Journal of Applied Global Research

ISSN 1940-1833 Journal of Applied Global Research

Volume 7, Issue 20

Published and Sponsored by: Intellectbase International Consortium

Volume 7, Issue 20

Editor-in-Chief Dr. David King, Tennessee State University, USA

Dr. David King holds a Ph.D in Computer Information Systems and over 14 years experience in Applied Research. He is also a Certified Cisco Systems Instructor, Microsoft Certified Professional, Certified Novell Administrator and has recently achieved Diplomas in Medical & Dental and Pharmacy academic programs. Dr. King’s educational background expands across Australia, Europe, Africa and North America. He is keen in teaching Networking Systems, Computer Systems Security, Applied Information Technology, Relational Database Management Systems, Management Information Systems, E-business strategies, Knowledge Management, Data Mining, Artificial Intelligence, Business Process Reengineering and ERP Application Systems.

Dr. King’s research work is in the areas of: Computer-Mediated-Communication, The Internet and Psychology, E-Learning and Distance Education, The Internet and Global Collaboration, Foreign Aid Projects in Developing Nations, Accounting Information Systems, Knowledge Management, Intelligence & Homeland Security Systems, Health Information Science & Management, Research Methods and Design. He has published in several top Information Systems Conference Proceedings and Journals (IFIP, ACIS, PACIS, IRMA, JAGR, JISTP, etc.). In addition, Dr King serves on several editorial boards in the research community. He has received several research presentation “Best Paper” awards in Seattle, USA, Bangalore, India, Las Vegas, USA, and Venice, Italy. As new research disciplines develop, Dr. King expands his horizons, investigates, experiments and contributes to intellectual consortiums and forums. He serves as the Chair for the Intellectbase International Consortium conferences and leads the Editors Excellence Review Panel (EERP) for the International Handbook of Academic Research & Teaching (IHART) Proceedings. In addition, he currently serves as the Program Coordinator for International Institute of Academic Research.

Contributing Editors Dr. Stephen Kariuki Mr. Kristopher Burris, Managing Editor Dr. Kong-Cheng Wong Associate Editor-in-Chief Intellectbase International Consortium Associate Editor-in-Chief Nipissing University, Canada USA Affiliate Governors State University, USA

Senior Advisory Board Dr. Brett Sims, Associate Editor Dr. Jeanne Kuhler, Associate Editor Dr. Frank Cheng, Associate Editor Borough of Manhattan Community College, USA Auburn University, USA Central Michigan University, USA

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Reviewers Task Panel and Executive Editorial Board

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Reviewers Task Panel and Executive Editorial Board (Continued)

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Reviewers Task Panel and Executive Editorial Board (Continued)

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Dr. Siva Somasundaram Dr. Medha Talpade University of Houston-Victoria, USA Clark Atlanta University, USA Dr. Tiffany Jordan Prof. Lana Brackett Nova University, USA Roger Williams University, USA Dr. M. N. Tripathi Dr. Kelly Waters Xavier Institute of Management – Bhubaneswar, India University of South Carolina Upstate, USA Dr. Marcia Lamkin Dr. Mark Crowley University of North Florida, USA Bridgewater State College, USA Dr. Jason Caudill Dr. Vojko Potocan Carson-Newman College, USA University of Maribor, Slovenia Dr. Yuxia Zhao Dr. Carrie Hurst Shandong Administration Institute, China Tennessee State University, USA Mr. Jesse Cox Dr. Richard Douglass Metropolitan State College of Denver, USA Eastern Michigan University, USA and Ashesi University, Ghana

The Journal of Applied Global Research (JAGR) is published semi-annually by Intellectbase International Consortium (IIC). The goal of the Journal of Applied Global Research (JAGR) is to provide relevant information to the business, government, and academic communities by helping to promote the interdisciplinary exchange of ideas on a global scale. Articles published in this Journal do not necessarily represent the opinions of Intellectbase International Consortium (IIC) or any of the editors or reviewers. JAGR is listed in Cabell’s Directory EBSCOhost Digital Database, ProQuest, Ulrich’s Directory, JournalSeek and Intexed and archived at the US Library of Congress. In addition, JAGR is in the process to be listed in the following databases: ABI Inform, CINAHL, ERIC, EconLit, ACADEMIC JOURNALS DATABASE, ABDC.

TABLE OF CONTENT

A SIMPLE MATLAB CODE TO CALCULATE LYAPUNOV EXPONENT FOR DISCRETE MAPS Temesgen Kebede ...... 1

REAL-TIME PROACTIVE MAINTENANCE APPROACH USING STATISTICAL PROCESS CONTROL TECHNIQUE Chulsoon Park and Changkyung Kim ...... 6

TEACHING BUSINESS STUDENTS MOBILE APPLICATION DEVELOPMENT Degan Kettles ...... 19

PROKARYOTIC COMMUNITY ANALYSIS IN A SUBTROPICAL COASTAL PLAIN RIVER: DO ARCHAEA AND BACTERIA RESPOND TO SAME SIGNALS? Dmitri Sobolev ...... 34

IMPACT OF INTERACTIVE GAMES ON INTRINSIC AND EXTRINSIC MOTIVATION, ACHIEVEMENT, AND SATISFACTION Yun Huang and Jianjun Yin ...... 45

VIRTUAL COMMUNICATION IN BUSINESS V. Joy Rose ...... 56

ECOTOXICOLOGICAL USE OF TERRESTRIAL, FRESHWATER, AND MARINE ORGANISMS TO QUICKLY DETECT POLLUTION AND EVALUATE REMEDIATION EFFORTS OF DIESEL CONTAMINATION Tatiana Tatum Parker and Rebecca Rosenthal ...... 68

Temesgen Kebede JAGR - Volume 7, Issue 20 (2014), pp. 1-5

Full Article Available Online at: Intellectbase and EBSCOhost │ JAGR is indexed with Cabell’s, JournalSeek, etc.

JOURNAL OF APPLIED GLOBAL RESEARCH

A SIMPLE MATLAB CODE TO CALCULATE LYAPUNOV EXPONENT FOR DISCRETE MAPS

Temesgen Kebede Clark Atlanta University

ABSTRACT compact MATLAB code for the calculation of the Lyapunov Exponent (LE) of a general discrete map is given and the code applied to the particular case of the logistic map. The variation of the LE as a function of the mu-parameter of Athe map is plotted and the parameter values for which the LE is positive and the motion goes chaotic noted and compared with the expectation from the trajectory graph.

Keywords: Lyapunov Exponent, Discrete Map, Logistic Map, Exponential Divergence.

