose follow up activities that connect to hands-on, real world experience, and the teacher will explain the connections made, specially for younger students.

Although educational television shows may be very interesting and excellent for explaining content and illustrating applications, they may not be truly interactive and may not address any misunderstandings of some students. This is where the classroom teacher, who presumably knows his/her students, would be irreplaceable (Skolnik and

Smith, 1993). And since the teacher is a major factor in the successful integration of

The Role of Knowledge Channel Television Shows on Students’ Learning 26 educational television shows to school curriculum, it is imperative to introduce these shows to schools with accompanying teacher training.

In another research, educational television series, the Peabody Award-winning series The Eddie Files, which was produced for elementary students, (Foundation for

Advancements in Science Education, 1997) found that educational television shows, when combined with other activities, can change the attitudes towards math and improve student performance. Each episode was focused on a topic from the elementary curriculum such as fractions, or statistics. Pre-test interviews showed that

90% of students found math “boring”. After watching episodes for two months with teacher guidance, post-test interviews showed that 75% of those students did not find math boring anymore. The same study showed that the number of students who wanted a career in math increased by 14%. A later poll showed increased ability of students to define concepts covered in the television series, to answer questions correctly, and to list applications of the curriculum topics that were addressed.

Nowadays, visual media, in the form of television or video has become an essential part of classroom instruction. This is likely to increase due to the presence of cable digital media and streaming video. A study by the center for children and technology

(2004), focused on key questions concerning the relationship of television to learning.

Television is said to promote children’s learning when children they use more senses for taking in information, which can be explained by the information processing theory. So instead of just seeing something, or hearing something, children remember more by seeing and hearing at the same time

Much research has shown the possitive effect of educational television or videos to enhance learning in students. Previous researches recommend how educational

The Role of Knowledge Channel Television Shows on Students’ Learning 27 television could be integrated in the classroom. For teachers to effectively use this media in the classroom, teacher training and exposure to the material is necessary.

A study by Eckenrod and Rockman (1988), (as cited in EDC Center for Children and Technology, 2004), show that teachers attended training session and were given a resource guide. Upon returning to their classes however, they tended to use the videos and activities demonstrated during the training, and tended not to use the videos and activities in the resource guide but were not demonstrated.

Another professional development training, Thirteen/WNET, New York’s National

Training Institute, in partnership with 15 other stations, trained teachers how to integrate internet, software applications and television and video programs into hands-on classroom learning activities (EDC Center for Children and Technology, 2004).

Evaluation showed that 81% of the teachers reported an increase in their students’ learning and 75% reported that their students retain more information. The ability of teachers to integrate technology with the lesson content, keeping in mind the learnig theories and teaching strategies (pedagogical knowledge) is the prime focus of teacher training in technology integration.

To understand better how teachers integrate technology in the classroom, understanding Technological Pedagogical Content Knowledge (TPACK), a theoretical framework for describing and understanding teacher knowledge required for effective technology integration (Mishra and Koehler, 2006, as cited in Mishra, Kochler and

Shin, 2009) is imperative.

In the 20th century, it has been known that teachers should be able to bring together content of the lesson with pedagogy, transforming how to teach a certain content depending on the learner’s context known as Pedagogical-content knowledge. In the 21st

The Role of Knowledge Channel Television Shows on Students’ Learning 28 century, technology has provided other forms of information, giving both teachers and students new ways to acquire knowledge. This added ICT to content and pedagogy, known as TPACK.

To be able to assess the quality of integration of technology in the classroom, a rubric was designed and validated, which included teacher attitudes, IT fluency (regular use), seamless integration (regular use, appropriate choice), use of technology by students, and classroom management (Schmidt, Thompson, Mishra, Kochler and Shin

(2009). This was used for self-assessment of 124 pre-service teachers. Data analysis included Cronbach’s alpha statistics on TPACK knowledge domain and factor analysis for each domain. Results showed that with the modification and deletion of 18 survey items, the survey instrument is reliable and valid in helping educators design longitudinal studies in assessing pre-service teachers’ development of TPACK.

Another study by Kaya, Kaya and Emre (2013) adapted this “Survey of Pre-service

Teachers Knowledge of Teaching and Technology” to assess pre-service primary teachers’ Technological Pedagogical content Knowledge (TPACK) to 407 Turkish pre- service primary teachers (227 female, 180 male). With the use of exploratory and confirmatory factor analyses, which includes Cronbach’s alpha and item-total correlation coefficients to check psychometric properties, it was concluded that the adapted scale should not be used in academic studies that focused on Turkish pre- service primary teachers’ TPACK.

Harris, Grandgenett, and Hofer (2011) tested a TPACK-Based Technology

Integration Assessment Rubric. They said there are only few measures that are available to measure quality of teacher integration, most of which favour the constructivist approaches to teaching, not accurately assessing the quality of technology integration

The Role of Knowledge Channel Television Shows on Students’ Learning 29 across various teaching approaches. They developed a more “pedagogically inclusive instrument reflecting TPACK concepts and has proven to be reliable and valid in two successive rounds of testing.

The current study used a TPACK – Based technology Integration Assessment

Rubric with more detailed adaptations that took into consideration levels in Bloom’s

Taxonomy in the portion of pedagogy.

Attitude of students towards technology integration

Several studies on attitude of students towards technology integration were about using various forms of media. Aliasgari, Riahinia, and Mojdehavar (2010) made a study on the effects of computer-assisted instruction (CAI) on the attitude of math students towards learning math. It studied second year girls of math or science in two high schools of Hashtgerd, Iran, for control and experimental groups. Results show that

CAI increases the learning level of students and improve their attitudes toward mathematics, although the study suggests this should be done in a larger sample and in another setting.

Another study that analysed student attitudes and beliefs towards e-learning was done in two universities in Libya, with engineering students (Rhema & Miliszewska,

2014). This also studied their satisfaction with technology and past e-learning experiences, finding out the perspective of the user. This analysed the relationship between student attitudes towards e-learning and their demographic characteristics, their access to technology, their use of technology for learning, their skill in technology and their satisfaction with technology.

Another study on student attitude toward the use of technology in learning is a case study investigating student attitude towards computer-assisted language learning

The Role of Knowledge Channel Television Shows on Students’ Learning 30

(CALL), by taking note of student attitude towards computer-assested learning (CAL) and foreign language learning (FLL), (Bezen, 2010). Factors affecting student attitude, relationship of CAL, CALL and FLL was also explored. Findings show that most students have positive attitude towards CAL, CALL and FLL. Factors that affect student attitudes were age, grade, gender, years of studying English, and prior experienced in CALL. It was also found that CAL, CALL and FLL are interrelated.

Study 3 explored students’ attitude towards educational television shows of

Knowledge Channel, instead of CAI, and its relationship to student achievement and teachers’ ability to integrate educational shows into their lessons. The study sought to establish the mediating effect of teacher’s ability to integrate KC shows in teaching on the effect of students’ attitude towards KC shows on their academic achievement.

Specifically, it sought to answer the following research questions:

1. Is there a significant effect of attitude towards KC Shows on student

achievement?

2. Is there a significant effect of teachers’ ability to integrate KC Shows on student

achievement?

3. Is the effect of the students’ attitude towards KC on student achievement

mediated by teacher’s ability to integrate KC shows in teaching?

The Role of Knowledge Channel Television Shows on Students’ Learning 31

Study 1 The Effect of Knowledge Channel Shows on the Students’

Academic Achievement

Study 1 Methods

Research Design

Study 1 utilized an exploratory descriptive survey research design to explain whether the exposure of students on Knowledge Channel shows can make a difference in their academic achievement compared to the achievement of students who have no exposure to Knowledge Channel shows.

Participants

Student respondents from 267 public schools, which received the Knowledge

Channel package for the 2009, 2010, and 2011 grants, referred to as recipient schools

(RS); and student respondents from 248 public schools, which did not receive the

Knowledge Channel package, referred to as comparison schools (CS) were the participants for Study 1 (Table 1). This translates to a total of 41,550 student respondents, from both RS and CS, who were surveyed.

Table 1 Summary of the number of schools involved in Study 1

Year Recipient Schools Comparison Schools 2009 111 100 2010 111 105 2011 45 43 Total 267 248

The Role of Knowledge Channel Television Shows on Students’ Learning 32

In order to satisfy the condition that RS respondents must have been truly exposed to

KC shows, only respondents who reported that they watch KC shows were included in the analysis. Table 2 presents the summary of the analyzed samples.

Table 2 Summary of the number of student respondents included in Study 1

Surveyed Samples Analyzed Samples RS CS Total RS CS Total 2009 8889 7516 16405 5318 7516 12834 2010 9305 8537 17842 4550 8460 13010 2011 3683 3620 7303 3227 3620 6847 Total 21877 19673 41550 13095 19673 32768

Instruments

An assessment package was developed for grades 3-6 and first year to second year high school covering the subject areas in Science, Mathematics, Filipino, English, and

Araling Panlipunan. The items were content validated by subject area experts from De

La Salle University - Br. Andrew Gonzalez FSC Collede of Education (DLSU-

BAGCED) and revised based on the experts’ evaluation. The reliability of the test instruments was determined using Cronbach’s alpha (Table 3). As can be seen in Table

3, reliability estimates ranged from .63 to .89 indicative that the test instruments used to measure students’ achievement were reliable.

The Role of Knowledge Channel Television Shows on Students’ Learning 33

Table 3 Reliability of Test Instruments used in study 1

No. Cronbach's No. Cronbach's Level Subject Level Subject Items Alpha Items Alpha

English 20 0.833 English 25 0.776

Science 20 0.693 Science 25 0.634

Math 20 0.850 Math 25 0.870 Grade Grade 6 Grade Grade 3 Filipino 20 0.815 Filipino 25 0.835 Araling 20 0.774 Araling 10 0.743

English 20 0.859 English 30 0.724

SciencePanlipunan 20 0.686 SciPanlipunanence 25 0.774

Math 20 0.823 Math 27 0.714 Grade Grade 7 Grade Grade 4 Filipino 20 0.793 Filipino 30 0.734 Araling 20 0.731 A. 30 0.772

English 25 0.758 English 30 0.720

SciencePanlipunan 25 0.691 SciencePanlipunan 25 0.768

Math 25 0.856 Math 25 0.664 Grade Grade 8 Grade Grade 5 Filipino 25 0.750 Filipino 30 0.706 Araling 25 0.830 A. 30 0.623

Panlipunan Panlipunan

Procedure

A team of field researchers (FRs) were invited to attend an orientation conducted by the Lasallian Institute for Development and Educational Research (LIDER) in selected cluster areas in Regions 1, 2, 3, 4A, 4B, 5, 6, 10, 12, CAR, CARAGA, and

NCR (July 9-25, 2014). The purpose of the orientation was to train the FRs about the procedure and scope of work that they will render for the duration of Study 1. LIDER sent initial communications to the Schools Division Superintendents (SDS) of the

DepEd Divisions where the target schools belong. The letter indicated the list of recipient schools and requested that the assigned FRs be made to select the comparison schools based on proximity and teacher-student (TS) ratio criteria. In calculating the TS ratio, the masterlist of public school teachers and the public school enrolment data

The Role of Knowledge Channel Television Shows on Students’ Learning 34 obtained from the Department of Education division offices, were used. The school with the closest TS ratio as the recipient school was chosen as the comparison school. The field researchers were tasked to follow up the approval of the letter of request and to secure the Superintendent’s endorsement letter addressed to the respective principals.

Once endorsement was secured, the FRs coordinated with the Principals and set the schedule of test administration. The FRs followed the random sampling procedure using sample randomizer (www.randomizer.org) and a total of 20 student respondents per grade level per school were randomly selected to participate in this study.

Data Analysis

To compare the mean scores between recipient and comparison schools, independent samples t-test and factorial ANOVA were used. Cohen’s d was calculated to determine the effect size of the differences between the means of student repondents the recipient and comparison schools.

Results

Students from the recipient schools were asked to report how often they watch

KC shows in various platforms. Specifically, RS respondents were asked how often they watch KC shows from the KC website, Television, and Youtube. Results revealed that students watch KC shows more often using the Television platform. Table 4 shows the mean rating for each media in the three sample groups. It can be deduced that KC

Website has already emerged as a popular platform to watch KC shows as the television.

The Role of Knowledge Channel Television Shows on Students’ Learning 35

Table 4 Mean ratings on how frequent students watch KC shows in three different platforms.

Knowledge 2009 Sample Group 2010 Sample Group 2011 Sample Group Channel Platfrom Mean SD Mean SD Mean SD

Website 2.98 1.17 3.0 1.27 3.07 1.134

Television 3.24 1.20 3.16 1.32 3.20 1.21

Youtube 2.26 1.25 2.34 1.31 2.32 1.29

Scale: 0=Never, 1=Rarely, 2=Sometimes, 3=Often, 4=Always.

The RS students were queried on whether Knowledge Channel shows have helped them gain knowledge, skills, and attitudes in the four subject areas (English,

Mathematics, Science, and Araling Panlipunan). Using the scale of 1 to 4, wherein “4” represents strong agreement to the statement that KC shows helped the respondent gain knowledge, skills, and attributes and the scale “1” represents strong disagreement. Table

5 shows that for the 2009 sample groups, the mean responses ranged from 3.43 to 3.65, which implies relatively strong agreement among RS respondents that KC shows helped them gain knowledge, skills, and attitudes in all subject areas. The same pattern of strong agreement can be observed for the 2010 and 2011 sample groups.

The Role of Knowledge Channel Television Shows on Students’ Learning 36

Table 5 Students’ mean responses on the benefits of Knowledge Channel Shows

Grade 2009 2010 2011 Subject Level (Mean) (Mean) (Mean) English 3.49 3.43 3.49 Science 3.48 3.41 3.39 Grade 3 Math 3.57 3.53 3.31 Araling Panlipunan 3.47 3.42 3.45 Filipino 3.47 3.39 3.39 English 3.50 3.40 3.50 Science 3.53 3.38 3.36 Grade 4 Math 3.56 3.48 3.39 Araling Panlipunan 3.44 3.30 3.36 Filipino 3.52 3.34 3.22 English 3.57 3.46 3.61 Science 3.57 3.52 3.58 Grade 5 Math 3.65 3.55 3.56 Araling Panlipunan 3.53 3.46 3.55 Filipino 3.52 3.43 3.54 English 3.51 3.46 3.54 Science 3.50 3.46 3.48 Grade 6 Math 3.51 3.50 3.51 Araling Panlipunan 3.43 3.40 3.45 Filipino 3.47 3.43 3.43

The study also delved into the specific competencies that students perceived they have developed from watching Knowledge Channel Shows.

Figure 1. Percentage of students’ perceptions on competencies in English developed in watching KC shows.

The Role of Knowledge Channel Television Shows on Students’ Learning 37

It can be seen in Figure 1 that 90% of the students perceived that watching KC shows have helped improved their competencies in English language in terms of reading comprehension and in learning new words.

Figure 2. Percentage of students’ perceptions on competencies in Math developed in Watching Knowledge Channel Shows.

As for Mathematics, among the 2009, 2010 and 2011 sample groups, more than 90

% of the student perceived that KC shows help them improve in their problem solving, computational skills and understanding of mathematical terms. While more than 80% of the students expressed that they can see the relationship of math operations in their daily life through KC shows (Fig. 2).

Regarding competencies in Science, Fig. 3 indicates that majority of the students

(96%) perceived that they benefit from KC shows in terms of understanding concepts related to living things. More than 90% of the students found KC shows to be helpful in understanding force, motion, space, energy, earth and matter.

The Role of Knowledge Channel Television Shows on Students’ Learning 38

Figure 3. Percentage of students’ perceptions on competencies in Science developed in Watching Knowledge Channel Shows.

With regard to the competencies developed in watching KC shows related to

Araling Panlipunan, more than 90% of the RS students expressed that KC shows help them in understanding their own selves as Filipino citizens, roles in the family, and participation in the community. Across the 2009, 2010 and 2011 sample groups, similar patterns of students’ perceptions can be observed (Fig. 4).

Figure 4. Percentage of students’ perceptions on competencies in Araling Panlipunan developed in Watching KC Shows.

The Role of Knowledge Channel Television Shows on Students’ Learning 39

Comparative Analysis

Students’ mean scores in their achievement test in each subject area and overall test are shown in Fig. 5 to show comparison between RS and CS across three sample groups.

Figure 5. Students mean scores in the achievement tests for the 5 subject areas for the 2009, 2010 and 2011 sample groups.

The Role of Knowledge Channel Television Shows on Students’ Learning 40

As can be gleaned in Figure 5, students from RS performed better in the English

achievement test than students from CS. The same pattern can be seen in all the other

four subject areas and in their overall acheivement scores.

In order to determine whether there is a significant difference in the achievement in

the 5-subject tests between students from RS and CS, an independent samples t-test was

used. Results showed that the mean percent scores of students from RS were

significantly (p < 0.005) higher than the scores of students from CS across all the 5-

subject areas in 2009, 2010 and 2011 sample groups. Further, the reported scores in the

overall mean percent scores from the RS across the five subject areas were significantly

higher than the CS (Table 6).

Table 6 Mean percent scores of respondents from recipient schools (RS) and comparison schools (CS) across the 2009, 2010 and 2011 sample groups.

Variable N M p 2009 2010 2011 2009 2010 2011 2009 2010 2011 English 0.00* 0.00* 0.00* RS 5318 4550 3227 53.8 48.9 51.1 (0.35) (0.32) (0.38) CS 7182 8460 3619 47.1 43.0 43.8 Science 0.00* 0.00* 0.00* RS 5318 4550 3227 47.7 44.4 43.6 (0.25) (0.20) (0.22) CS 7182 8460 3620 43.8 41.3 40.1 Math 0.00* 0.00* 0.00_ * RS 5318 4550 3227 52.4 45.7 48.3 (0.28) (0.22) (0.40) CS 7182 8460 3620 46.6 41.3 40.3 Filipino 0.00* 0.00* 0.00* RS 5318 4550 3227 49.8 44.0 48.3 (0.24) (0.24) (0.40) CS 7182 8460 3620 45.0 39.2 40.5 Araling P 0.00* 0.00* 0.00* RS 5318 4550 3227 47.3 42.9 43.6 (0.15) (0.17) (0.23) CS 7182 8460 3620 43.7 38.9 38.6 Overall 0.00* 0.00* 0.00* RS 5318 4550 3137 49.88 44.8 47.2 (0.33) (0.31) (0.45) Achievem CS 7182 8460 3494 44.8 40.3 41.0 *Mean difference between RS and CS in the indicated subject and year is significant. entCohen’s d in parentheses below p value

The Role of Knowledge Channel Television Shows on Students’ Learning 41

The effect size was also calculated for each of the 5 subject areas and for the overall achievement score. Comparatively, for the 2009 and 2010 sample groups, English returned the highest effect size (d=0.35) followed by Mathematics (d=0.28) in 2009 and

Filipino (d=0.25) in 2010. This pattern, however, is different in 2011, wherein the biggest effect size (d=0.40) was seen in Mathematics and in Filipino, then followed by

English (d=0.38). The effect size of the overall achievement scores was calculated at

0.33 in 2009, 0.31 in 2010 and 0.45 in 2011 (p < 0.005). This suggests that the mean scores of RS students were at 33%, 31%, and 45% advantage over the mean scores of the CS students for the 2009, 2010, and 2011 sample groups respectively. These results corroborate the findings of the 2007 impact evaluation of Knowledge Channel shows on students’ achievement scores (Mapa, 2007). While the present study found that the higher effects were found in English test performance (in 2009 and in 2010) and in

Math test performance (in 2011), Mapa (2007) found that the presence of Knowledge

Channels was likely to be felt in Science and in Mathematics.

Study 1 also looked at gender differences in the test scores across the 5 subject areas. Each chart displays the pattern of gender differences in the students’ mean scores. For the 2009 sample group, results showed that the female student respondents scored significantly higher than males in English, Science, Filipino, and Araling

Panlipunan. However, the difference in mean scores in Mathematics between male and female students was not statistically significant (Table 7). The overall achievement scores of the student respondents across the 5-subject areas indicated that the mean percent scores of females (47.49) was statistically different (p-value< 0.005) from those of males (46.15).

The Role of Knowledge Channel Television Shows on Students’ Learning 42

Table 7 Mean percent scores between male and female students across the 2009, 2010 and 2011 sample groups .

Variable N M P 2009 2010 2011 2009 2010 2011 2009 2010 2011 English 0.00* 0.00* 0.98 Female 7063 6757 3845 50.5 45.7 47.2 Male 5437 6253 3001 49.2 44.4 47.3 Science 0.00* 0.10 0.05 Female 7063 6757 3845 46.2 42.4 41.4 Male 5437 6253 3002 44.6 42.4 42.2 Math 0.07 0.01* 0.21 Female 7063 6757 3845 49.3 43.3 43.8 Male 5437 6253 3002 48.7 42.4 44.4 Filipino 0.00* 0.00* 0.01* Female 7063 6757 3845 47.7 41.7 44.7 Male 5437 6253 3002 46.2 40.0 43.5 Araling 0.00* 0.01* 0.25 Female 7063 6757 3845 46.3 40.8 40.7 Panlipunan Male 5437 6253 3002 44.0 39.7 41.3 Overall 0.00* 0.00* 0.83 Female 7063 6757 3733 47.5 42.3 44.0 Achievement Male 5437 6253 2898 46.2 41.4 43.9 *Mean difference between gender cohorts in the indicated subject and year is significant. Females outperformed males in all subjects.

For the 2010 sample group, the female students significantly outperformed the male students in all subject areas except in Science. For the 2011 sample group, it was only in

Filipino that the female students scored significantly (p< 0.005) higher than the males.

In all other subject areas, male students’ mean scores were higher but the difference is not significant. Overall scores of respondents from the 2011 sample group show that females have higher mean scores but the difference is not statistically significant.

It can be deduced that it is only the 2009 and 2010 sample groups that females performed better than the males in terms of their achievement scores (Fig. 6). This finding confirms previous findings that females scored significantly higher than males did (Quimbo, 2003; Wentzel, 1988; Amelink, 2009).

The Role of Knowledge Channel Television Shows on Students’ Learning 43

Figure 6. Gender differences in the students’ mean scores in 2009 , 2010 and 2011 sample groups in the five subject areas and in the overall score.

The Role of Knowledge Channel Television Shows on Students’ Learning 44

Regional Differences

Seven regions were covered for analysis in 2009 sample group, eight regions in the 2010 sample group, and four regions in the 2011 sample group. The overall mean scores refer to the average of students’ scores in all subjects (Table 8 & Fig 7). The overall score of the recipient group (M=49.78) is significantly higher than that of the comparison group (M=44.78). All regions have recipient schools that performed higher than their comparison schools except in regions 4a and NCR. Among the recipient schools, the highest performing students are in Region 4b (M=57.13) and the lowest performing students come from Region 4a M=(44.58).

Table 8 Overall Mean Achievement Score per region between RS and CS in the 2009 sample group.

Variable Mean Recipient Comparison Overall Achievement 49.78 44.78 Region 1 53.05 45.34 3 53.89 41.11 4a 44.58 45.73 4b 57.13 48.39 6 44.64 42.05 10 45.16 39.82 NCR 48.41 49.84

Figure 7. Students’ Overall Mean Scores between Recipient and Comparison Schools across regions in 2009.

The Role of Knowledge Channel Television Shows on Students’ Learning 45

In each of the subject areas, the RS performed better than CS. Table 9 shows which specific regions where KC recipients performed better and whose scores are more convergent or more consistent across different subject areas.

Table 9 Summary of Regions where RS performed better, and have more convergent scores than CS in the 2009 sample based on their descriptive statistics.

Regions where recipient Regions where recipient schools’ Subject Area schools performed better than scores are more convergent than comparison schools comparison schools

English 1, 3, 4b, 6, and 10 None Science All 1and 6

Math 1, 3, 4b, 6, and 10 4a

Filipino 1, 3, 4b, 6 , and 10 4aand 10 Araling Panlipunan 1, 3, 4a, 4b, and 10 4a, 6, 10 and NCR Overall 1, 3, 4b, 6 and 10 4a

To see if these differences in their average scores are significant and not due to sampling error, as well as to determine how much does each factor contribute to the variation in scores, the 2-way ANOVA test of between subjects effects was conducted.

Students’ achievement scores in each subject area was analyzed using a factorial analysis of variance (ANOVA) with two between participant factors: Type (RS vs. CS) and Region (1, 3, 4a, 4b, 6, 10, and NCR). Table 10 shows the test results.

The Role of Knowledge Channel Television Shows on Students’ Learning 46

Table 10 Two-way ANOVA test of between Subjects Effects using the 2009 sample group.

Subject F Sig. Partial Eta Squared Area Type Region Type * Type Re- Type Type Re- Type Region gion * Re- gion * Re- gion gion 287.284 68.255 33.199 0.000 0.000 0.000 0.022 0.032 0.016 English 146.953 60.227 13.459 0.000 0.000 0.000 0.012 0.028 0.006 Science 156.882 64.107 35.142 0.000 0.000 0.000 0.012 0.030 0.017 Math 115.773 91.856 28.206 0.000 0.000 0.000 0.009 0.042 0.013 Filipino Araling 56.508 41.735 20.372 0.000 0.000 0.000 0.005 0.020 0.010 Panlipunan 259.282 108.31 40.858 0.000 0.000 0.000 0.020 0.049 0.019 Overall

In English for instance, the main effects due to type (RS or CS), F(1, 12486) =

3.84< 287.284, p<0.0005), and region factors F(6, 12486) =2.10<68.255, p< 0.05), and the interaction between these F(6, 12486) = 2.10<33.199, p < 0.05, η2 = 0.016 were unlikely to have arisen due to sampling error, thus suggesting that those who received the KC videos perform better than those who did not (means of 53.51 and 46.89, respectively, partial η2 = 0.022). This implies that 2.2% of the overall variance was attributable to the influence of the KC videos. The main effect of region suggests that there are regions that perform significantly higher than the others (two of these regions take the extremes: Region 4b and 4a with means 60.29 and 47.43, respectively, partial

η2 =0.032) in the English test. Thus, 3.2% of the variance in achievement scores was due to the region.

The Role of Knowledge Channel Television Shows on Students’ Learning 47

In the graph (please see Figure 8), this refers to the vertical distance (red line) between the highest and the lowest point in the blue line. Finally, the interaction between the type and the region was considerable and accounts for 1.6% of the overall variance. This interaction can be further investigated using t-tests and analysis of the following graphs. These analyses showed that the effects of region on both recipient and comparison groups were such that they were unlikely to have arisen from sampling error. Similarly, the effects of being in the recipient or comparison group in any region were also unlikely to have arisen due to sampling error (all p-values < 0.05).

In all subject areas, the main effect of type and region, and their interaction effects contribute little to the variation in the achievement scores (at most 2.0%). The greatest main effect by type is seen in English (partial eta squared value of 0.022) and the least in Araling Panlipunan (partial eta squared value of 0.005). The greatest main effect by region is seen in Filipino (partial eta squared is 0.036) and the least in Araling

Panlipunan (partial eta squared is 0.020). The greatest interaction effect is found in

Math (partial eta squared is .017) and the least is in Science (partial eta squared is

0.006). All effects are significant, which means that effect sizes (both main and interaction effects) attributable to the said factors (i.e. type and region) were unlikely to have arisen due to sampling error. The main effect of type in the variation in students’ overall achievement score is 2.0%. The main effect of region to the variation of overall achievement score is 4.9%. While the interaction effect of both type and region to overall achievement score is 1.9%.

The region factor is presented in the horizontal axis of the graph. The type of respondent factor is represented as lines. The blue line in Figure 8 represents overall achievement mean score of students in the recipient schools and the green line is that of the students

The Role of Knowledge Channel Television Shows on Students’ Learning 48 in the comparison schools. We can immediately see from this graph that having received the KC videos contribute to a better performance (in most regions).

Figure 8. Line graph illustrating the interaction between the type of respondents and Region in English test using the 2009 sample group.

For example, the broken vertical lines connecting between the blue and green lines in Region 1 refer to the difference in overall achievement scores between RS respondents (performing better because blue line is on top of the green line) and its comparison group. So, in most regions (except 4a and NCR), the students in the RS performed better in English than the students in the CS. The main effect of the second factor region can be seen in each of the two lines. In the blue line (recipients group), we can see that it is at its peak in Region 3 and lowest at Region 4a. The difference in the

The Role of Knowledge Channel Television Shows on Students’ Learning 49

English scores between these two extreme scores refers to the vertical distance (length of the red line) between these two extreme points in the blue line. In the green line

(comparison group), students in the NCR scored the highest and students in Region 10 got the lowest score. These differences (between regions in the same type) are found to be significant (the main effect of region in English has p< 0.0005). Since the lines are not parallel, there is a disordinal interaction between the type of recipients and region where they come from. The graph shows that in most cases (Regions 1, 3, 4b, 6, and

10), which received the KC videos have a positive effect (increase in gain scores) on students’ performance. A similar pattern can be observed in the line graphs of each subject area test (Fig. 9).

Figure 9. Line graph illustrating the interaction between the type of respondents and Region in English (E), Science (S), Math (M), Filipino (F), and Araling Panlipunan (AP) tests in the 2009 sample group.

The Role of Knowledge Channel Television Shows on Students’ Learning 50

Post Hoc tests were conducted to determine the regions where performance of the students in the recipient schools are significantly better than the performance of the students in the comparison schools. Table 11 provides a summary of these regional differences.

Table 11 Summary of regions where recipient schools performed significantly better than the students in the comparison schools in the 2009 sample group.