INTRODUCTION The signs of the LE indicate the chaotic or non-chaotic behaviors of a discrete dynamical system. When positive, neighboring trajectories diverge exponentially from each other and hence the motion is highly sensitive to initial conditions, which is the marc of chaotic behavior. Similarly, when negative, neighboring trajectories converge exponentially. It is to be noted that the use of LE s is by no means restricted to discrete dynamical systems. Lyapunov exponents can also be computed for continuous dynamical systems via their Poincare Maps. The intersection points of the continuous trajectory of a dynamical system in Rn with a convenient (n-1)-dimensional surface constitute a set of infinite discrete points which can be modeled by a discrete map which is referred to as the Poincare map of the continuous dynamical system. The LE of the continuous dynamical system is then by definition that of the associated Poincare map.

 0 Given two initial seed points x0 and x0   0 separated by an infinitesimal parameter , let  the separation of the nth iterates of the two initial seed points be denoted by n . The LE of an x  f (n) (x ) iterated map n1 0 is defined as follows:

A Simple MATLAB Code to Calculate Lyapunov Exponent for Discrete Maps

x x Though in general lambda depends on the initial seed point 0 , for 0 that originates from the basin of attraction, lambda is the same after taking the long iteration limit n  .

GENERAL DESCRIPTION: Below is presented a compact MATLAB code as it applies to the logistic map. The same code can be applied to any 1-dimensional discrete map by changing the expression for the derivative of the discrete map. The running time for the program is calculable by sandwiching the body of the code between the “tic” and “toc” MATLAB commands. The elapsed running time (approximately 91 seconds in this instance on a Dell Laptop) pops up in the command window at the end of the run. The range of mu-values in that range from 2.8 to 4.0 in steps of 0.0001are experimented on. Similarly, the initial seed point is picked by the random number generator from the unit interval [0, 1]. After ten thousand iterations of the discrete map are done, the first 300 are rejected and the rest used to calculate the average value of the quantity ln (1 2x ) i .This is because the first 300 iterations are enough to guarantee that that the transients have died away.

RESULTS: Following the MATLAB code is the graph of the LE as a function of the mu-parameter. The set of mu-parameter values for which the LE is negative correspond to stable fixed points, super stable fixed points or stable periodic orbits in the trajectory graph. The deep negative spikes occur where the trajectory graph indicates 2n –periodic orbits. The mu-value where the LE attains its first positive value (approximately 3.57) signals the first onset of chaos and agrees with the expectation from the trajectory graph.

Temesgen Kebede JAGR - Volume 7, Issue 20 (2014), pp. 1-5

MATLAB CODE:

A Simple MATLAB Code to Calculate Lyapunov Exponent for Discrete Maps

-1

-2

Lyapunov-Exponent -3

-4

-5 2.6 2.8 3 3.2 3.4 3.6 3.8 4 mu-Parameter

ANALYSIS AND DISCUSSION: The paper takes the logistic map as a prototype 1-dimensional discrete map and applies the MATLAB code solely to this map. On the other hand, the same code can be applied to other 1- dimensional discrete maps and there are many 1-dimensional discrete maps with fascinating properties. The only issue that can be raised is computation time. If the discrete map is a non- algebraic map, say one of the transcendental elementary functions, the time interval between tic & toc across the entire program body is definitely going to be longer. The logistic map is polynomial (hence algebraic) and the tic-toc time is, as stated in the general description almost 91 seconds.

LIMITATIONS AND SUGGESTIONS In addition to the computing resource issue raised in the analysis and discussion paragraph within the restricted context of 1-dimensional maps, discrete maps can also be 2, 3, in general n- dimensional. In this case an entirely different code has to be written to accommodate each component map along each dimension. The system parameters will in general be n- dimensional vectors and the LE s vector valued functions of the system parameter vectors. In a future conference, the author will present progress report for at least 2 and 3 dimensional discrete maps. The case of computing the LE s for continuous dynamical systems and higher

Temesgen Kebede JAGR - Volume 7, Issue 20 (2014), pp. 1-5 dimensional discrete maps is a source of great advanced undergraduate and graduate thesis project.

CONCLUSION Save for resource limitation, computer-experiment projects like the one detailed in this short paper can have interesting generalizations and offshoots that have great theoretical and practical values. A documentation of the LE s for a dynamical system as a function of its system parameters is a significant and handy detail on the behavior of the dynamical system, in that one then knows for what set of parameters the system is chaotic or regular. In addition to this clearly useful application, the result can spawn mathematical conjunctures or falsify or affirm existing ones.

BIBLIOGRAPHY Strogatz,S. (1994) Non-Linear Dynamics and Chaos with Application to Physics, Biology, Chemistry, and Engineering (Addison-Wesley Publishing Company) Lindfield,G.& Penny, J. (2012) Numerical Methods Using MATLAB, 3rd Edition (Elsevier Science & Technology) Hanselman, D.& Littlefield, B. (1996) Mastering MATLAB, A Comprehensive Tutorial and Reference (Prentice Hall, Inc. Upper Saddle River, New Jersey 07458) Baker,G.L. & Gollub,J.P. (1996) Chaotic Dynamics, An Introduction,2nd Edition (Cambridge University Press) Schuster,H.G. & Just, W. (2005) Deterministic Chaos: An Introduction, 4th Edition (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)

Chulsoon Park and Changkyung Kim JAGR - Volume 7, Issue 20 (2014), pp. 6-18

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JOURNAL OF APPLIED GLOBAL RESEARCH

REAL-TIME PROACTIVE MAINTENANCE APPROACH USING STATISTICAL PROCESS CONTROL TECHNIQUE

Chulsoon Park and Changkyung Kim Changwon National University, Korea

ABSTRACT n this research, we propose a proactive maintenance approach using the statistical process control technique with the real-time operating data of process parameters. At first, we identified parts of injection molding machine which are Irequired for maintenance and process parameters which may be affected by mal-functioning of the identified machine parts. Second, we used regression analysis to select the process parameters which significantly affect the quality of the products and, therefore, need to be received attention for maintenance. Third, based on the statistical analysis, we developed the prediction models of the selected process parameters of injection molding, which are identified by previous statistical model to forecast its future patterns/trends and schedule its maintenance point in time. We adopted Nelson’s rules to detect abnormal patterns in both of monitored and predicted data. Finally, we used fault tree to find out the mal-functioning parts, and then finally find out the equipment or parts to be corrected.

Keywords: Proactive Maintenance, Statistical Process Control, Statistical Analysis, Nelson Rules

BACKGROUND As the companies want to be competitive in the market, they are performing a lot of efforts to increase the efficiency of production, which is partially achieved by decreasing unplanned operation stops, and their product quality. The competitiveness of production systems was known to be also affected by their maintenance procedure as well as design and operation of maintenance (Blischke et al, 2003). More than 30% of the maintenance cost was known to be caused by misplaced maintenance schedule which involve unnecessary production cost (Salonen and Deleryd, 2011). Specially, in the injection molding production line, unexpected stops may cause the waste of expensive raw material which is resulting from purging work that pushes the remained raw material out of screw. Therefore, the companies were more getting interested in scheduling of maintenance planning to keep smooth operation and prevent undesirable situation.

Real-Time Proactive Maintenance Approach Using Statistical Process Control Technique

Maintenance is defined as restoring the systems or products to desired operational status or taking all the available measures to keep them in desired operational status (Blanchard et al, 1995). Generally, maintenance can be classified into three categories such as corrective, preventive and predictive maintenance (Blanchard et al, 1995, Dhillon and Liu, 2006). First, corrective maintenance is defined as restoring equipment or parts of them to operational status when the systems are out of order or parts of them are malfunctioning. That is, corrective maintenance may cause high risk in maintenance scheduling and performing because it does not consider adequate maintenance moment unlike preventive or predictive maintenance (Blischke et al, 2003, Campbell and Jardine, 2001). Second, preventive maintenance is defined as scheduling all the planned maintenance activities to prevent malfunction or failure and keeping them in desired operational conditions. Finally, predictive maintenance attempts to evaluate the condition of equipment by performing periodic or continuous real-time equipment condition monitoring. The ultimate goal of predictive maintenance is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold. The predictive component of predictive maintenance stems from the goal of predicting the future trend of the equipment’s condition. The predictive maintenance is getting more interests than the routine maintenance which is performed when machine fault occurs. The predictive maintenance techniques help determining the condition of in-service equipment or systems in order to predict when maintenance should be performed (Wikipedia, 2013). The predictive maintenance is to allow convenient scheduling of corrective actions, and to prevent unexpected equipment stops. The key is the right information at the right time. By knowing which equipment or parts needs maintenance, maintenance work can be better planned and what would have been unplanned stops are transformed to shorter and fewer planned stops, thus increasing equipment availability. This approach usually uses principles of statistical process control to determine at what point in the future maintenance activities will be appropriate. To evaluate equipment condition, predictive maintenance utilizes nondestructive testing such as sensor, vibration, sound level analysis and other real-time tests. That is, predictive maintenance includes procedure that monitors information about the machine status and plan maintenance schedule (Niebel, 1994).

The operation stops and maintenance cost are known to be significantly decreased by adopting exact maintenance strategy (Pintelon and Pinjala, 2006). As the corrective maintenance approach is generally adopted in the real world field, it is accompanied by sudden operation stops and additional cost by causing other parts affected from sudden stops. Practically, it is impossible to prevent malfunctioning of machines. Furthermore, this approach requires long-term or continuous monitoring and, it cannot cover all of the machines or parts of them which require maintenance. That is, status monitoring method through visual inspection is considered as standard and mostly adopted by companies, but, practically there are lots of cases which cannot be covered with sensors or X-ray to detect machine’s degree of degeneracy.

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Therefore, in this paper we propose a proactive maintenance approach which performs preventive maintenance together with predictive one. That is, for some of the machine parts or equipment that can provide their operational status with related process parameters, we adopt predictive approach and we adopt preventive approach for other parts or equipment. First, we identified machine parts and their related process parameters, and then derive the relationship diagram between process parameters and machine parts. It has many to many relationships. Second, we analyze the process parameters data using statistical analysis. In this analysis model, we use the product configuration error as response variable and process parameter data as independent variables. With this analysis, we identify the parameters, which rarely affect the response value, and we may exclude from the process parameter list for predictive maintenance. Third, we derive prediction model with remained significant process parameters data. We adopt Nelson’s rules to detect abnormal patterns. Fourth, we monitor the real-time operational parameters and evaluate the data patterns against Nelson’s rules. Fifth, when abnormal patterns of parameters were detected, the related parts of the parameter are notified to maintenance workers by referring to fault tree diagram. Finally, for the parts or equipment which is not coved by predictive maintenance, we use preventive maintenance. For the purpose of this, we classify the parts or equipment based on its checking period.

The remainder of the paper is organized as follows. In Section 2, related research methodology is described. After a brief introduction of methodology, Section 3 discusses research results. Finally, Section 4 concludes the paper with proposed approach’s limitation and suggestions.

RESEARCH METHODOLOGY In this paper, we propose a proactive maintenance approach which combines preventive maintenance and predictive maintenance. The preventive maintenance uses periodic checking of maintenance items and the predictive maintenance forecast the maintenance items and its maintenance time with real-time process parameter data analysis. Figure 1 shows procedure of our approach. At first, through experts’ opinions and literature survey we identified the parts of injection molding machine, which requires maintenance, and their related injection molding process parameters. Second, we used statistical analysis model such as multiple regression and ANOVA to identify the significant parameters which significantly affect the quality of injection molding products. We pick out only the parameters which give significant effect to our response variable, that is, configuration error. Third, we developed the statistical time series models to predict the significant parameters’ future patterns and predict its maintenance point in time (Box, Jenkins and Reinsel, 2008). Finally, with the real-time monitored parameter values and predicted values, we evaluate the trends or patterns against Nelson rules. When the abnormal patterns are detected, maintenance information is notified to maintenance worker by referring fault tree. By using fault tree model which can relate the parameters with equipment or parts, we can identify the target equipment to perform corrective actions before fault occurs.

Real-Time Proactive Maintenance Approach Using Statistical Process Control Technique

Figure 1: Maintenance Procedure

RESEARCH RESULTS Predictive Maintenance In injection molding process, the 13 parameters were recommended as candidate process parameters by literature survey and field experts’ opinion. For the purpose of efficiency, we picked out only 7 significant parameters to use in prediction model development. Figure 2 shows the result of regression analysis. This analysis shows only 7 parameters, including feeding time (‘T302’ in the figure) and minimum cushion (‘S303’ in the figure), were significant to our response variable, configuration error.

Figure 3 shows the result of goodness of fit test of our regression model. This figure shows that our regression model, which picked out 7 parameters, is adequate, so we can use statistically only 7 parameters for predictive maintenance.

Figure 4 shows the relationship between 7 process parameters and their related maintenance item. This relationship was derived from the maintenance manuals of injection molding vendors.

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In the meantime, every company may have a policy which describe that they can manage their false alarm, that is, type I error in statistical term. We adopted three rule out of 8 Nelson;s rules because only three rules are related to the wear or breakdown of machines or part of them. Figure 5 shows example p-values for k of each rule and overall p-values for example combination of three rules. Therefore, based on the company’s policy, we can select a combination of three rules to evaluate the patterns of monitored or predicted data in our predictive models.