Regions where recipient schools Regions where performance of the performed significantly better than recipient schools and comparison Subject Area comparison schools schools do not significantly differ (p < 0.05 and t > 0) (p > 0.05 ) English 1, 3, 4b,6, and 10 NCR Science 1, 3, 4a, 4b, 10 6, NCR

Math 1, 3, 4b,6, and 10 NCR

Filipino 1, 3, 4b, 6, and 10 None A.Panlipunan 1, 3, 4b, and 10 4a Overall 1, 3,4b,6, and 10 NCR

It can be observed from Table 11 that in English, Math and Araling Panlipunan, in regions 1, 3, 4b, 6 and 10, RS performed better than the CS. While in Science, scores of the students in the RS and in the CS do not differ significantly. As for region 4a, it was only in Science, where the RS performed significantly better than CS. While in the rest of the subjects, NCR’s RS and CS do not significantly differ.

Overall Achievement score per region in 2010

For the 2010 sample group, the overall score of the recipient group (44.38) is significantly higher than that of the comparison group (40.31). Table 12 shows that in terms of overall achievement, the top performing RS students come from Region 1

The Role of Knowledge Channel Television Shows on Students’ Learning 51

(59.74) and the lowest performing RS students come from CAR (38.15). For each of the subject areas, RS performed better than CS in most regions.

Table 12 Overall Mean Achievement Score per region between recipient and comparison schools in the 2010 sample group.

Variable Mean Recipient Comparison Overall Achievement 44.38 40.31 Region 1 59.74 39.00 2 44.84 39.93 4a 41.98 39.83 5 40.31 43.40 6 49.66 42.58 12 43.11 34.29 CAR 38.15 42.48 NCR 50.27 42.86

Figure 10. Students’ Overall Mean Scores between Recipient and Comparison Schools across regions in the 2010 sample group.

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Table 13 Summary of Regions where RS performed better, and have more convergent scores than CS in the 2010 sample group based on their descriptive statistics.

Regions where recipient Regions where recipient schools’ scores are more Subject Area schools performed better than convergent than comparison schools comparison schools English 1, 2, 4a, 6, 12, and NCR 5 Science 1, 2, 4a, 6, 12, and NCR 5

Math 1, 2, 4a, 6, 12, and NCR 5 and CAR

Filipino 1, 2, 4a, 6, 12, and NCR 5 Araling Panlipunan 1, 2, 4a, 6, 12, and NCR 5 and CAR Overall 1, 2, 4a, 6, 12, and NCR 5 and CAR

Table 14 reveals students’ achievement scores in each subject area analyzed using a factorial analysis of variance (ANOVA) with two between participant factors: Type (RS vs. CS) and Region (1, 2, 4A, 5, 6, 12, CAR and NCR).

In English for instance, the main effects due to type (RS or CS), (F(1, 17,842) =

3.84 < 348.763, p < 0.05), and region factors (F(7, 17,842) = 2.10 < 89.522, p < 0.05), and the interaction between these (F(7, 17,842) = 2.10 < 128.80, p < 0.05, η2 = 0.048) were unlikely to have arisen due to sampling error, thus suggesting that those who received the KC videos perform better than those who did not (means of 50.02 and

42.58, respectively, partial η2 = 0.019). This shows that 1.9% of the overall variance was attributable to the influence of the KC videos. The main effect of region suggests that there are regions that perform significantly higher than the others (two of these regions take the extremes: Region 1 and 6 with means 64.75 and 55.34, respectively,

The Role of Knowledge Channel Television Shows on Students’ Learning 53 partial η2 =0.034) in the English test. Thus, 3.4% of the variance in achievement scores was due to the region.

Table 14 Two-way ANOVA Test of between Subjects Effects using the 2010 sample group.

Subject F Sig. Partial Eta Squared Area Type Region Type * Type Re- Type * Type Re- Type * Region gion Re- gion Re- gion gion 348.763 89.522 128.80 0.000 0.000 0.000 0.019 0.034 0.048 English 182.229 42.534 49.215 0.000 0.000 0.000 0.010 0.016 0.019 Science 237.859 72.170 68.647 0.000 0.000 0.000 0.013 0.028 0.026 Math 79.709 54.855 101.62 0.000 0.000 0.000 0.004 0.021 0.038 Filipino Araling 75.866 54.954 65.232 0.000 0.000 0.000 0.004 0.021 0.025 Panlipunan 300.463 112.26 144.41 0.000 0.000 0.000 0.017 0.042 0.054 Overall

Finally, the interaction between the type and the region (Fig. 11) was considerable and accounts for 5.4% of the overall variance. In all subject areas, the main effect of type and region, and their interaction effects contribute little to the variation in the achievement scores (at most 1.7%). The greatest main effect by type is seen in English

(partial eta squared value of 0.019) and the least in Filipino and Araling Panlipunan

(partial eta squared value of 0.004). The greatest main effect by region is seen in

English (partial eta squared is 0.034) and the least in Science (partial eta squared is

0.016). The greatest interaction effect is found in English (partial eta squared is .048) and the least is in Science (partial eta squared is 0.019). All effects are significant, which means that effect sizes (both main and interaction effects) attributable to the said factors (i.e. type and region) were unlikely to have arisen due to sampling error. The main effect of type in the variation in students’ overall achievement score is 1.7%. The

The Role of Knowledge Channel Television Shows on Students’ Learning 54 main effect of region to the variation of overall achievement score is 4.2%. The interaction effect of both type and region to overall achievement score is 5.4%.

Figure 11 Line graph illustrating the interaction between the type of respondents and region in Overall Mean scores in 2010. In most regions (except 5 and CAR), students in the RS group performed better than students in the CS. The main effect of the second factor region can be seen in each of the two lines. In the blue line (recipients group), we can see that it is at its peak in

Region 1 and lowest at Region CAR. The difference between these two extreme scores refers to the vertical distance (length of the red line) between these two extreme points in the blue line. In the green line (comparison group), Region 5 scores the highest and

Region 12, the lowest. These differences (between regions in the same type) are found

The Role of Knowledge Channel Television Shows on Students’ Learning 55 to be significant (the main effect of region in English has p< 0.0005) at 5% level of significance.

Since the lines are not parallel, there is a disordinal interaction between the type of recipients and region where they come from. The graph shows that in most cases

(Regions 1, 2, 4A, 6, 12, and NCR), having received the KC videos have a positive effect (increases) on students’ performance. A similar pattern can be observed in the remaining subject areas.

Post Hoc tests were conducted to see which regions, recipient schools (1) statistically performed better than, (2) statistically performed poorer than and (3) do not significantly differ with those of their comparison schools. Table 14 is then refined into the following:

Table 15 Summary of Regions where students in recipient schools performed significantly better than those in the comparison schools in the 2010 sample group.

Regions where recipient schools Regions where performance of the performed significantly better recipient schools and comparison Subject Area than comparison schools schools do not significantly differ (p < 0.05 and t > 0) (p > 0.05 ) English 1, 2, 4a,6, 12 and NCR None Science 1, 2, 4a,6, 12 and NCR 5

Math 1, 2, 4a,6, 12 and NCR One

Filipino 1, 2, 4a,6, and 12 None A.Panlipunan 1,2, 4a, 6 and 12 NCR Overall 1, 2,4a,6, 12 and NCR None

It can be observed from Table 15 that for English, Math and Science, in regions 1,

2, 4A, 6, 12 and NCR students in the recipient schools performed better than the their comparison schools. Almost in all regions and subjects, the RS performed significantly better than CS. While in Science, Region 5’s RS and CS scores do not significantly

The Role of Knowledge Channel Television Shows on Students’ Learning 56 differ. Except in CAR, all RS in other regions performed better than CS in Science. This may be due to the regularity in schedule of viewing in Science compared to other subjects.

Overall mean score per region in 2011

In 2011, the overall mean score of the recipient group (47.21) is significantly higher than that of the comparison group (41.02) as shown in Table 16 and Fig. 12. The recipient schools scored significantly higher than comparison schools in all regions except NCR. Overall, among the recipient schools, the highest performing students come from CARAGA (51.82) and the lowest come from NCR (41.58). Among the comparison schools, the highest score is registered for NCR (52.55) while the lowest score is from Region 1 (38.51).

Table 16 Overall Mean Achievement Score per region between recipient and comparison schools in the 2011 sample group.

Variable Mean Recipient Comparison Overall Region 1 44.16 38.51 Performance Region 3 46.09 42.21 CARAGA 51.82 43.14 NCR 41.58 52.55 TOTAL 47.21 41.02

The Role of Knowledge Channel Television Shows on Students’ Learning 57

Figure 12 Students’ Overall Mean Score between Recipient and Comparison Schools across regions in the 2011 sample group. In each of the subject area, RS performed better than CS. However, it is noticeable that not all regions contribute to this effect. Table 17 shows which regions across different subject areas did KC recipients perform better and whose scores are more convergent.

Table 17 Summary of Regions where RS performed better, and have more convergent scores than CS based solely on their descriptive statistics in the 2011 sample group.

Regions where recipient Regions where recipient schools’ Subject Area schools performed better scores are more convergent than than comparison schools comparison schools

English All except NCR None Science All except NCR NCR

Math All except NCR None

Filipino All except NCR None AralingPanlipunan All except NCR NCR Overall All except NCR Region 3 and NCR

To see if these differences in their average scores are significant and not due to sampling error, the 2-way ANOVA test of between subject effects was conducted.

The Role of Knowledge Channel Television Shows on Students’ Learning 58

Further, the analysis aimed to find out how much does each factor contribute to the variation in scores.

Students’ achievement scores in each subject area were analyzed using a factorial analysis of variance (ANOVA) with two between participant factors: Type (RS vs. CS) and Region (1, 3, CARAGA, and NCR). Table 18 shows the test results.

Table 18 Two-way ANOVA Test of between Subjects Effects in the 2011 sample group.

Subject F Sig. Partial Eta Squared Area Type Region Type * Type Re- Type * Type Re- Type * Region gion Re- gion Re- gion gion 12.42 106.36 32.72 0.000 0.000 0.000 0.002 0.045 0.014 English 0.951 70.70 23.96 0.329 0.000 0.000 0.000 0.030 0.010 Science 4.83 132.39 62.71 0.028 0.000 0.000 0.001 0.055 0.027 Math 18.54 23.65 31.67 0.000 0.000 0.000 0.003 0.010 0.014 Filipino Araling 0.108 36.09 22.97 0.743 0.000 0.000 0.000 0.016 0.010 Panlipunan 14.963 88.93 49.65 0.000 0.000 0.000 0.002 0.039 0.022 Overall

In English for instance, the main effects due to type (RS or CS), F(1, 6838) =

12.42, p< 0.0005), and region factors F(3, 6838) = 106.36, p < 0.0005), and the interaction between these F(3, 6838) = 32.72, p < 0.0005, η2 = 0.014) were unlikely to have arisen due to sampling error. The effect size (η2 = 0.014) suggests that 1.4% of the overall variance was attributable to the interaction of regional location and presence of the KC videos.

The Role of Knowledge Channel Television Shows on Students’ Learning 59

The main effect of region suggests that there are regions that perform significantly higher than the others in the test. Thus, 4.5% of the variance in achievement scores was due to the difference in regional location.

Finally, the interaction between the type and the region was considerable and accounts for about 1.4% of the overall variance. This interaction can be further investigated using t-tests and analysis of the following graphs. These analyses showed that the effects of region on both recipient and comparison groups were such that they were unlikely to have arisen from sampling error. Similarly, the effects of being in the recipient or comparison group in any region were also unlikely to have arisen due to sampling error (all p-values < 0.05 for type*region interaction).

In all subject areas, the main effect of type and region, and their interaction effects contribute little to the variation in the achievement scores. The greatest main effect by type is seen in Filipino and the least in Araling Panlipunan and Science. The greatest main effect by region is seen in Math (partial eta squared is 0.055) and the least in

Filipino (partial eta squared is 0.010). The greatest interaction effect is found in Math

(partial eta squared is .027) and the least interaction effect is in Filipino and Science

(partial eta squared is 0.010). All type*region interaction effects are significant, which means that effect sizes (both main and interaction effects) attributable to the two factors

(i.e. type and region) were unlikely to have arisen due to sampling error.

The Role of Knowledge Channel Television Shows on Students’ Learning 60

Figure 13. Line graph illustrating the interaction between the type of respondents and Region in English test in the 2011 sample group. The blue line in Figure 13 represents English achievement average score of recipient schools and the green line that of the comparison schools. We can infer from the graph that having received the KC videos contribute to an overall better performance of RS samples (except in NCR) compared to their comparison groups. For example, the broken vertical lines connecting between the blue and green lines in Regions 1 and

CARAGA refer to the difference in overall achievement scores between RS respondents

(performing better because blue is on top of green) and its comparison group. So, in all regions but NCR, the recipients performed better than their comparison groups (Table

19).

The Role of Knowledge Channel Television Shows on Students’ Learning 61

The main effect of the second factor region can be seen in each of the two lines. In the blue line(recipients group), we can see that it is at its peak in CARAGA and lowest at Region 1. The difference in the overall scores between these two extreme scores refers to the vertical distance (length of the red line) between these two extreme points in the blue line. In the green line (comparison group), NCR scores the highest and

Region 1 the lowest. These differences (between regions in the same type) are found to be significant (the main effect of region in overall achievement scores has p-value <

0.05) at 5% level of significance. Since the lines are not parallel, there is a disordinal interaction between the type of recipients and region where they come from. The graph shows that in most regions, having received the KC videos results to a positive effect

(increases) on students’ performance. A similar pattern can be observed in the line graphs of each subject area test.

Table 19 Summary of Regions where students in recipient schools performed significantly better than those in the comparison schools in the 2011 sample group.

Regions where Regions where Regions where the recipient schools performance of the recipient schools performed recipient schools and Subject significantly significantly better comparison schools Area performed below their than comparison do not significantly comparison schools schools differ (p < 0.05 and t < 0) (p < 0.05 and t > 0) (p > 0.05 ) English 1, 2, 4a,6, 12 and NCR 5 and CAR None Science 1, 2, 4a,6, 12 and NCR CAR 5

Math 1, 2, 4a,6, 12 and NCR 5 and CAR One

Filipino 1, 2, 4a,6, and 12 5, CAR, and NCR None Araling 1, 2, 4a, 6 and 12 5 and CAR NCR Panlipunan

Overall 1, 2,4a,6, 12 and NCR 5 and CAR None

The Role of Knowledge Channel Television Shows on Students’ Learning 62

Rural vs. Urban Difference

This study further looked into the achievement scores between RS and CS groups when respondents are grouped according to the rural-urban classification of provinces and cities. This analysis was motivated by the result in the previous section which found that in certain regions, comparison schools scored significantly higher than recipient schools. We hypothesized that schools in urban areas scored significantly better than schools in rural areas.

Rural vs. Urban Difference in the 2009 Sample

Based on the 2010 census of population and housing (web0.psa.gov.ph), the 13 provinces and cities involved in 2009 study are classified as presented in Table 20 below.

Table 20 Urban-Rural Classification of Provinces and Cities in the 2009 sample group.