By referring this relationship and their related frequency values in fault tree information, we can pick out the maintenance item when abnormal patterns were detected with any related process parameters, and maintenance notified to maintenance workers.

In this research, we showed our approach with two example parameters: feeding time and minimum cushion quantity. The injection molding cycle begins when the mold closes, followed by the injection of the polymer into the mold cavity. Once the cavity is filled, a holding pressure is maintained to compensate for material shrinkage. In the next step, the screw turns, feeding the next shot to the front screw. This causes the screw to retract as the next shot is prepared. This elapsed time is called feeding time. Once the product is sufficiently cool, the mold opens and the product is ejected (Osswald, Turng and Gramann, 2008).

Real-Time Proactive Maintenance Approach Using Statistical Process Control Technique

Figure 2: Result of Regression Analysis with 13 Parameters

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Figure 3: Result of Goodness of Fit test of Regression model

Figure 4: Relationship between Maintenance Items and Parameters

Real-Time Proactive Maintenance Approach Using Statistical Process Control Technique

p-value of one rule for sample k (b) overall p-value for sample rule combination Figure 5: p-values for each rule and Rule combinations

Minimum cushion quantity means the minimum raw material quantity which must be remained at the end of screw after injection of raw material is finished into the mold cavity. This cushion quantity guarantees that the cavity is filled with enough raw materials. If this quantity is less than the minimum threshold value, it means the check ring, which is functioning as preventing backflow, is broken or mal-functioning and the raw material was flowed backward. The backflow may cause the loss of weight of product and defective product. Therefore, when the cushion quantity goes out of normal range, the check-ring check must be scheduled to find out whether it broke or not.

We gathered the values of cycle time and minimum cushion quantity with our developed controller interface program. We also developed a maintenance support system on LabView® environment. The injection molding machine for this experiment is Sumitomo 30 ton model (SE30DUZ) which are producing phone camera lens. For the lens, the machine used EP-5000 resin for injection molding. Figure 6 shows a snapshot of monitoring and pattern evaluation minimum cushion quantity parameter. The horizontal lines show 4 sigma value lines. The white line represent real raw data, green line represent fitted data, red line means predicted data. As this figure shows that the two shots were violating rule 1 and four shots were violating rule 2, it means that the check rings need to be notified for maintenance.

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Figure 6: Snapshot of Monitoring and Pattern Evaluation of Minimum Cushion Quantity (4-11-6 case)

In the meantime, Figure 7 shows another snapshot of monitoring and pattern evaluation of minimum cushion quantity parameter. As you can see, there were no abnormal patterns in the figure in the figure.

Figure 8 and 9 shows show snapshots of monitoring and pattern evaluation of feeding time parameter. In Figure 8, abnormal patterns were detected at two shots. However, there were no abnormal patterns detected in Figure 9 case. Therefore, by adjusting the statistical constant values such as standard deviation (sigma) and run numbers, we can forecast the more accurate detection about abnormal pattern or out of order of related parts.

Figure 7: Snapshot of Monitoring and Pattern Evaluation of Minimum Cushion Quantity (6-14-7 case)

Real-Time Proactive Maintenance Approach Using Statistical Process Control Technique

Figure 8: Snapshot of Monitoring and Pattern Evaluation of Feeding Time Parameter (5-10-5 case)

Figure 9: Snapshot of Monitoring and Pattern Evaluation of Feeding Time Parameter (6-10-6 case)

Preventive Maintenance For the parts or equipment which is not coved with predictive maintenance, we perform preventive maintenance. We surveyed maintenance manuals of injection molding machine vendors and field experts’ opinion, we classified the parts or equipment based on its checking period. Figure 10 shows a part of periodic checking items for preventive maintenance. It shows daily, weekly, monthly, and quarterly checking item list. Therefore, we can notify maintenance information to workers based on maintenance history that is stored in maintenance database system.

To manage maintenance information such as its history, relationship between process parameter and its related part or equipment, we developed maintenance support database system. Figure 11 shows a part of database schema designed for our maintenance support system. It includes the required entities for preventive and predictive maintenance.

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Figure 10: Snapshot of Periodic checking items for Preventive maintenance

Figure 11: Snapshot of Database Design for Proactive Maintenance

CONCLUSION This research is a part of three year project and the research is still in actively progress. We proposed a proactive maintenance approach for injection molding process. The proposed proactive maintenance model is consisted of preventive maintenance and predictive maintenance. Predictive maintenance is focused on the real time data monitoring, predicting

Real-Time Proactive Maintenance Approach Using Statistical Process Control Technique future patterns, and evaluating patterns against Nelson’s rules which are usually adopted as one of the statistical process control. Preventive maintenance use periodic checking list which include the maintenance item list that is not covered with predictive maintenance. We used statistical analysis to pick out only the significant operational parameters and reduce the burden of prediction model.

Currently, we are developing various prediction models on the injection molding parameters and testing them to identify the adequate model for each core parameters with monitored data set. We expect that we can apply this approach to similar environment. In this research, we are developing prediction models on NI’s LabView environment, however, unluckily, LabView prediction function is not plentiful in terms of its resources such as algorithms and tools compared to, for example, MathWorks’ Matlab. Therefore we have limitations in applying more realistic and well-performing algorithms. Therefore, we are considering migration to Matlab or even C++ code program for prediction model development. Furthermore, we are going to apply another prediction models such as Neural Network and SVM to compare with time series based models.

Another further research includes validating or adjusting the constant values of our statistical models. For example, we have to adjust our model’s sigma value and run number to prevent false maintenance alarms. We are continuously monitoring to capture the various types of abnormal patterns to validate and fit our suggested approach.

ACKNOWLEDGEMENT This work was supported by the Industrial Strategic Technology Development Program (10040952, Development of BIS based injection molding system with rapid response ability and autonomous intelligence) funded by the Ministry of Knowledge Economy of Korea.

REFERENCES Blanchard, B. S., and D. Verma (1995), E. L. Perterson, Maintainability: A key to effective serviceability and maintenance management, John Wiley & Sons, Inc. Box, G., Jenkins, G.G., Reinsel, G.C. (2008), Time Series Analysis – Forecasting and Control, 4th Edition, John Wily & Sons. Blischke, Wallace R, and D.N Prabhakar Murthy. Case Studies in Reliability and Maintenance. New Jersey: John Wiley and Sons.. Campbell, John D. and Andrew K.S. Jardine (2001), Maintenance Excellence: Optimizing Equipment Life-Cycle Decisions (Dekker Mechanical Engineering), Marcel Dekker, Inc. Dhillon, B.S., and Y. Liu (2006), Human error in maintenance: a review, Journal of Quality in Maintenance (Emerald Group Publishing Limited) 12, no. 1, pp.21‐36. FANUC Ltd (2005), FANUC Roboshot S-2000i Instruction Manual, FANUC Ltd. Niebel, Benjamin W (1994), Engineering maintenance management, Marcel Dekker Inc. Osswald, T., Turng, L.S., Gramann, P. (2008), Injection Molding Handbook, 2nd Edition, Hanser.