Province/City Classification Ilocos Sur Rural La Union Rural Bataan – Mariveles Urban Tarlac – Concepcion Rural Cavite – Naic Rural Rizal Urban Occidental Mindoro – San Jose Urban Oriental Mindoro Rural Antique Rural Lanao del Norte – Iligan City Urban Misamis Oriental – Cagayan de Oro City Urban NCR – Markina Urban

The Role of Knowledge Channel Television Shows on Students’ Learning 63

Urban provinces and cities are areas with urbanization level higher than the national level. In 2010, the national urbanization level was pegged at 45.3%. This suggests that respondents coming from Bataan, Rizal, Occidental Mindoro, Iligan City, Cagayan de

Oro City, and Marikina City shall be classified as urban respondents for the purpose of comparative analysis.

Table 21 Differences in mean percent scores between urban and rural respondents in the 2009 sample group.

Variable N M t P English 10.2a 0.000 Urban 6869 50.51 Rural 5631 48.05 Science 11.1 0.000 Urban 6869 46.88 Rural 5631 43.72 Math 5.5a 0.072 Urban 6869 49.97 Rural 5631 47.92 Filipino 6.9a 0.000 Urban 6869 48.20 Rural 5631 45.70 Araling Panlipunan 7.2a 0.000 Urban 6869 46.67 Rural 5631 43.60 Overall 10.7a 0.000 Urban 6869 48.21 AchievementRural 5631 45.32 aThe t and df were adjusted because variances were not equal. N = 12,500

As can be gleaned from Table 21, the independent samples t-test revealed that mean scores of the respondents from urban provinces and cities were significantly higher than those from the rural areas. This result confirms our hypothesis that students in highly urbanized areas scored higher than those in the rural areas, which implies that both CS and RS students have equal access to instructional input through Television and other

The Role of Knowledge Channel Television Shows on Students’ Learning 64 media, and may explain why students in comparison schools in Region 4A performed significantly higher than students in recipient schools.

Rural vs. Urban Difference in the 2010 sample

Based on the 2010 census of population and housing (web0.psa.gov.ph), the locations involved in the 2010 sample were classified and presented in Table 22.

Table 22 Urban-Rural Classification of Provinces and Cities in the 2010 sample group.

Province/City Classification Ilocos Norte Rural Ilocos Sur Rural Isabela Rural Batangas Rural Cavite Rural Laguna – Pangil Urban Laguna – Cavinti, Liliw, Luisiana, Rural Pagsanjan Camarines Norte – Daet Urban Camarines Norte – Mercedes, Vinsons Rural Sorsogon Rural Iloilo Rural Sarangani Rural Benguet Rural Pasig Urban

Urban Provinces and Cities are areas with urbanization level higher than the national level. In 2010, the national urbanization level was pegged at 45.3%. This suggests that respondents coming from Pangil, Laguna, Daet, Camarines Norte, and Pasig shall be classified as urban respondents for the purpose of comparative analysis.

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Table 23 Differences in percent mean scores between urban and rural respondents in the 2010 sample group.

Variable N M t p English 0.762a 0.446 Urban 809 46.23 Rural 17,033 45.73 Science -1.948a 0.051 Urban 809 41.70 Rural 17,033 42.83 Math -1.516a 0.129 Urban 809 42.50 Rural 17,033 43.61 Filipino 0.005a 0.996 Urban 809 41.50 Rural 17,033 41.50 Araling Panlipunan -0.705a 0.481 Urban 809 40.06 Rural 17,033 40.67 Overall -0.899a 0.368 Urban 809 41.98 Achievement Rural 17,033 42.45 aThe t and df were adjusted because variances were not equal. N = 17,842

As can be gleaned from Table 23, the independent samples t-test reveals that the scores of students from both urban provinces and cities and the rural areas are not significantly different. This means that as for the 2010 sample group, there is not enough evidence to support the hypothesis that students in urbanized areas score higher than those in the rural areas. The findings further revealed that the mean score differences between urban and rural areas is highest in science and lowest in Filipino.

The Role of Knowledge Channel Television Shows on Students’ Learning 66

Rural vs. Urban Difference in the 2011 sample

Based on the 2010 census of population and housing (web0.psa.gov.ph), the 7 provinces and cities involved in the 2011 sample group are presented in Table 24.

Table 24 Urban-Rural Classification of Provinces and Cities in the 2011 sample group.

Province/City Classification Butuan Urban Ilocos Rural La Union Rural Nueva Ecija (San Jose City) Urban Pasig Urban Surigao del Norte Rural Zambales Rural

Urban Provinces and Cities are areas with urbanization level higher than the national level. In 2010, the national urbanization level was pegged at 45.3%. This suggests that respondents coming from Butuan, Nueva Ecija (San Jose City), Pasig shall be classified as urban respondents for the purpose of comparative analysis.

As can be gleaned from Table 25, the independent samples t-test revealed that student respondents from urban provinces and cities consistently scored significantly higher than those student respondents from the rural areas.

The Role of Knowledge Channel Television Shows on Students’ Learning 67

Table 25 Differences in percent mean scores between urban and rural respondents in the 2011 sample group.

Variable N M SD t df P English 9.84a 4514a 0.000 Rural 4644 45.70 19.449 Urban 2202 50.50 18.540 Science 7.08 6845 0.000 Rural 4645 40.82 16.473 Urban 2202 43.79 15.563 Math 12.79a 4188a 0.000 Rural 4645 41.81 20.397 Urban 2202 48.73 21.128 Filipino 10.93 6845 0.000 Rural 4645 42.40 19.582 Urban 2202 47.92 19.405 AralingPanlipunan 10.97a 4358a 0.000 Rural 4645 39.07 21.124 Urban 2202 44.88 23.419 Overall 11.94a 4275a 0.000 Rural 4429 42.49 13.814 Achievement Urban 2202 46.88 14.248 aThet and df were adjusted because variances were not equal. N = 6846

Synthesis of Comparative Analysis

Comparative analysis of the mean scores across subject areas and in the overall scores between rural and urban type of provinces and cities in the 2009 and 2011 sample groups revealed interesting findings. Student respondents from schools in the urban areas performed better than those student respondents in the rural areas.

The Role of Knowledge Channel Television Shows on Students’ Learning 68

Grade Level Differences To see if there are significant differences in mean scores between groups according to type and grade levels, and to describe how much does each factor contribute to the variation in scores, the 2-way ANOVA test of between subjects effects was conducted.

Conditions of normality and homogeneity of variance were satisfied, which warranted the use of ANOVA in overall scores as well as per subject area between groups and within each of the groups.

Overall Achievement Score per Grade Level in the 2009 sample

A total of 12,787 student respondents constitute the 2009 sample groups included in the analysis of the differences in mean test scores among grade levels and between school type (RS and CS). In this 2009 sample group, 43% were students from RS and the other 57% were students from CS (Table 26).

Table 26 Distribution of participants per type and per grade level in the 2009 sample group.

Number of Total Participants Number of KC Participants from Grade from each Grade Recipients Comparison Level Group 3 1,207 1,792 2,999 4 1,374 1,833 3,207 5 1,380 1,792 3,172 6 1,357 1,765 3,122 7 90 50 140 8 88 59 147 Total 5,496 7,291 12,787

Table 27 shows the mean of the overall scores in the 6 grade levels. The overall mean achievement score is 49.34 which vary by 15.97. Grade 6 respondents have the

The Role of Knowledge Channel Television Shows on Students’ Learning 69 highest mean score at 54.66, while the Grade 3 students recorded the lowest mean score

(44.61).

Table 27 Mean achievement percent score per grade level between RS and CS in the 2009 sample group.

Variable Mean Achievement Test Score Recipient Comparison Overall Achievement 49.34 44.76 Grade 3 44.61 37.87 4 52.01 47.20 5 47.29 43.91 6 54.66 50.16 7 42.52 39.52 8 40.24 39.48

Overall, mean achievement test score of the students from the recipient schools

(46.89) was significantly higher compared with the mean achievement test score of the students from the comparison schools (43.02). Across grade levels, mean scores of the students in the recipient schools were likewise significantly higher than the mean scores of the students in the comparison schools.

Students’ achievement scores in each subject area was analyzed using a factorial analysis of variance (ANOVA) with two between-participant factors: type (RS: recipient of KC vs. non-recipient schools labeled as CS-comparison schools) and grade levels. Table 28 shows the test results.

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Table 28 Two-way ANOVA test of between subjects effects in the 2009 sample group.

Subject F Sig. Partial Eta Squared Area Type Grade Type Type Grade Type Type Grade Type Level * level * level * Grade Grade Grade Level level level English 384.02 102.76 0.86 0.000 0.000 0.461 0.030 0.024 0.000 Science 270.88 2819.67 3.19 0.000 0.000 0.023 0.021 0.404 0.001 Math 241.40 82.03 11.36 0.000 0.000 0.000 0.019 0.019 0.003 Filipino 173.54 37.77 12.32 0.000 0.000 0.000 0.014 0.009 0.003 Araling 75.49 1343.95 5.19 0.000 0.000 0.001 0.006 0.244 0.001 Panlipunan Overall 353.47 346.36 7.14 0.000 0.000 0.000 0.028 0.077 0.002

The main effects due to the type are significant in all subject areas: English (F(1,

11492)=3.84 < 384.02, p < 0.05, η2 = 0.030), Science (F(1, 11492)= 3.84 < 270.88, p <

0.05, η2 = 0.021)Math (F(1, 11492)= 3.84 < 241.40, p < 0.05, η2 = 0.019), Filipino (F(1,

11492)= 3.84 <173.54, p < 0.05, η2 = 0.014) and Araling Panlipunan (F(1, 11492)= 3.84

< 75.49, p < 0.05, η2 = 0.006). This means that there is enough evidence to show that results were unlikely to have arisen due to sampling error. It is sufficient to conclude that in all subject areas, those who received the KC videos performed better than their comparison who did not receive it.

The main effects due to the grade level are all significant in all subject areas (p <

0.05). In Science, about 40% of the variation in scores is attributed to the grade level.

The main effect of grade level suggests that there are grade levels that significantly performed better than the others.

Interaction effects (Type * Grade level) of these two factors in all subject areas were found to be significant, therefore unlikely to have arisen from sampling error. Take for instance the average score in Math and Filipino, which have the greatest effect size

The Role of Knowledge Channel Television Shows on Students’ Learning 71 caused by the interaction of type and grade level (η2 = 0.003). This interaction can be further investigated using t-tests and analysis of the following graphs. These analyses showed that the effects of grade level on both recipient and comparison schools were such that they were unlikely to have arisen from sampling error. Similarly, the effects of being in the recipient or comparison group in any grade level were also unlikely to have arisen due to sampling error (all p-values < 0.05).

In terms of overall mean scores, the main effects of type and grade level, and their interaction effects, contributes little to the variation in the achievement scores. Of these three effects, the greatest was the main effect of grade level (eta squared 0.077). All effects are significant, which means that effect sizes (both main and interaction effects) attributed to the two factors (type and grade level) were unlikely to have arisen due to sampling error.

Table 29 Summary of the test performance of student participants in the Recipient Schools in the different Grade levels for the 2009 sample group.

Grade levels where recipient schools Grade levels where performance of the performedsignificantly better than recipient schools and comparison Subject Area comparison schools schools do not significantly differ (p < 0.05 and t > 0) (p > 0.05 ) English 3, 4, 5, 6, 7, 8 None Science 3, 4, 5, 6, 7, 8 None Math 3, 4, 5, 6, 7, 8 None Filipino 3, 4, 5, 6 , 7, 8 None APanlipunan 3, 4, 5, 6, 7, 8 None Overall 3, 4, 5, 6, 7, 8 None

Post Hoc tests were conducted to see which grade levels, the recipient schools (1) statistically performed better than, (2) statistically performed poorer than and (3) do not significantly differ with those of their comparison schools.

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It can be deduced from Table 29, that in all subjects, except in Araling Panlipunan,

RS performed significantly better than CS. In Araling Panlipunan. Mean scores of

Grade 5 students in RS did not significantly differ from the mean scores of the students in CS.

Overall achievement scores per grade level in the 2010 sample group

Sample sizes in each grade level for RS and CS in the 2010 sample group are given in Table 30. It can be gathered that 34.97% of the students were from RS and the remaining 65.03% of the students were from CS (Table 30).

Table 30 Distribution of Participants per Type and per Grade Level in 2010 sample group.

Number of Total Participants Number of KC Grade Participants from from each Grade Recipients Comparison Group Level 3 1,163 2,208 3,371 4 1,105 2,055 3,160 5 1,169 2,074 3,243 6 1,113 2,123 3,236 Total 4,550 8,460 13,010

Table 31 shows the overall mean scores across the four grade levels. Average scores in all grade levels indicate that students are in the beginning level. Grade 6 respondents have the highest mean score at 49.83and the lowest mean score (41.41) is from grade 3. It is below half of the total number of items.

Table 31 Overall mean achievement percent score in the 2010 sample group.

Variable Mean Recipient Comparison Overall Achievement 44.78 40.28 Grade 3 41.41 34.63 4 46.39 42.46 5 41.77 37.88 6 49.83 46.40

The Role of Knowledge Channel Television Shows on Students’ Learning 73

The recipient group had an overall mean score (44.78) that is significantly higher than that of the comparison group (40.28). Across all the four grade levels, the students in the recipient group have a mean score significantly higher than the comparison group.

To see if these differences in the mean scores between groups according to type and grade levels are significant and to determine how much each factor contributes to the variation in scores, the 2-way ANOVA test (Table 32) of between subjects effects was conducted.

Table 32 Two-way ANOVA Test of between Subjects Effects in the 2009 sample group.

Subject F Sig. Partial Eta Squared Area Type Grade Type Type Grade Type Type Grade Type level * Level * level * Grade Grade Grade Level level level English 335.67 100.16 11.79 0.000 0.000 0.000 0.025 0.023 0.003 Science 217.79 3,410.58 20.08 0.000 0.000 0.000 0.016 0.440 0.005 Math 145.92 45.69 9.14 0.000 0.000 0.000 0.011 0.010 0.002 Filipino 182.63 28.61 4.37 0.000 0.000 0.004 0.014 0.007 0.001 Araling 118.71 1,194.98 2.72 0.000 0.000 0.043 0.009 0.216 0.001 Panlipunan Overall 334.82 343.60 9.80 0.000 0.000 0.000 0.025 0.073 0.002

The main effects due to the type are significant in all subject areas: English (F(1,

13010) = 3.84 < 335.67, p < 0.05, η2 = 0.025), Science (F(1, 13010) = 3.84 < 217.78, p

< 0.05, η2 = 0.016) Math (F(1, 13010) = 3.84 < 145.91, p < 0.05, η2 = 0.011), Filipino

(F(1, 13010) = 3.84 < 182.63, p < 0.05, η2 = 0.014) and Araling Panlipunan (F(1,

13010) = 3.84 < 118.71, p < 0.05, η2 = 0.009). This means that there is enough evidence to conclude that in all subject areas, those who received the KC videos performed better than the comparison group, who did not receive KC videos.

The Role of Knowledge Channel Television Shows on Students’ Learning 74

The main effects due to the grade level are all significant in all subject areas (p <

0.05). In Science, about 44% of the variation in scores can be attributed to the grade levels. The main effect of grade level suggests that there are grade levels that significantly performed better than the others.

Interaction effects (Type * Grade level) of these two factors in all subject areas are significant, therefore unlikely to have arisen from sampling error. For instance: the mean score in Science, which had the greatest effect size caused by the interaction of type and grade level (η2 = 0.005). This interaction can be further investigated using t- tests and analysis of the succeeding graphs. These analyses showed that the effects of grade level on both recipient and comparison groups were such that they were unlikely to have arisen from sampling error ( p < 0.0005).

Overall, the main effects of type and grade level, and their interaction effects, contribute little to the variation in the achievement scores. Of these three effects, the greatest was the main effect of type and grade level (eta squared 0.005). All effects are significant, which means that effect sizes (both main and interaction effects) attributable to the factors type and grade level were unlikely to have arisen due to sampling error.

Post Hoc tests were conducted to better understand the significant differences in the achievement of students from recipient schools vis-à-vis the achievement of the students from comparison schools.

The Role of Knowledge Channel Television Shows on Students’ Learning 75

Table 33 Summary of performance in achievement tests across grade levels for recipient schools in the 2010 sample group.

Grade levels where recipient schools Grade levels where performance of performedsignificantly better than the recipient schools and comparison Subject Area comparison schools schools do not significantly differ (p < 0.05 and t > 0) (p > 0.05 ) English 3, 4, 5, 6 None Science 3, 4, 5, 6 None Math 3, 4, 5, 6 None Filipino 3, 4, 5, 6 None A.Panlipunan 3, 4, 6 None Overall 3, 4, 5, 6 None

It can be observed from the Table 33 that across all the 5-subject areas and in all the four grade levels (Grades 3,4, 5 and 6), students from RS performed significantly better than students from CS. There was no instance wherein students from CS performed significantly better than RS.

Overall achievement score per grade level in the 2011 sample group

A total of 5,945 students (Table 34) were included in this analysis, wherein 46.5% came from KC-recipient schools and the remaining 53.5% were students from the comparison schools.

The Role of Knowledge Channel Television Shows on Students’ Learning 76

Table 34 Distribution of Participants per type and per grade Level in the 2011 sample group.

Number of Grade Number of KC Participants from Total Participants Recipients Comparison from each Grade Group Level 3 554 669 1223 4 546 717 1263 5 563 669 1232 6 572 684 1256 7 253 214 467 8 275 229 504 Total 2763 3182 5945

While Table 35 shows that students in the recipient group had an overall mean score

(46.85) that is significantly greater than the comparison group (mean score 39.76).

Table 35 Overall Mean Achievement Score per grade level between RS and CS in the 2011 sample group.

Variable Mean Recipient Comparison Overall 46.85 39.76 Grade 3 46.48 39.07 Performance4 54.55 43.94 5 48.70 41.32 6 55.08 47.39 7 36.56 33.94 8 39.75 36.45

To see if the difference in students’ average scores between groups according to type and grade levels are significant and and to determine how much each factor contributes to the variation in scores, the 2-way ANOVA test of between-subjects effects was conducted.

The Role of Knowledge Channel Television Shows on Students’ Learning 77

Table 36 Two-way ANOVA Test of between Subjects Effects for the 2011 sample group.

Subject F Sig. Partial Eta Squared Area Type Grade Type Type Grade Type Type Grade Type level * level * level * Grade Grade Grade Level level level English 190.375 280.984 19.315 0.000 0.000 0.000 0.027 0.224 0.019 Science 134.614 600.607 12.323 0.000 0.000 0.000 0.019 0.381 0.012 Math 208.967 190.603 10.865 0.000 0.000 0.000 0.030 0.163 0.011 Filipino 206.308 26.672 6.211 0.000 0.000 0.000 0.029 0.027 0.006 Araling 42.789 328.581 23.143 0.000 0.000 0.000 0.006 0.252 0.023 Panlipunan Overall 253.735 160.057 13.34 0.000 0.000 0.000 0.037 0.145 0.014

Table 36 shows the ANOVA test results of between subjects effects for the 2011 sample group. The main effects due to the type are significant in all subject areas:

English (F(1, 6830)=3.84 < 190.375, p < 0.05, η2 = 0.027), Science (F(1, 6831)= 3.84 <

134.614, p < 0.05, η2 = 0.019)Math (F(1, 6831)= 3.84 < 208.967, p < 0.05, η2 = 0.030),

Filipino (F(1, 6831)= 3.84 <206.308, p < 0.05, η2 = 0.029) and Araling Panlipunan (F(1,

6831)= 3.84 < 42.789, p < 0.05, η2 = 0.006). This means that there are enough evidences to show that results were unlikely to have arisen due to sampling error.

Therefore it is sufficient to conclude that in all subject areas, those students who received the KC videos performed better than their counterparts who did not receive it.

The main effects due to the grade level are all significant in all subject areas (p <

0.05). In Science, about 38% of the variation in scores is caused by grade level. The main effect of grade level suggests that there are significant differences in the achievement of students across the 8 grade levels .that significantly performed better than the others. The interaction effects (Type * Grade level) of these two factors in all subject areas are significant, therefore unlikely to have arisen from sampling error. For

The Role of Knowledge Channel Television Shows on Students’ Learning 78 example, the average score in Araling Panlipunan returned the greatest effect size caused by the interaction of type and grade level (η2 = 0.023). This interaction can be further investigated using t-tests and analysis of the following graphs. These analyses showed that the effects of grade level on both recipient and comparison groups were such that they were unlikely to have arisen from sampling error. Similarly, the effects of being in the recipient or comparison group in any grade level were also unlikely to have arisen due to sampling error (all p-values < 0.0005).

Since all effects were significant, the effect sizes (both main and interaction effects) attributable to the two factors (type and grade level) were unlikely to have arisen due to sampling error.

Table 37 Summary of performance in the achievements tests across 6 grade levels.

Grade levels where recipient Grade levels where schools performed performance of the recipient Subject Area significantly better than schools and comparison comparison schools schools do not significantly (p < 0.05 and t > 0) differ (p > 0.05 ) English 4,5,6,7,8 None Science 4,5,6,7,8 None Math 3,4,5,6,7,8 None Filipino 3,4,5,6,7,8 None APanlipunan 3,4,5,6,8 None Overall 3,4,5,6,7,8 None

It can be gathered from Table 37, that for the 2011 sample group, students from the recipient schools performed better than students from the comparison schools in 6 grade levels (Grades 4, 5, 6, 7, 8 and 9). Students from RS also performed higher than their

CS counterparts in all the 5-subject areas.

The Role of Knowledge Channel Television Shows on Students’ Learning 79

Conclusion

Study 1 compared the achievement in the five subject areas between two groups of students: students from schools that integrated Knowledge Channel Shows (RS) in their curriculum and students from schools with no Knowledge Channel shows, referred to as comparison schools (CS). The considerably large sample size (N=32,368 students) included in the analysis provided sufficient evidence that led to the following significant findings:

1. Students from KC recipient schools (RS) have significantly higher scores than those from comparison schools (CS). Further investigation on the effect of exposure to KC shows suggests that students in the RS performed 33% better than the students in the CS for the 2009 sample group, 31% for the 2010 sample group and 45% fo the 2011 sample group. Interestingly, highest effects were noted in English (in 2009 and in 2010) and in

Math (in 2011).

2. Across various regions in the country, the RS respondents generally performed better than the CS respondents.

3. Female students in both 2009 and 2010 sample groups outperformed the males in almost all subjects.

4. Overall, students from RS performed better across all subjects in all grade levels compared with students from CS. Interestingly, grade 6 students were found to perform significantly higher than students from other grade levels.

The Role of Knowledge Channel Television Shows on Students’ Learning 80

Study 2 The Effect of Knowledge Channel Shows on Academic Achievement of Students from Various Learning Groups

Methods

Research Design

Study 2 utilized an experimental research design to investigate whether students from various learning groups (i.e. Passive, Active, Lecture) will have significantly different gains in terms of achievement scores. Students in the passive learning group were simply made to watch Knowledge Channel (KC) videos. Students in the active learning group watched KC videos with the teacher facilitating the processing of the contents of the video. Students in the lecture group were taught using the lecture type of instruction.

Participants

A total of 926 students were involved in this study and these students were randomly assigned to each of the three learning groups. The experiment was conducted in four recipient schools located in Luzon and Mindanao. The first experiment was implemented in Don Mariano Matugas NHS and Don Enriquez Navarro Elementary

School in Siargao, Mindanao; the second experiment was conducted in NAIC National

High School of Cavite and Pineda Elementary School of Pasig.

Instruments.

A 15-item test was developed for Science, Mathematics, English, and

AralingPanlipunan. For each subject area, the researchers selected three topics with a corresponding Knowledge Channel video. These tests were subjected to content

The Role of Knowledge Channel Television Shows on Students’ Learning 81 validation by subject matter experts from the Br Andrew Gonzalez College of

Education. A lesson plan was developed for the teachers who were assigned to the

Active Group. The contents in the videos were incorporated into the lesson plan.

Specific instructions were provided for teachers regarding the processing activities that they should do before, during, and after viewing the shows. A similar lesson plan was given to the teachers who were assigned to the Lecture Group.

Procedure

Prior to the experiment, teachers who were purposively selected to participate were given an orientation, copies of the videotapes of lessons selected for the study, and the lesson plan. The list of students randomly assigned for each learning group were also prepared by the participating teachers.

During the experiment, the Active Group went through several procedures. At the start of the experiment, the objectives and the procedures of the experiment were briefly discussed. The students then took a multiple-choice test which required them to use their recall, comprehension, analytic, and evaluative skills in test taking. Questions were based on the selected videos of Knowledge Channel. The teacher spent 3-5 minutes asking questions about the topic. Its purpose was to determine whether or not the students had prior knowledge about the topic. Then the teacher showed the videotape for the first topic. The teacher paused the videotape then asked students some questions about the lesson. The teachers explained some difficult concepts that students did not understand. The rest of the topic was viewed by the students. The teacher asked questions to test how much information was understood and retained by the students.

Difficult concepts were explained by the teacher. These steps were repeated for the two

The Role of Knowledge Channel Television Shows on Students’ Learning 82 other topics selected for the study. Finally, the students took the test after having viewed all the videos. The questions in the pre-test and post-test are the same.

The Passive Group went through the same procedure except that the teacher did not explain the topic to the students and did not ask questions before, during, and after viewing the videotapes. In the Lecture Group, the students were tested before and after the lecture instruction. The teachers directly taught the three topics discussed in the videos using the transmissivel way (asking questions, explaining concepts, showing visual aids, writing on the board).

Data Analysis

Paired Samples t-test was used to determine if there is difference between the pre-test and posttest scores for all student participants, in each learning group (passive, active and traditional lecture), and in each area (Luzon and Mindanao). Cohen’s d was used to determine the effect size of the instruction type in each learning group and area in their gain scores. A student’s gain score is determined by the difference between the pretest and posttest scores. In order to investigate further the difference in scores across the three learning groups, two-way Analysis of Variance (ANOVA) was used.

Study 2 Results

About 70% of the participants came from Luzon (n= 626) and the other 30% were from

Mindanao (n=293). As regards gender, 57.79% were females and the remaining 42.21% of the student participants were males (Fig. 14).

The Role of Knowledge Channel Television Shows on Students’ Learning 83

Figure 14 Profile of the student participants in study 2 in terms of gender, location, and grade level.

The participants in Study 2 were distributed among the three learning groups in about the same number. The lecture group was composed of 343 students (37%), 314 students in the passive (34%) and 262 students in the active group (29%).

Comparative Analysis

In order to determine whether there is significant difference in the pretest and posttest mean percent scores in each learning group and their effect sizes, an independent samples t-test was used. The same statistical test was used to determine the significant differences between pretest and posttest in each location.

Mean scores across learning groups and their effect sizes

The three learning groups posted gains in mean percent scores (posttest > pretest) as differences were all in positive values. Across the three learning groups, t-tests were found to be significant, where t(313)=5.714, p<0.0005, d=0.2316 for the Passive group, t(342)=8.605, p<0.0005, d=0.4088 for the Lecture group, and t(261)=13.976, p<0.0005, d=0.7415 for the Active group. Overall, across the three learning groups, t(918)=15.697, p<0.0005, d=0.4273.

The Role of Knowledge Channel Television Shows on Students’ Learning 84

Table 38 Mean scores across learning groups and locations in study 2.

Effect Mean Percent Standard Paired Samples Size Scores Deviation Learning Mean Group Difference Sig. Cohen’s Pre- Post- Pre- Post- t Df (2- d test test test test tailed) Passive 39.39 43.61 4.22 17.53 18.89 5.714 313 0.000 0.2316 Lecture 38.13 44.66 6.53 15.94 16.01 8.605 342 0.000 0.4088 Active 36.56 48.15 11.45 14.82 16.40 13.976 261 0.000 0.7415 Overall 38.11 45.26 7.15 16.22 17.23 15.697 918 0.000 0.4273 Mean Percent Standard Effect Paired Samples Scores Deviation Size Mean Location Sig. Cohen’s Pre- Post- Difference Pre- Post- t df (2- d test test test test tailed) Luzon 40.26 49.22 8.97 16.56 16.58 16.974 625 0.000 0.5407 Mindanao 33.53 36.79 3.26 14.48 15.45 3.918 292 0.000 0.2177

Mean scores between location and their effect sizes

Table 38 also shows the pretest and posttest mean percent scores per location and their corresponding standard deviations. Both Luzon and Mindanao means show gains in scores (post-test > pre-test), as mean differences are both positive values (3.26 and

8.97). Results revelaed significant difference between the posttest and pretest for Luzon where t (625)=16.97, p < 0.0005 and for Mindanao where t (292)=3.918, p < 0.0005.

Learning Group and Location Effects on Gain Score

Students’ gains scores in each of the three learning groups and two locations were analyzed using a factorial analysis of variance (ANOVA) with two between participant factors: learning group (passive, lecture and active) and location (Luzon vs. Mindanao).

Table 39 shows the cross-tabulation of the explanatory variables (learning group and location).

The Role of Knowledge Channel Television Shows on Students’ Learning 85

Table 39 The 3 x 2 contingency table of mean gain scores in study 2.

Location Combined mean Luzon Mindanao gain scores Passive 5.96 1.17 4.22 Lecture 7.39 5.02 6.53 Active 13.53 3.64 11.45 Total 8.97 3.26 7.15

Inspection of the contingency table showing mean gain scores, the Active group in

Luzon garnered the highest (13.53), followed by the lecture group (7.39), then the passive group last (5.96). This, however, is not the case in Mindanao where the lecture group got the highest (5.02), followed by the active group (3.64), then the passive group last (1.17).

The combined scores of both areas show that the active group performed the highest (11.45), followed by the lecture group (6.53) and the passive group (4.22).

Combining all scores from the three learning groups but comparing these per area, the

Luzon group has gained higher percent scores than the Mindanao group. This can be further clarified through the line graph (Fig. 15).