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Salonen, Antti, and Mats Deleryd (2011), Cost of poor maintenance, Journal of Quality in Maintenance Engineering 17, pp 63‐73. Sumitomo Heavy Industries, Ltd. (2003), Instruction Manual SE-D series Injection Molding Machine, Sumitomo Heavy Industries. Wikipedia (2013), Predictive Maintenance (http://en.wikipedia.org/wiki/Predictive_maintenance).

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Full Article Available Online at: Intellectbase and EBSCOhost │ JAGR is indexed with Cabell’s, JournalSeek, etc.

JOURNAL OF APPLIED GLOBAL RESEARCH

TEACHING BUSINESS STUDENTS MOBILE APPLICATION DEVELOPMENT

Degan Kettles University of Central Oklahoma, USA

ABSTRACT obile applications that run on phones and tablets now number in the millions. Businesses need employees that can build and manage the development of these applications. The challenges with developing these applications are Mthat native application development is difficult in relation to the skills of business school students and native development is not cross platform among the many devices that are in use. The purpose of this paper is to demonstrate how a course can be taught to business school students that makes mobile application development achievable within their skill sets while at the same time having the applications be cross platform.

Keywords: Mobile Application Development, HTML 5, CSS, JavaScript, Web SQL, jQuery

INTRODUCTION Since 2007 when the iPhone came out, so called smart devices and the applications that run on them have proliferated. As of June 2014 it was reported that the iTunes store contained over 1.2 million applications and had delivered over 75 billion downloads (App Store (iOS), n.d.). Google Play reports similar numbers (Google Play, n.d.). In addition to these, application stores are available focusing on mobile device platforms for Windows, Amazon’s Kindle, Nook, Blackberry, WebOS, and others. Additionally, on top of the millions of mobile applications that are built specifically for the public application stores for the aforementioned platforms, there are countless other applications being developed for internal use by organizations.

This explosion in mobile application development activity has led to a shortage in qualified developers (Ayo, 2013; Bureau of Labor Statistics, 2014; Goodwin, 2013). Meeting the market need for qualified mobile developers and mobile development managers can in part be filled by business schools that offer training in software development that is targeted at solving business problems. Historically business schools and Information Systems programs have taught programming languages such as Visual Basic, C#, and Java to prepare students for programmer analyst positions. With the possible exception of Java, which runs natively on

Teaching Business Students Mobile Application Development

Android devices, these languages may not be adequately preparing students to be effective developers of mobile applications.

Addressing the need for mobile application developers begins with an understanding of mobile application development. Mobile application development includes programing for smart phones as well as tablets. Software on these devices has advantages and disadvantages over previous forms of software development. On the negative side, mobile devices typically have smaller screen sizes, less efficient keyboards for typing, less available memory, and less available processing power than applications developed for desktop computers or servers. On the positive side, they excel in terms of battery life and portability. In addition, mobile devices also have access to unique hardware features such as location awareness, motion sensitivity, vibration capability, camera integration, and phone calling. Although it is possible to duplicate desktop software functionality on a mobile device, some apps are better suited for desktop computers and others are more useful on a mobile device. For example, desktop apps like spreadsheets are easier to use on a desktop while video-enabled apps may be better suited to mobile use.

Addressing the need for mobile application developers also requires an understanding of the skillsets they must possess. Mobile development requires that a developer learn a programming language that is suitable for the target device that they will be programming in. Most platforms such as Google’s Android and Apple’s iOS have a native language that runs the fastest on their particular platform, but there are also other alternatives that tend to be easier to learn than the native languages. When speaking of the options for programming for a mobile device, the terms native app, web app, and hybrid app are often used. A native language app is one that runs directly on a device on the operating system level and has access to a device’s hardware. A web app is an application that can be made to look and function like a native app, but is actually written in HTML (and JavaScript and CSS). A hybrid app is one that contains elements of both native apps and web apps. An example of a hybrid app would be one that is partially written in a native language but also has an embedded screen area that uses a widely available web app such as Google Maps.

Further complicating the options related to developing for a mobile device is the fact that it is also possible to develop for a “platform” that can be installed along with an application on a particular mobile device. For example, although Java is the native application language used for Android devices, it is also possible to program for a platform called Corona which can run on many different devices. If a person learns to program for the Corona platform, the program can run with minimal modification on Android, iOS, and Windows devices. Sometimes platforms can only run on one device, and sometimes they run on many. In the case of Corona, it can run on many different devices but requires that a developer learn a unique programing language called Lua in order to use it. There are over 50 different platforms that can be developed for that target the main devices that are commonly used today such as the iPhone and Android phone (Mobile Application Development, n.d.). The languages that can be used to program for these platforms include ActionScript, HTML, JavaScript, Java, C, C++,

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Objective-C, .Net languages, Lua, Object Pascal, Scheme, Python, and Ruby to name just some.

Suffice to say, choosing which language to teach a student who aims to do mobile development is not a simple choice. Some languages work exclusively with devices from a single vendor, some platforms are specialized for video games rather than business-oriented applications, and some languages that require explicit memory management are on the upper end of what a novice business programmer can handle. Furthermore, there are not currently mobile application books targeted directly towards business students as there are for other platforms such as .Net. With these issues in mind I recently created and successfully delivered a mobile application course tailored to the needs of business students. I chose web app development as the approach to build mobile apps because the skills are easier to pick up than alternative languages and because the applications themselves can be deployed on virtually all mobile devices. Doing web app development for mobile devices requires learning several different, relatively easy skills. An explanation of what those skills are and how they can be presented in a class is explained in this paper.

COURSE DEVELOPMENT In order to teach web app development as a method for creating stand alone applications on mobile devices there are several skills that need to be learned. To effectively create an application requires an understanding of HTML, CSS, JavaScript, databases, and mobile device frameworks. A framework in this context is a library of code comprised primarily of HTML, CSS, and JavaScript and there are several framework options available. Teaching mobile app development using the web app approach therefore requires teaching lessons on each of these five concepts. A pre-requisite for any student taking this course is to have had at least one programming course. The JavaScript language has a simplified C-like syntax and therefore any C-based language such as C# or Java will provide a good enough foundation for learning it. VB.Net is also sufficient but less ideal as a foundation for this course. This course should not be offered in lieu of an introductory programming course because foundational concepts such as variables, loops, and methods should be covered in a stand-alone course. Although learning a programming language in another class is the only true pre-requisite for this class, it is beneficial if the student has already had or is simultaneously enrolled in a database course. As reading materials for this course I use three primary sources: tutorials about web technologies available at w3schools.com, the book Building iPhone Apps by Jonathan Stark (Stark, 2010), and the book jQuery Mobile by Jonathan Firtman (Firtman, 2012). The following sections describe what needs to be taught as it relates to the five foundational concepts for mobile app development.