The Role of Knowledge Channel Television Shows on Students’ Learning 86

Figure 15. Estimated marginal means of post-test scores by learning group and location.

The lines in the graph intersect. This means that there is interaction between the two factors (learning group and location) affecting students’ posttest scores. The gain scores due to learning group were moderated by the location where the participants came from. Teacher’s processing skills vis-à-vis their lecture skills can be a plausible explanation for this finding. To determine if the differences in mean gain scores by learning group and location, as well as their interaction are significant, the 2-way

ANOVA test of between-subjects effects was conducted. Normality and homogeneity of variances were tested and satisfied warranting the use of the two-way ANOVA.

The Role of Knowledge Channel Television Shows on Students’ Learning 87

Table 40 ANOVA test of Between-Subjects Effects for Learning Group and Location.

Source Sum of Df Mean Fcomputed Fcritical p- Effect Squares Square value Size (2) Between 14049.689a Learning Group 2849.005 2 1424.502 8.088 F(2, 913) 0.000 0.016293 = 3.01 Location 5894.295 1 5894.295 33.466 F(1, 913) 0.000 0.033709 = 3.85 Learning 1588.669 2 794.335 4.510 F(6,913) 0.011 0.009086 Group*Location = 2.11 Within 160806.120 913 176.129 Corrected Total 174855.808 918 a squared = 0.060 Computed using alpha = 0.05

Table 40 shows the 2-way analysis of variance (ANOVA) with two between participant factors: learning group (passive, lecture and active) and location (Luzon and

Mindanao) and their effects on students’ gain scores. The main effect due to learning group is significant since the computed value 8.088 is greater than the critical value F(1,

913) = 3.01, and the p< 0.0005. This means there is evidence to support that learning group can improve students’ academic performance. Specifically, if we discount the location, the active group performed better than the other two learning groups.

Table 41 Learning Group Pairwise Comparison.

Learning Group Pair Mean Difference p-value (1-tailed) (Gain Scores) Active vs. Lecture 4.9207* 0.000 Active vs. Passive 7.2334* 0.000 Lecture vs. Passive 2.3127 0.067 *The mean difference is significant at the 0.05 level.

Post-Hoc Analysis (Tukey HSD) of pairwise comparisons (Table 41) shows that there is no significant difference between the lecture and the passive groups. However, the active group is significantly better than either the lecture or the passive group.

The Role of Knowledge Channel Television Shows on Students’ Learning 88

Hence, hypotheses 1 and 2 were substantiated by this result. This finding corroborates

Zhang et al.’s (2006) finding that students with interactive video that utilizes interaction performed significantly better than the students who belong to the non-interactive or passive group. This implies that simply using the technology in the classroom may not be enough to improve student’ achievement. Therefore, the teacher remains to be an important partner in the effective utilization of KC videos.

Moreover, there exists significant main effect due to location since the computed

F=33.466 > critical value F(1, 913)=3.85, p< 0.0005). A bigger percentage of students’ gain score is accounted for by this factor (effect size = 3.37%). This means that student participants in Luzon performed better than those in Mindanao.

The interaction effect of these two factors is significant (computed F-value = 4.510 is greater than the critical value F(6, 913) = 2.11, p< 0.011). This means that all effects due to learning group, location and their interaction - on gain scores are significant.

Thus, there is evidence to suggest that students’ gain scores due to learning group were moderated by the location.

Conclusion

Results obtained in this experimental research elucidated why students from three learning groups (Passive, Active, Lecture) had significantly different gains in terms of achievement scores. Specifically the following significant findings are advanced:

1. The mean gain scores for each of the learning groups yielded significantly

positive results, with posttest scores > pretest scores. Students in the Active

The Role of Knowledge Channel Television Shows on Students’ Learning 89

group had the highest gain score. Therefore the use of KC shows with teachers’

processing accounted for the 74.15% difference in the students’ posttest scores.

2. There are significant differences between the gain scores of the students in the

Active group and the gain scores of the students in either the Passive group or

the Lecture group. Results further revealed that the gain scores of the students in

the Passive group is comparable with the gain scores of the students in the

Lecture group.

3. There is enough evidence to support that learning group may account for

differences in students’ achievement.

The Role of Knowledge Channel Television Shows on Students’ Learning 90

Study 3 Students’ Attitude Towards KC Shows, Students’ Achievement and Teacher’s Ability to Integrate KC Shows

Methods

Research Design

Study 3 utilized a descriptive correlational design to investigate the relationship between students’ attitude towards knowledge channel shows and students’ achievement with the teachers’ ability to integrate channel shows as a mediating variable on students’ achievement.

Participants

The participants in study 3 comprised of 143 high school teachers across grade levels and disciplines and 950 high school students in 8 public schools in the Division of La Union (Table 42). During the conceptualization of study 3, the research team has identified the Division of La Union as the study setting since there were several public high schools in this division, which were recipients of Knowledge Channel (KC) shows package.

Table 42 Number of teacher participants by school.

Number of School Teachers Aringay NHS 14 Damortis NHS 18 Don Eulogio De Guzman Memorial NHS 19 President Elpidio Quirino NHS 18 Pugo Central NHS 19 Rosario Integrated School 17 Southern Naguilian NHS 19 Tubao NHS 19 Total 143

The Role of Knowledge Channel Television Shows on Students’ Learning 91

Efforts were made to equalize the number of teacher participants in the study, hence almost equivalent percentages of teachers in the four grade levels were chosen by the division Superintendent (Table 43). In terms of subject taught during observation, highest number of teacher participants were Araling Panlipunan teachers (n=29 teachers) and the least number were English teachers (n=17 teachers).

Table 43 Profile of teacher participants by grade level and subject taught.

Grade Level Frequency Percent Grade 7 39 27.3 Grade 8 36 25.2 Grade 9 32 22.4 Grade 10 36 25.2 Total 143 100 Subject Taught During Observation Frequency Percent Araling Panlipunan 29 20.28 English 17 11.89 Values Education 20 13.99 Filipino 24 16.78 Math 26 18.18 Science 27 18.88 Total 143 100

As indicated in Table 44, among the components of teachers’ ability to integrate KC shows in their lessons, the highest is content knowledge (3.35) using a scale of 1 to 4.

Table 44 Mean scores of the teachers’ ability to Integrate KC Shows.

Skills Mean Technological Knowledge (TK) 3.05 Pedagogical Knowledge (PK) 3.08 Content Knowledge (CK) 3.35

As can be seen from the profile of student respondents (Table 45) for study 3, each school and each grade level has similar number of students. Of the 950 student

The Role of Knowledge Channel Television Shows on Students’ Learning 92 respondents, the total number for each school ranges from 116-123 (12.1 % to 12.9%).

In terms of gender profile, 66% of the student respondents were females and only 34% were males, with ages ranging from 10 -18 years old.

Table 45 Student respondents’ profile by school, grade level, and age.

School Frequency Percent Aringay National High School 119 12.5 Damortis National High School 120 12.6 Don Eulogio de Guzman Mem. Natl High School 123 12.9 President Elpidio Quirino National High School 119 12.5 Pugo Central National High School 118 12.4 Rosario Integrated School 116 12.2 Southern Naguilian National High School 120 12.6 Tubao National High School 115 12.1 Grade Level Frequency Percent Grade 7 238 25.1 Grade 8 239 25.2 Grade 9 246 25.9 Grade 10 227 23.9 Age Frequency Percent 10 1 0.1 11 13 1.4 12 176 18.5 13 232 24.4 14 218 22.9 15 220 23.2 16 73 7.7 17 5 0.5 18 2 0.2

To find out the teachers’ ability to integrate knowledge channel shows in the lessons, 8 education supervisors from the Division of La Union observed the 143 teachers from November 3, 2014 to February 13, 2015.

The Role of Knowledge Channel Television Shows on Students’ Learning 93

Instruments

To gather pertinent data for study 3, three instruments were utilized in this study such as: (1)assessment package, (2) observation protocol (Teaching Observation

Protocol on Use of KC Shows–TOP-KCS), and (3) attitude checklist (Attitude Towards

Knowledge Channel Shows- ATKCS).

An assessment package was developed for grades 7-10 covering the subject areas in Science, Mathematics, Filipino, English, and Araling Panlipunan. The reliability of the test instruments was determined using Cronbach alpha.

Table 46 Reliability of achievement test instruments used.

Level Subject No. of items Cronbach's Alpha English 30 0.724 Science 25 0.774 Math 27 0.714 Filipino 30 0.734

Araling 30 0.772 Grade Grade 7 English 30 0.720 Science 25 0.768 Math 25 0.664 Filipino 30 0.706

Araling 30 0.623 Grade Grade 8 English 30 0.633 Science 25 0.847 Math 25 0.677 Filipino 30 0.825

Araling 30 0.638 Grade Grade 9 English 30 0.627

Science 25 0.675 Math 15 0.668 Filipino 30 0.701

Araling 30 0.721 Grade Grade 10

Teaching Observation Protocol on the Use of KC Shows –TOP-KCS is a 25-item observation checklist that is divided into three components such as teachers' technical,

The Role of Knowledge Channel Television Shows on Students’ Learning 94 pedagogical, and integration skills. This instrument was drawn from McGrath, Karabas

& Willis (2011) TPACK framework. The first part of the checklist aims to measure the teachers' technological knowledge in operating the video. The second part, the pedagogical knowledge, intends to measure the teachers' ability to elicit students' prior knowledge about the lesson prior to viewing knowledge channel shows, their ability to ask questions, developing students' critical thinking skills during and after the viewing of knowledge channel shows. The third part, content knowledge intends to assess the teachers’ mastery of learning content. TOP-KCS was designed by the research team and validated by two experts in the field. Revision of TOP-KCS was done according to the experts’ comments.

An attitude checklist, ATKCS, was also developed by the research team and validated by the two experts in the field. The instrument was revised following the expert’s comments. The checklist contains items that measure the components of attitude such as students’ feelings and attentiveness while watching KC shows, their perceived importance and usefulness of KC shows in understanding concepts in five subjects covered in this study and in the application of these KC shows to life, and their personal evaluation about their learning through KC shows.

Table 47 shows the indicator loadings and reliability coefficients of the variables under study such as students’ attitude towards KC shows and teachers’ ability to integrate KC shows in their lessons.

The Role of Knowledge Channel Television Shows on Students’ Learning 95

Table 47 Indicator loadings, average variance extracted, and reliability coefficients of the variables in the study.

Indicator/Item AVE Composite Cronbach's Loading Reliability Alpha A. Attitude .581 .890 .849 Feels happy while watching 0.574 KC shows in five subject areas Focused while watching KC 0.848 shows Learned many things from KC 0.855 shows in five subject areas KC shows helped remember 0.903 lessons in five subject areas Encouraged others to watch KC 0.656 shows KC shows are useful in 0.680 everyday life B. Teacher Achievement .840 .954 .936 Technological Knowledge 0.808 Pedagogical Knowledge 0.948 Content Knowledge 0.956 Combination of Technological, Pedagogical, and Content 0.946 Knowledge Note: All indicators/item loadings are statistically significant (p <.001)

Analysis of the results of the measurement model reveals that the loadings of the items for both attitude and teacher achievement constructs are statistically significant and greater than the 0.5 threshold (Hair et al., 1987 & 2009 cited in Kock, 2013); the average variance extracted (AVE) for each construct is greater than the .5 cut-off

(Fornell and Larker, 1981) and the composite reliability and Cronbach’s alpha are greater than the .7 cut-off (Fornell & Larcker, 1981; Nunnaly, 1978; Nunnally &

Bernstein, 1994), indicating that the constructs have convergent validity. Moreover, the square roots of the AVE (diagonal elements in Table 48) are larger than the correlations of the constructs (off-diagonal elements in the same table), indicating that each construct has discriminant validity based on Fornell & Larker (1981) criterion.

The Role of Knowledge Channel Television Shows on Students’ Learning 96

Table 48 Average Variance Extracted and correlation coefficients among constructs.

1 2

1. Attitude (0.917) -0.009

2. Teacher Achievement -0.009 (0.763) Note: Diagonal elements are the square root of AVE between constructs. For discriminant validity, the diagonal elements should be larger than the off-diagonal elements.

Procedure

LIDER sent a communication to the Schools Division Superintendent (SDS) of

DepEd La Union on August 8, 2014, indicating the list of recipient schools where study

3 would be conducted. Upon the approval of the Schools Division Superintendent

(SDS), the assessment package in five subject areas were administered to 950 student

respondents in eight schools in La Union.

To measure students’ ability to integrate KC shows in their lessons, LIDER

communicated with the KC coordinator and made arrangements with DepEd Division

supervisors in La Union to conduct observation of teacher respondents in eight schools

using TOP-KCS, an observation protocol designed by the research team. Prior to their

observation, the research team went to DepEd Division of La Union Office and oriented

the supervisors on the process of rating the teachers’ ability to integrate KC shows in

their lessons using TOP-KCS. They were also given a rubric aside from the observation

protocol sheet to calibrate their ratings. During the orientation, the research team found

out that the target respondents of 320 teachers was impossible to meet because many

teachers were newly hired in eight schools covered in the study. Hence, to get the

novice teachers to be matched with seasoned teachers trained by Knowledge Channel in

The Role of Knowledge Channel Television Shows on Students’ Learning 97 integrating KC shows in lesson presentation and discussion may not be feasible either because results may be biased and therefore not valid. Hence, the original question of identifying the significant difference between the achievements of teachers trained and those not trained in integrating KC shows in their lessons was not considered in this study. This is the reason why the target respondents of N= 320 was narrowed down to

143 trained teachers.

Supervisors’ observations of classes were completed in two months. Field researchers went with the supervisors to administer the attitude checklist, ATKCS, to the student respondents who took the assessment package test.

Data Analysis

Path Analysis was used to depict the hypothesized causal paths of variables in this study. Specifically, the Maximum Likelihood (ML) estimation method in AMOS was used to estimate the path coefficients. Maximum likelihood was preferred because of its ability to run simultaneous and iterative estimation of coefficients. Furthermore, the ML estimation accounts for disturbances or “error terms” caused by other exogenous variables.

The path model of this study was hypothesized such that teacher’s ability to integrate technology in teaching mediates the effect of students’ attitude towards technology on their academic achievement. Fig. 16 presents the hypothesized path of these variables.

The Role of Knowledge Channel Television Shows on Students’ Learning 98

Figure 16. Hypothesized path diagram of the effect of students’ attitude towards Knowledge Channel shows on their academic achievement.

Results

Teachers’ Performance

Using the classroom observation protocol, supervisors evaluated the teacher participants in terms of their proficiency skills. Proficiency skills in this study is described in terms of the following components: technological knowledge, pedagogical knowledge, and content knowledge. As can be gleaned from the Table 49, the teachers were highly rated. Teachers’ mean ratings ranged between 3.27-3.57, depicting very good performance. Out of a perfect score of 4, the highest rating was on

Content knowledge (3.57), then followed by technological knowledge (3.30) and pedagogical knowledge (3.27).