1 HTML Figures 1 and 2 demonstrate a starting point for a simple application that students will produce as part of the class. In Figure 1 you see a screenshot that looks like a menu on a mobile device and in Figure 2 you see a block of HTML source code that is used to create that menu.

Teaching Business Students Mobile Application Development

The first step in mastering the set of skills required to create mobile apps in this way is therefore to learn HTML. Individuals that have built web pages before may see the source code in Figure 2 and think that this looks similar to the source code required to make a web page that would be displayed in a traditional web browser. The reason for this is that it is very similar. Web apps installed on mobile devices can be made to look like a natively programmed application, complete with their own launch buttons, but despite looking like native apps they are actually just plain web pages. The reason that they don’t look like web pages when running on a mobile device is that you can add in a little code to your page that makes the browser’s borders disappear. Therefore, with clever looking graphics and styling you can make apps in HTML that are indistinguishable from native apps.

The HTML language is comprised of over 100 tags that collectively are used to build individual web pages. A tag is comprised of pairs of angle brackets with keywords inside of them such as … for bolding text or … for italicizing text. These tags can be typed into a simple text editor such as notepad or textedit and when the document is saved with an .html file extension and opened in a web browser, the page shows up with formatting applied. Although there are many tags that can be used to make an individual web page, mobile apps built as web apps often only require knowledge of a small handful of them. In order to learn the basic HTML tags needed to do mobile development I have students go to the w3chools.com website and do relevant readings and tutorials. At the end of the tutorials the students should have the ability to create a basic web page in a text editor and display it in a web browser. This ability forms the basis for doing all mobile application development because all of it is done using a text editor and a standard web browser such as Chrome or Safari.

Figure 1: Screenshot of Sample Application Created In Course

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Figure 2: Screenshot of source code for interface in Figure 1.

Below is the url for the readings as well as a list of the sections that they should read. http://www.w3schools.com/html/default.asp

HTML Introduction HTML Editors HTML Basic HTML Elements HTML Attributes HTML Headings HTML Paragraphs HTML Formatting HTML Comments HTML Links

Teaching Business Students Mobile Application Development

HTML Head HTML CSS HTML Images HTML Tables HTML Lists HTML Blocks* HTML Layouts* HTML Forms

2 CSS In the early days of web development the styling of a web page was done using HTML tags. Font tags were used to indicate the size and color of text, for example. Later, the styling of web pages was separated out into a separate language called Cascading Style Sheets (CSS). CSS styles are typically indicated by using keyword followed by curly braces that contain lists of formatting commands, see an example in Figure 3 below. With the advent of CSS, HTML tags became used primarily to indicate document structure, such as to indicate where a header, footer, and navigation bar would go in the page, and CSS was used to indicate the color, font size, and images that would go into those areas. The same concepts apply to the layout and visual appearance of mobile web apps. HTML is used to indicate structural elements of an application screen page such as the header, footer, and navigation locations, and CSS is used to make those screens look virtually indistinguishable from those written in a native programming for a particular device. In order to teach these concepts I have students read several sections from the w3schools.com site on CSS and then I have them read the first few chapters of the Jonathan Stark book in which they learn how to write CSS code from scratch that creates mobile interfaces that look native.

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Figure 3: Source code and screenshot demonstrating the use of CSS for text formatting

The specific CSS readings on the w3schools.com site that I assign and their location is as follows: http://www.w3schools.com/css/default.asp

Introduction Syntax Selectors (important)

Teaching Business Students Mobile Application Development

How To Backgrounds Text Fonts Links Lists Tables Box Model Display

3 JavaScript JavaScript is a language developed for web pages that has a C-like syntax. When developing mobile web apps it is the primary method for implementing application logic, doing things like reading content that has been typed into form fields by users and conditionally displaying it back out to a screen. Business applications rely heavily on the input and retrieval of data and so using JavaScript is a critical skill to develop and I take more time on this skill set than on the others. For many students this feels like learning a programming language for the first time, even though it is a simple language.

JavaScript has heavy integration with web pages because it was designed to support them specifically. JavaScript is aware of the structure of any HTML page (or the tags that have been used in it) and can be used to target and change the contents of any tag within a page. Unfortunately, browser incompatibilities among Internet Explorer, Chrome, and Safari make it so that web developers have to write separate code to do the same thing using JavaScript in different browsers. From this problem emerged jQuery as a library of code that could be used to do common tasks in JavaScript using a single command and it would work the same across all browsers. It has the added benefit of providing simple commands to do special effects such as animated page transitions. Therefore, I train students in JavaScript first and then jQuery second because jQuery is commonly used in web app development as a way to access input field information.

Figure 5a demonstrates a simple block of html code with an area designated as “content”. All it does is show content in a web browser without any special commands. Figure 5b shows how to update the content in this web page using traditional JavaScript code, and 5c shows how the same thing would be done if using the JavaScript library called jQuery.

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Figure 5a: A plain HTML document and its display in a web browser

Teaching Business Students Mobile Application Development

Figure 5b: Updating a block of text using traditional JavaScript

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Figure 5c: Updating the same block of text using jQuery

The readings and tutorials I assign for learning JavaScript and jQuery come from w3schools.com and chapters 1, 2, and 3 in the Jonathan Stark book. I also assign a brief jQuery tutorial of which there are many quality ones available on the web.

The readings for JavaScript on the w3schools.com that I assign are as follows:

JS Introduction JS Where To JS Output JS Syntax JS Statements JS Comments JS Variables JS Data Types JS Functions

Teaching Business Students Mobile Application Development

JS Events JS Conditions DOM Intro DOM Methods DOM Document DOM HTML DOM CSS

The jQuery tutorials are useful for understanding how jQuery works, however mastery of this topic is not strictly necessary because only a few features of the language are needed. If time permits, it is useful to have students read the first six lessons or so from this website: http://www.w3schools.com/jquery/.

Note: It is also of critical importance to teach and demonstrate the use of the JavaScript debugger that is built into all major web browsers when doing JavaScript development. This debugger is also useful when developing databases as will be described next. The Stark book discusses the use of this tool.