The Role of Knowledge Channel Television Shows on Students’ Learning 99

Table 49 Teachers' Mean Ratings in ability to integrate KC shows.

Teacher’s Proficiency Skills Mean Std. Dev. Technological Knowledge (TP1) The teacher has the necessary technical skills to use the video, 3.30 0.84 in terms of setting it up, pausing/resuming the video, and trouble shooting. Pedagogical Knowledge (TP2) The teacher has ability to Pre-viewing : activate prior knowledge effectively, motivates students, elicits predictions about the video; While watching: take note of portions in the video that elicit strong reactions from the students, elicits predictions and 3.27 0.43 inferences about specific portions in the video; Post-viewing: Asks specific questions/provides learning activities that require simple recall; understands of concepts presented in the video and to real life situations, analyze, evaluate, synthesize and create ideas; monitors students’ progress by giving feedback and scaffolding; Content Knowledge (TP3) The teacher was able to clearly explain/expound the topic, 3.57 0.54 correct students’ answers and answer student’s questions, clarify information in the videos.

Student’ Attitude towards KC shows

Students were asked to respond to a symmetric agree-disagree scale, where 1- strongly disagree, 2 – disagree, 3 – agree and 4 – strongly agree. A response of 3 or 4 would mean a positive attitude towards KC videos. The attitudinnaire would indicate whether - KC helps them to understand better their lessons, information in the videos are credible or factual, the material provide them knowledge, skills, values and inspiration, etc.

Generally, the students’ mean attitude rating ranges from 3.01 to 3.57, indicative of a positive attitude towards the KC videos. Table 50 presents the mean rating and standard deviation of each of the items in the attitudinnaire.

The Role of Knowledge Channel Television Shows on Students’ Learning 100

Table 50 Mean ratings of students’ attitude towards KC shows.

Mean SD At1 I believe that knowledge channel shows can help me 3.40 0.725 understand easily my lessons. At2 believe that the lessons discussed in knowledge channel shows are credible or based on facts because they were 3.39 0.918 prepared by experts in the fields. At3 I believe that knowledge channel shows can help me 3.37 0.771 appreciate lessons. At4 I believe that knowledge channel shows will provide me 3.57 0.764 knowledge. At5 I believe that knowledge channel shows will provide me 3.56 0.733 skilss. At6 I believe that knowledge channel shows will provide me 3.57 0.766 values. At7 I believe that knowledge channel shows will provide me 3.51 0.740 inspiration. At8 I feel sad when I miss watching knowledge channel shows*. 3.01 0.879 At9 I tell others to watch knowledge channel shows 3.38 0.703 *inversely coded

Students’ Achievement per Subject

The student participants of this study were administered an achievement test in five

subject areas. Fig. 17 shows the mean scores of these students in English, Math,

Science, Filipino, and Araling Panlipunan. As can be gleaned from the graph, students

garnered the highest score in Filipino (M=43.28) and lowest in Araling Panlipunan

(M=33.18).

The Role of Knowledge Channel Television Shows on Students’ Learning 101

Figure 17. Students’ achievement scores in the 5 subject areas.

The succeeding section elucidates whether the students’ attitude towards KC shows has an effect on their achievement scores. It also seeks to know if the ability of teachers to integrate KC shows in teaching mediates such effect.

Effect of Student’ Attitude towards KC Shows on Student Achievement

IBM®SPSS®AMOS version 6 was used in testing the path relationship hypothesized in this study employing the Maximum Likelihood estimation. The direct relationship between students’ attitude towards KC shows and students’ achievement was first conducted in order to establish the baseline estimates.

It was revealed that Attitude has a positive significant direct effect on students’ achievement (β=41.8unstandardized). The beta estimates suggest that a unit increase in students’ attitude would translate to a 41.804 units increase on students’ achievement scores.

The Role of Knowledge Channel Television Shows on Students’ Learning 102

Table 51 Estimates for the relationship between Students’ Attitude towards KC shows and Students’ Achievement when Teacher Performance is introduced as mediating variable.

Estimate Achievement Attitude 41.804 After Mediation Teacher Performance Attitude 0.053 Achievement Attitude 40.086 Achievement Teacher Performance 2.191

When teacher performance was introduced into the model, it was revealed that attitude has a positive effect on teacher performance (Table 51) . Teacher performance also returned a positive effect towards achievement. Further examination of other causal relationships in the path diagram revealed that Teacher’s Performance (TP) positively affects students’ achievement. Table 51 shows that every unit increase in the rating of teachers’ ability to integrate KC shows translates to about 2.2 units increase in students’ achievement. Figure 18 reveals the path diagram of the mediation model showing the estimates.

The Role of Knowledge Channel Television Shows on Students’ Learning 103

Figure 18. Path diagram when Teacher’s performance is introduced as a mediating variable on the relationship between students’ attitude towards KC shows and students’ achievement.

Conclusion

Analysis of quantitative data using the maximum likelihood (ML) estimation method of Path Analysis depicted causal paths of the variables in this study that led to the following conclusions:

1. The relatively high mean ratings of students’ attitude towards Knowledge

Channel shows indicate a positive attitude among the student respondents.

2. Students’ attitude towards KC shows has a significant direct positive effect on

students’ achievement.

The Role of Knowledge Channel Television Shows on Students’ Learning 104

3. The model revealed that teachers’ ability to integrate KC shows in instruction

partially mediate the effect of students’ attitude on achievement since students’

attitude remained to have a positive significant effect on students’ achievement

even after introducing the mediation variable.

The Role of Knowledge Channel Television Shows on Students’ Learning 105

Study 4 Teachers’ Lived Experiences in Integrating Knowledge Channel Videos in Instruction

Methods

Research Design

Study 4 is a qualitative research designed to describe the lived experiences of teachers in integrating Knowledge Channel videos in instruction. The study made use of a written questionnaire and focus group discussions (FGD) in obtaining data. Written questionnaire was used to profile the teacher participants and to determine how frequent the KC videos are viewed, how the the KC videos are used in the lesson, and how the

KC videos enhance the teaching and learning experience. Focus group discussions

(FGD) probed on the different teaching strategies and methods that the teachers employ when integrating KC videos into the lesson and how the teachers use KC videos in teaching. For qualitative content analysis of the data from the FGD, the framework method was used. This methodological approach examines the content of the FGD in order to derive meaning and particular implications for describing the lived experiences of the teachers. The approach involved identifying commonalities and differences in the qualitative data, before focusing on relationships between different parts of the data, thereby seeking to draw descriptive and/or explanatory conclusions clustered around themes.

The Role of Knowledge Channel Television Shows on Students’ Learning 106

Participants

Participants of study 4 included 30 teachers from three schools located in the three

major islands (Luzon, Visayas and Mindanao). Profile of the teacher participants is

presented in Figure 19.

Figure 19. Profile of teacher participants included in Study 4 (N=30).

As can be gleaned from Figure 19, 10 teachers each come from a school in Luzon,

Visayas and Mindanao. There are more female teachers (n=26) compared to their male

counterparts.

The Role of Knowledge Channel Television Shows on Students’ Learning 107

Instruments

The study made use of a written questionnaire and focus group discussions (FGD) in obtaining data. Written questionnaire was used to profile the teacher participants and to determine how frequent the KC videos are viewed, how the the KC videos are used in the lesson, and how the KC videos enhance the teaching and learning experience. Focus group discussions (FGD) probed on the different teaching strategies and methods that the teachers employ when integrating KC videos into the lesson and how the teachers use KC videos in teaching.

The written questionnaire has three parts: Teachers’ Profile, Showing Knowledge

Channel Shows in School, and Watching Knowledge Channel Shows Outside of

School. A total of 22 items were included in the questionnaire: 10 items for part 1, 8 items for part 2, and 4 items for part 3. Completion of the questionnaire lasted for about an hour. While focus group discussions were conducted to probe on the teachers’ beliefs, attitudes, feelings, experiences, and reactions (Gibbs, 1997). FGD was done thrice (once per loction) for about an hour using an FGD protocol. The FGD protocol

(i.e., 12 items) were aligned to the survey questionnaire. The FGDs were audio-recorded to preserve the actual and natural language and to record data with utmost objectivity and accuracy.

Procedure

Prior the actual data gathering, instruments were prepared, pilot tested and validated.

Letters of requests were sent to participating schools for the conduct of data gathering.

As soon as the schools principals approved the request, three groups of researchers were sent to the three different locations namely: Cavite, Iloilo and Siargao. Prior to actual

The Role of Knowledge Channel Television Shows on Students’ Learning 108 data-gathering, a briefing session was conducted to orient the participants about the rationale of the study. The participants were able to finish the survey within the allotted time. Thereafter, the FGD was conducted. Twelve questions were raised duing the FGD and it delved on teacher’s experiences related to integrating KC videos.

Data Analysis

For qualitative content analysis of the data from the FGD, the framework method was used. This methodological approach examines the content of the FGD in order to derive meaning and particular implications for describing the lived experiences of the teachers. The approach involved identifying commonalities and differences in the qualitative data, before focusing on relationships between different parts of the data, thereby seeking to draw descriptive and explanatory conclusions clustered around themes.

The qualitative responses of this study were analyzed using the 3E framework of technology-enhanced learning (TESEP, 2007). This framework consists of three broad iterative stages of learning transformation referred to as the “3E continuum” or simply

“continuum” in this study. Despite being iterative, it can be noted that each stage of the continuum represents an increasing level of learner ownership and control. Although the

3 stages can be seen as a continuum of change in teaching practice, they should not be viewed as mutually exclusive (TESEP, 2007). The analysis proceeded with these 3 stages set as primary categories in the coding process. The coding process was conducted utilizing MaxQDA10™.

The Role of Knowledge Channel Television Shows on Students’ Learning 109

Figure 20. Screenshot of the MaxQDA10 project illustrating the document, browser and code system.

Study 4 Results

As can be seen from Fig. 20, there were three documents loaded into the software for analysis. These are the transcripts of the FGDs conducted in Luzon (NAIC Coastal

National High School), Visayas (Janiuay Elementary School), and Mindanao (Don

Enrique Navarro Memorial School). The Code system window shows the preset categories Enhance, Extend, Empower. A new code was also introduced for the emerging codes that were deemed crucial in validating the analysis. It can be gleaned further that a total of 132 segments of the three transcripts were coded, where most of the codes are on describing the typical scenario of KC integration in teaching. The document browser shows the coded segments in the active transcript. The code summary is presented (Fig. 21).

The Role of Knowledge Channel Television Shows on Students’ Learning 110

Figure 21. Screenshot of the MaxQDA10 document browser showing the coded segments in the active transcript.

As can be noticed from Fig. 21, the empower code did not yield any coded segment in any of the three transcripts. This suggests that these codes did not emerge during the

FGDs. This led the researchers to further examine the teachers’ responses in the questionnaire.

The Role of Knowledge Channel Television Shows on Students’ Learning 111

Table 52 Summary of codes and the coder’s memos.

Code Source Memos Main Lesson – Introduction of the lesson is given in respective classrooms before going to the viewing room. Processing is conducted inside their respective classrooms. Mode: 20 minutes viewing time. Range 15-30 minutes viewing time. Enrichment – Supplementary material. Conducted as an activity (film viewing). Sometimes not in lesson plan of teacher. FGD Motivation Activity – Discussion is conducted Enhance Transcript and immediately. Students can relate to the video. Or a Questionnaire preview of main lesson. Students are really interested in viewing videos. Principal’s Role – Encourage/Require integration of KC shows Choosing topics. Not all topics of KC can be used. The teacher must pick only the suitable to the current topic. Technology is available but limited. Need to maximize the use of what are available. Extend Questionnaire Teachers give assignments based on KC Video. Descriptives Teachers assign projects emerging from the lesson and inspired by KC videos. Empower Questionnaire Teachers may give assignments which students Descriptives need to watch KC videos and other resources outside the school. Teachers tell the students to watch KC shows outside the school. Teachers tell students to watch other videos and materials outside the school. The purpose is for students to gain more knowledge. Effectiveness FGD Students score higher when aided with KC videos Transcript than in topics without KC videos. Students are excited to learn. Note that learners today are mostly visual learners. Teachers observed their students gain broader understanding. Issues FGD Schedule does not match with current topic. Transcript Interval with the next lesson is long. Pacing of students is also a problem. Some low performing students delay the lessons and the more that lessons do not match with KC. Only one viewing room. Recommendations FGD Coordinate well on schedule and topics. Add more Transcript topics and videos Add more TV sets (if possible one in every classroom) equipped with cable connection. Add internet connection too.

The Role of Knowledge Channel Television Shows on Students’ Learning 112

Enhance generally involves a straightforward and effective use of technology and structured peer support opportunities (Table 52). At this level, the students are viewed as being more actively involved in their learning experience and having greater degree of responsibility for their learning than traditional classroom lecture.

This study looked into the available learning technology in schools that facilitated technology integration and structured peer learning. The questionnaire part of this study revealed that desktop computer is the most prevailing technology where 83% (n=25) of the teacher respondents reported to have been using in classroom teaching. This is followed by television set (TV) at 80% and CD and DVD players at 60%. Other learning technologies that teachers use in classroom teaching include cellphones (56%) and tablets (24%). It is noteworthy to mention that despite having computer and TV sets in classrooms, only few of these facilities are hooked to the internet and cable connection.

The teacher respondents in this study were also probed on the various learning activities they introduce in classroom teaching which are aided by the Knowledge

Channel (KC) shows. It was found out that KC shows are primarily used for activities identified at the “enhance” level of the 3E continuum. These activities include using KC shows as both an opening activity for the lesson or as the main lesson. When asked on which part of the classroom teaching the video is shown, survey revealed that majority

(62%) of the teacher respondents shows the videos in the middle of a classroom discussion. The teachers were probed further on the specific activities introduced together with the KC shows. Teachers were asked how frequently they ask questions about the topic before showing the video, pause the video and clarify some concepts,

The Role of Knowledge Channel Television Shows on Students’ Learning 113 ask questions to check their comprehension, conduct post-viewing discussion, and assign group activities based on the video shown. It was found out that although they acknowledged that at some point they introduced these activities to supplement the content of the KC shows, the frequency of doing so is very seldom. Given the scale of 1 to 4 to examine the frequency of introducing these activities, where 1 represents “not even once” and 4 represents “very frequent”, the teachers rated these activities at an average ranging from 1.5 to 1.96 signifying that they seldom introduce these activities.

Teachers were probed further on the typical scenarios that the KC shows were utilized in teaching. It was revealed that the lesson is being introduced by the teacher in their respective classrooms while they queue for the KC schedule. The teacher then brings his class to the KC viewing room on the timeslot of the specific KC video to watch, and back to their classroom for post-viewing processing. Teachers reported that they conduct post-viewing processing in order to discuss thoroughly the concepts in the video. “Most of the times after viewing, we use the video as a point of discussion”. The time allotted to discuss the content of the KC shows ranges from 15 to 30 minutes, with

50% of the respondents declared doing it in an average of 20 minutes. This signifies that teachers give an ample time to process the video in order to build and develop the content lesson at hand. This is indicative that the teachers are cognizant of their crucial role in a technology-enhanced learning activity.

There are some teachers who declared having obtained copies of specific KC videos in CDs and DVDs. When these teachers use the KC shows as the main lesson, they employ the “pause-play” technique, where they pause the video for a while to throw questions, and emphasize the important concepts.

The Role of Knowledge Channel Television Shows on Students’ Learning 114

In order to maximize the utility of the available learning technologies in schools, this study sought to know how the school principals encourage their teachers to integrate technology in their teaching. It was revealed by the 72% (n=22) of the respondents that their respective school principals require them to integrate KC shows in their lessons. It was further found out that 59% (n=18) were required by the principal to include viewing of KC shows in their lesson plan. Further examination during focus group discussions revealed that the teacher respondents from Visayas and Mindanao schools were the ones required by their principals to include viewing of KC shows in their teaching.

Extend engages the students in collaborative or individual tasks which offer new opportunities to extend the classroom activities in ways that provide choice and control in what, when, and how students learn. At the extend level, students move from an active to pro-active modes which require them to make some key decisions about the activities they undertake.

The activities that the teacher respondents indicated in this study that extend the classroom learning encounter included assignments and projects. Again, although they acknowledged that at some point they have given assignments and projects related to or based on the KC shows, they seldom do so. Given the scale of 1 to 4 where 4 represents

“very frequent” and 1 “not even once”, it was found out that teachers rated both “giving assignments” and “assigning projects” at an average of 2.38 (seldom). The questionnaire part of this study further revealed that respondents from Luzon give assignments more frequently than those from Visayas and Mindanao. On the other hand,

The Role of Knowledge Channel Television Shows on Students’ Learning 115 respondents from Visayas assign projects more often than those from Luzon and

Mindanao.

Empower drives the students to seek learning independently. This stage of the continuum represents that “ideal” technology-enhanced learning where students take full control of their learning.

In terms of empowering the students to seek learning independently, this study simply looked into how the teachers moved their students to watch videos and seek other resources to further enhance their learning. It was found out that what the teachers did to encourage independent learning was simply to pose assignment questions at the end of the discussion. Teachers encourage their students to answer the questions by watching other KC videos and other related materials that could help them answer the question. All the teacher respondents declared that they instruct their students to watch

KC videos and other related materials outside the school. When probed on their reasons for doing so, the most common answer was - for students to gain more knowledge about the topic from “other sources”. This strategy is apparently inclined towards empowering the students to exercise responsibility and control of their own learning endeavor. The fact that questions were given as an assignment, teachers may be able to monitor the learning progress of his students. This suggests that a mechanism to monitor students’ progress in independent learning may be adapted.

Implementation Issues

This study also investigated the various issues that the teachers encountered in implementing KC integration in teaching. Common among the responses is the timing and scheduling of KC shows. Recalling the typical scenario where KC shows are

The Role of Knowledge Channel Television Shows on Students’ Learning 116 integrated in teaching, the teachers have to queue their classes for the timeslot of the specific video they need to watch. This entails adjusting to the schedule of the KC shows. While it may work for some, most of the teachers find this difficult because most of the times, the scheduled KC shows do not coincide with the topic at hand. One teacher disclosed “Halimbawa, iba yung topic kapag ipapadala mo sila sa knowledge channel (viewing room)… hindi po magkatugma” (For example- the topic at the

Knowledge Channel (viewing room) does not coincide with topic (in class)). In some cases, teachers simply bring their class to the viewing room and discuss whatever video is being shown. “Kung ano man yung pinanonood namin, yun yung ididiscuss namin”

(we just discuss whatever video is being shown). Some teachers have to swap schedules with other teachers in order to catch the scheduled KC shows. “Ginagawa po namin is hinihiram po namin yung time nang ibang guro para sa viewing maam tapos kinabukasan yung time namin ang gamitin nila” (What we do is we exchange class schedule with our co-teachers for our KC viewing). Other teachers have to skip some topics in order to catch the schedule KC shows. It was also revealed that the teachers are not receiving regularly the KC schedule of shows. “Dati po nagkocoincide yung topic at alam namin ang I view for the whole semester” (Before the topics coincide and we know what (videos) to view for the whole semester). Hence, they cannot determine when to bring their classes to the KC viewing room. These scenarios are deemed significant contributory factors why teachers seldom integrate the KC shows in their teaching. However, it is also important to note that the pacing of lessons is another problem. There are instances that despite having a schedule of KC shows, some topics lag behind as teachers have to teach the topic again for the low-performing students.

“Depende po sa IQ nang mga bata kasi minsan kailangan namin e reteach yung

The Role of Knowledge Channel Television Shows on Students’ Learning 117 lesson” (It depends on the students’ IQ because sometimes we need to reteach the lesson).

However, despite these issues, teacher respondents declared that they are convinced that integrating KC shows in the curriculum effectively enhances learning. Given a scale of 1 to 5 where 5 represents the highest perceived effectiveness of KC shows in helping students learn the lessons, results revealed that all teachers gave a rating of 4.

When probed further, these answers are based on teachers’ observation of their students’ scores during examinations. It was revealed that students score higher when

KC shows are integrated compared to classes/topics without KC shows. “After nila nanood nagbigay ako nang quiz then nakakuha sila nang matataas na score compare yung nag lecture lang ako ng lecture” (When I give a quiz after viewing KC videos, the students get higher scores than when I just give a lecture”. Some teachers are even surprised to see that their students are able to answer even the seemingly difficult questions. “Yung hindi mo na expect na makakuha sila nang tama o makasagot sila”

(that times when you do not expect your students to get the right answer).

Teacher respondents were then asked what they can recommend to improve the implementation of the integration of KC shows in teaching. Apparently, all teachers recommended that the schedule for the entire school year be set. Further, the teachers must be informed of this schedule so they can also plot their classes based on the given

KC schedule. Moreover, teachers also recommended that the cable subscription and access to KC shows be brought to their individual classrooms so they need not queue at the viewing room and students need not transfer from their respective classrooms to the viewing room.

The Role of Knowledge Channel Television Shows on Students’ Learning 118

Conclusion

The use of the 3E framework of technology integration in interpreting and analyzing the lived experiences of teachers was found to be appropriate. Reflecting carefully on these lived experiences, it can be deduced that the teachers’ techniques in integrating

Knowledge Channel videos fall primarily within the enhance level of the 3E continuum.

This suggests that teacher training is needed to further develop their pedagogy in integrating technology in order to achieve the stage where students are self-motivated to learn. Following the social constructivist lens of the framework, results of this study maintain that teachers must be cognizant of their primary role as facilitators of learning.

Through the lived experiences of the teacher participants, the social constructivist roles of teachers at the enhance level is recognized. There are some activities that the teachers employ in teaching that are reflective of the extend level of technology integration. The empower level manifests in the process of giving assignment questions which calls for students to watch other KC shows and related learning materials.

The Role of Knowledge Channel Television Shows on Students’ Learning 119

References

Adoguzel & Timcin, 2010. The effect of creative drama on student achievement in the instruction of some development and learning theories. Procedia Social and Behavioral Sciences 9 (2010) 1741–1746. Aliasgari, Riahinia, Mojdehavar, (2010) "Computer‐assisted instruction and student attitudes towards learning mathematics",Education, Business and Society: Contemporary Middle Eastern Issues, Vol. 3 Iss: 1, pp.6 – 14. Amelink, C (2009). Gender Differences in Math Performance. SWE-AWE CASEE Overviews. Retrieved from http://www.AWEonline.org. Anderson, D. R., Huston, A. C., Schmitt, K.L., Linebarger, D.L., & Wright, J.C. (2001). Early childhood television viewing and adolescent behavior: The recontact study. Monographs of the Society for Research in Child Development, 66 (1), vii-147. Ayers JB (1972). Elementary Teachers’ Attitudes towards Instructional Television. The Journal of Experimental Education. Taylor & Francis, Ltd. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182. Bryant, J., Mullikin, L., McCollum, J., Ralastin, L., Raney, A., Miron, D., Thompson, S., Stuart, Y., Mundorf, N., Mundorf, J., Wilson, B., and Smith, S. (1998). Effects of one year’s viewing of Blues Clues. Tuscaloosa, AL: Institute for Communication Research, The University of Alabama. Baydar, N., Kagitcibasi, C., Kuntay, A., & Goksen, F. (2008). Journal of Applied Developmental Psychology, 29, 349-360. Chen, M., & Hodder, L. (1997). A research overview of FASE productions' TV series on science, mathematics, and technology education. Unpublished manuscript. Christakis, D.A. et al.. “Early Television Exposure and Subsequent Attentional Problems in Children,” Pediatrics 113 (2004): 708–13. Cruz, M. (August, 2012). Children’s TV Act given ‘real teeth’ with IRR. Philippine Daily Inquirer. Eckenrod, J, Rockman, S. (1988). Connections between Television and the Social Studies Curriculum. Social Education, v52 n5 p357-62 Sep 1988. Foundation for Advancements in Science and Education (1997). Classroom television: A useful resource for mathematics and science education. Evaluation of The Eddie Files. Los Angeles: FASE. Gardner, H. (1985). The Mind’s New Science: A History of the Cognitive Revolution. New York, NY; Basic Books Publishing. Harwood, W.S. McMahon, M.M. (1997). Effects of Integrated Video Media on Student Achievement and Attitudes in High School Chemistry. Journal of Research in Science Teaching,34 (6), 617–631. Hattie, J. (2011) Ranking: Influences and Effect Sizes Related To Student Achievement. Visible Learning for Teachers: Maximizing Impact on Learning. ISBN- 13: 8601401316398 ISBN-10: 0415690153 Edition: 1st Hendry , D. Instructional Television's Changing Role in the Classroom. The Technology Source, May/June 2001.

The Role of Knowledge Channel Television Shows on Students’ Learning 120

Hofer, M; Grandgenett, N; Harris, J..; and Swan, K. (2011). , "Testing a TPACK-Based Technology Integration Observation Instrument". Teacher Education Faculty Proceedings & Presentations. Paper 19. Kaya, Z., Kaya, O., Emre, I. (2013) Adaptation of Technological Pedagogical Content Knowledge Scale to Turkish Educational Sciences: Theory and Practice, v13 n4 p2367-2377 Koehler, M. J., & Mishra, P. (2008). Introducing TPCK. In J. A. Colbert, K. E. Boyd, K. A. Clark, S. Guan, J. B. Harris, M. A. Kelly & A. D. Thompson (Eds.), Handbook of Technological Pedagogical Content Knowledge for Educators (pp. 1– 29). New York: Routledge. Knowledge Channel Foundation, Inc. (2009). Knowledge Channel Foundation, Inc.: an overview. Retrieved from https://www.ammado.com/nonprofit/48611/articles/8868 Linebarger, D. L.,Kosanic, A.Z.,& Greenwood, C.R. (2004). Effects of viewing the television program Between the Lions on the emergent literacy skills of young children. Journal of Educational Psychology, 96(2), 297-308. Mapa, D. (2007). Impact Evaluation of the Programs of Knowledge Channel on the Performance of the Schools in the National Achievement Test (NAT). Final Report.UP Statistical Research Foundation, Inc. Mapa, D. (2009). Proficient Measures for Quality Education (PMQE). Final Report.UP Statistical Research Foundation, Inc. Marshall, J. (2002) Learning with Technology Evidence that technology can, and does, support learning. San Diego State University. Mishra, P and Koehler, M. (2006). Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge. Michigan State University. Moeller, B. (1996). Learning from television: A research review (Reports Issue No.11). Center for Computation and Technology.Nielsen Report on Television . Northbrook, IL: A.C. Nielson Co. Nicolaidou, M. and Philippou, G. 1999. Attitudes towards mathematics , self-efficacy and achievement in problem-solving. Retrieved from www.dm.unipi.it/~didattica/CERME3/proceedings/Groups/TG2/TG2_ nicolaidou_cerme3.pdf Pelletier, J. (2011). The effects of educational television viewing in an early childhood family literacy intervention. Retrieved from http://www.tvo.org/learnwithtvo/resources/PelletierTVO.pdf. Rhema, A., and Miliszewska, I. (2012). “The potential of e-learning in assisting post- crisis countries in re-building their higher education systems: the case of Libya,” Issues in informing Science and information technology, 2012, vol. 9, pp. 149-160. Register, D. (2004).The effects of live music groups versus an educational children’s television program on the emergent literacy of young children. Journal of Music Therapy, 41, 2. Savenye, Wilhelmina, Davidson, and Smith. (1991). "Teaching Instructional Design in a Computer Literacy Course." Educational Technology Research and Development, 39(3), 49-58. Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (tpack): The development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 123-149.

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Schmidt, M E and Anderson, D (2007) “The Impact of Television on Cognitive Development and Educational Achievement” in Children and Television: Fifty Years of Research, Norma Pecora, John P. Murray, and Ellen Ann Wartella, eds., Mahwah, NJ: Lawrence Erlbaum, pp. 65-84 Seels, B., Fullerton, B., Berry, L., & Horn, L. (2008).Research on learning from television. Retrieved from http:///www.coe.csusb.edu/faculty/newberry/classes/archive/fall2008 Shoemaker, A. (2011). Do educational TV programs have positive effects on children learning? Online [Available] http://www.associatedcontent.com/shared.shtml?content_type=article&content_type _id=5630635 Skolnik, R., & Smith, C. (1993, February). Educational technology: Redefining the American classroom. Network News and Views, 12 (3), 79-83. TESEP. (2007). TESEP in Practice: The 3E Approach. Retrieved from Edinburg Napier University Transforming and Enhancing the Student Experience through Pedagogy: Retrieved from: http://www2.napier.ac.uk/transform/TESEP_3E_Approach.pdf Tips for Using Instructional Video and Public Television Programming in the Classroom. The Technology Source Archives at the University of North Carolina. Retrieved from http://www.thirteen.org/edonline/ntti/formanagers/02Media.pdf on February 2015. Wentzel, K. (1988). Gender differences in Math and English Achievement: A longitudinal study. Sex Roles, 18(11-12), 691-701. Wilson, B.J., Linz, D., Federman, J., Smith, S., Paul, B., Nathanson, A., Donnerstein, E., and Lingsweiler, R. (1999). The Choices and Consequences evaluation: A study of Court T V’s anti-violence curriculum. Santa Barbara : University of California, Santa Barbara, Center for Communication and Social Policy Wright, J.C., Huston, A.C., and Kotler, J. (2001). Chapter 6, The early window project: Sesame Street prepares children for school. In S.M. Fisch and R.T. Truglio (Eds.), “G” is for growing: Thirty years of research on children and Sesame Street ( p p. 97– 114). Hillsdale, NJ: Erlbaum. Yates, Bradford L. "Modeling Strategies for Prosocial Television: A Review". Paper presented to the Open Paper Competition, AEJMC Southeast Colloquium; Lexington, KY, 4–6 March 1999. Zhang, D., Zhou, L., Briggs, R., &Nunamaker, J. (2006). Instructional video in e- learning: Assessing the impact of interactive video on learning effectives. Information & Management, 43, 15-27.