4 Databases When building applications for mobile applications one interesting dilemma is where to get data from and where to store data that a user enters in to the app. One option is to use data stored locally on the device, and another is to use and store data remotely. When teaching this course I emphasize skills related to the first option. Teaching students how to store and retrieve data remotely is something I discuss because in a corporate setting is makes a lot of sense to use and update organizational data, however actually doing it is beyond the scope of an introductory course because it involves dealing with security and web services.

The Stark book demonstrates several methods for storing data locally on devices. One method involves storing simple key/value pairs, which is of limited usefulness when creating data-rich applications. Complex data consisting of records is better stored in full databases. The Stark book shows how to create SQL compliant databases and this is what I teach as part of this course and it works splendidly. It should be noted that this capability called Web SQL is supported in the major browsers other than FireFox but as far as being a web standard it is not being developed further by the web standards body known as the W3C. Compatibility with specific web browsers is important to be aware of because mobile apps run in the preferred web browser of any given mobile device, and the preferred web browsers are currently either Chrome or Safari. It appears unlikely that Web SQL support will be dropped from the web browsers on popular devices but it is possible. One alternative to Web SQL is to use IndexedDB which is only recently being supported in all major web browsers, so many currently used web browsers will not support it. The difference between Web SQL and IndexedDB is that IndexedDB is optimized for storing hierarchical objects which are typical to object oriented programming while SQL databases are not. Nevertheless, students are

Degan Kettles JAGR - Volume 7, Issue 20 (2014), pp. 19-33 typically taught SQL in business schools and using Web SQL allows students to leverage a skill they are likely to have already learned.

Typically I teach interaction with a Web SQL database after students have learned HTML, CSS, and JavaScript. By that point students sometimes feel a bit overwhelmed by all that they have already learned and this new skill pushes their comfort level a bit. To help make the learning process easier, I provide examples of code for creating databases, creating tables, inserting data, reading data, and deleting data, and let them customize this code for their own assignments that require different tables and databases. The starting point for learning about Web SQL databases is to carefully read Chapter 5 of the Stark book and to try the exercises. Interacting with the Web SQL databases requires learning the appropriate syntax in JavaScript. I provide a sample of this syntax in the following figures.

Figure 6: JavaScript code to create a database and a database table within it

Figure 7: JavaScript code to insert hard coded values into a Web SQL table

Teaching Business Students Mobile Application Development

5 Mobile Development Frameworks The final major topic to teach as part of a course on mobile web app development is the use of frameworks. A framework is a library of code that includes CSS, images, and JavaScript which together can be used to quickly create consistent, feature-rich interfaces on mobile devices. In other words, mobile frameworks provide User Interface options for mobile applications. The screenshot from Figure 1 was created using a framework called jQuery Mobile. A framework such as jQuery Mobile provides a standard set of buttons, tools, input fields, backgrounds, etc. that you can customize and use in your applications. The Stark book emphasizes a framework which is known today as jQT while the Firtman book emphasizes the jQuery Mobile framework. The Stark book is excellent because it shows how to design native looking interfaces from scratch as well as intro ducting the jQT framework, but the book’s greatest feature is actually teaching about how to use JavaScript to provide application logic and write to a database. The jQuery Mobile book is used as part of my course because it is considered the most popular mobile development framework today and enjoys considerable 3rd-party support including plug ins. The jQuery Mobile book provides a multitude of interface options for designing mobile applications. I only require that students read the first couple of chapters and then use the rest of the book as a reference. In addition to this book I also have students look at a related site called the theme roller for jQuery Mobile (http://themeroller.jquerymobile.com). This site allows developers to visually select the color combinations they want for their mobile application and then download the corresponding framework source files.

CONCLUDING REMARKS The previous sections provide an overview of the topics that need to be taught when presenting a course on mobile web apps. A few extra insights will make teaching such a course more manageable. The first is how to post and review assignments. It is possible to use Google Docs to create publicly accessible URLs for creating and submitting assignments. Do a search on how to create a publicly accessible web page using Google Docs and explain how to use this to your students. The one problem I ran into with this in my course was students not putting their files in a new folder and setting the properties of that folder and its files to public.

Another tip for teaching a course like this is to make an online forum in your learning management system available and to allow students to interact about the topics they are learning in there. When they teach each other these concepts it helps to reinforce their learning and it reduces the load placed on the instructor. One thing I did was to have the URL for completed homework assignments posted into moderated forums (so posts require moderator approval before they can be viewed by others) and then when the assignments were graded I made them all public. This allowed students to review the code that other students wrote and benefit from the creativity and learning of others.

I have taught this course twice so far. The first time I did it as an independent study course. In the independent study course I assigned the student readings and assignments and had the

Degan Kettles JAGR - Volume 7, Issue 20 (2014), pp. 19-33 student check in with me when they had questions. Overall this went well. The second time I taught it as an online course. The graded items in this format included quizzes based on readings, homework assignments on individual topics, and a cumulative project that was selected from a list of options that I provided. In an online setting I found that there were some students who had no problems at all with the material while at the same time there were other students that got stuck and were reluctant to ask for or receive help despite me reaching out to them several times. This problem might have been less of an issue had we had more face to face sessions as with a traditional course. The biggest issue that students had was with getting comfortable with an initial framework and then transitioning to another framework. In future classes it might be possible lessen this issue by introducing the jQuery Mobile framework earlier and presenting it as an interface creation tool. This would make it the first UI framework they would learn rather than the second, and make it easier to come back to it towards the end of the course.

REFERENCES App Store (iOS). (n.d.). In Wikipedia. Retrieved June 24, 2014, from http://en.wikipedia.org/wiki/App_Store_(iOS) Bureau of Labor Statistics. (2014, January 8). Software Developers. Retrieved from http://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm Firtman, M. (2012). jQuery Mobile: Up and running. Sepastapol, CA: O’Reilly. Goodwin, Bill. (2013, February). CW500: Skill shortages loom as development comes back in- house. Retrieved from http://www.computerweekly.com/feature/CW500-Skills-shortages- loom-as-development-comes-back-in-house Google Play. (n.d.). In Wikipedia. Retrieved June 24, 2014, from http://en.wikipedia.org/wiki/Google_Play Mobile Application Development. (n.d.). In Wikipedia. Retrieved June 24, 2014 from http://en.wikipedia.org/wiki/Mobile_application_development Omojola, Ayo. (2013, July 15). The Shortage of Developer Talent is Crushing Mobile. Retrieved from http://www.forbes.com/sites/ayoomojola/2013/07/15/the-shortage-of- developer-talent-is-crushing-mobile/ Stark, J. (2010). Building iPhone Apps with HMTL, CSS, and JavaScript. Sepastapol, CA: O’Reilly.

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JOURNAL OF APPLIED GLOBAL RESEARCH

PROKARYOTIC COMMUNITY ANALYSIS IN A SUBTROPICAL COASTAL PLAIN RIVER: DO ARCHAEA AND BACTERIA RESPOND TO SAME SIGNALS?

Dmitri Sobolev University of Houston-Victoria, USA

ABSTRACT reshwater microbial communities, including those of coastal plain rivers, have been extensively studied over the last few decades. However, studies of freshwater prokaryotes were largely limited to the members of domain FBacteria. Development of molecular techniques for community analysis allowed detection and identification of organisms previously unrecognized, most notably various Archaea. We analyzed the Guadalupe River prokaryotic community by amplifying a 200 base pair eubacterial and 600 base pair archaeal 16S rRNA fragment, with the forward primer modified with a GC tail. A community fingerprint was produced by separating amplicons on a DGGE gel. Each one of the five stations indicated consistent presence of Archaea in the riverine microbial community. In contrast to eubacteria, the archaeal community varied among sites. Substantial similarity of the eubacterial communities among the sites, coupled with significant site to site variation of the archaeal community, suggests that eubacterial and archaeal communities may be responding to different sets of environmental stimuli. Monitoring both archaeal and bacterial communities in the environment is necessary to obtain a complete picture of prokaryotic community response to various challenges. Our findings highlight the potential utility of natural archaeal communities as bioindicators.

Keywords: Archaea, Bacteria, DGGE, River, Bioindication

INTRODUCTION Guadalupe River is a part of the Guadalupe – San Antonio river system, flowing approx. 230 miles from Kerr County, Texas to San Antonio Bay on the Texas Gulf coast. The river has been significantly impacted by a drought in 2010-2013. Multiple small urban and rural communities along the course of the river influence the river water quality, highlighting the need to monitor the status of the river ecosystem.

Microbial community fingerprinting has been long used to assess community diversity, site-to- site community variations, community succession and influence of various natural and

Prokaryotic Community Analysis In A Subtropical Coastal Plain River: Do Archaea and Bacteria Respond to Same Signals? anthropogenic factors upon the community (e.g., Kozdrój and van Elsas 2000). Denaturing gradient gel electrophoresis (DGGE) technique is one of the approaches to generating microbial community fingerprints (Muyzer et al. 1993) by separating PCR-amplified fragments based on their melting temperature, producing a pattern of bands, allowing comparison of different microbial communities or monitoring community changes over time (e.g., Jackson et al., 1998).

Archaea is a unique group of prokaryotic organisms, which represents one of the three domains of the living world. Previously characterized as extremophiles, those organisms were found to be ubiquitously distributed in various environments (DeLong, 1998, Fuhrman and Davis 2000). A thriving archaeaplankton community was found in various rivers as well (Crump and Barros 2006, Galand et al. 2006), suggesting a substantial role of those organisms in functioning of the prokaryotic community.

Use of the 16S rRNA gene marker specific to Eubacteria to monitor microbial community changes is a well-established approach to detecting community response to environmental change (Dahllöf 2002, Nguyen and Sobolev 2013, Sobolev et al 2013). The use of those markers will detect changes only within eubacterial community, ignoring other groups that may serve as indicators of such change. With the discovery of widespread mesophilic archaeal communities in a variety of habitats, the question becomes whether eubacterial and archaeal communities would respond differently to the same set of stimuli, and whether archaeal community should be used as an indicator of environmental disturbance.

This study sought to investigate whether changes in archaeal community mirror those in the eubacterial one and whether similarities between the sites identified by eubacterial community analysis would be consistent with similarities of archaeal communities.

MATERIALS AND METHODS River water samples were collected from existing structures at 5 locations along Guadalupe River system designated "Seguin" (Max Starcke Park), "Gonzales" (Highway 183 bridge), "Cuero" (Highway 72 bridge), "Victoria" (Boat ramp off McCright Drive) and "Goff Bayou" (Goff Bayou boat ramp off Highway 35) in Southeast Texas (Fig. 1). Sterile plastic vials were submerged inverted to the depth of ca. 10 cm and then righted to fill. Samples were then transported on ice to the laboratory (<2 hours). Fifty milliliters or less of the sample was filtered through 0.22 um membrane syringe filter (Millipore) by use of a peristaltic pump and DNA was extracted by modified phenol-chloroform procedure (Griffith et al. 2000). Resulting extract was purified with Amicon Ultra centrifugal filters (100000 MWCO; Millipore) and diluted to ca. 100 ng/uL. Diluted DNA was used as a template in PCR at 1% of the total reaction volume.

All genes were amplified in a PCR mixture containing 10 uL 10X PerfectTaq buffer, 20 uL 5P solution, .2 uL each of 200 mM forward and reverse primer solutions (Operon Technologies), 2 uL of 20 mM dNTP solution (Fisher Scientific), 2.5 units PerfectTaq polymerase (5 Prime, Inc.), and PCR-grade water to a total of 100 uL. All chemicals, unless otherwise noted, were

Dmitri Sobolev JAGR - Volume 7, Issue 20 (2014), pp. 34-44 supplied as a part of the PerfectTaq kit from 5 Prime, Inc. Each reaction mix received 1 uL of the above template DNA and was divided into three roughly-equal subsamples. Subsamples were cycled in a heated-lid Eppendorf Mastercycler as follows: initial melting at 94°C for 5 minutes, followed by 25 cycles of melting at 96°C for 30 seconds, annealing at 60°C for 30 seconds and extension for 1 minute at 72°C. The cycling was followed by a final extension step of 5 minutes at 72°C. Use of PerfectTaq allowed the use of the same annealing temperature for all of the primer sets. Archaeal 16S gene fragments ca. 550 bp long were amplified with primers A348Kf (A348If used by Hori et al. (2006), modified by replacing inositol with equimolar G and T base mixture) and Arch915R (Siboni et al. 2008). Eubacterial 200 bp 16S fragments were amplified with the primer set P2/P3 (Muyzer et al. 1993). For DGGE analysis, primer A348Kf for Archaea was modified by addition of the 5' GC tail (Myuzer et al. 1993); P3 primer for Eubacteria already included the GC tail as designed (Myuzer et al. 1993). DGGE was conducted as described previously (Jackson et al., 1998) in 10-40% gradient at 70C for 4 hours, with constant voltage at 120V. Resulting gel was stained with ethidium bromide solution (1 mg/L for 15 minutes), rinsed and photographed with ultraviolet illumination. Major bands were identified and marked. Jaccard distances (J') between the sites were calculated for each pair of sites as

J'1,2=1-[C/(2N-C), where C – number of bands common between sites 1 and 2, N – total number of different bands in 1 and 2 (Tibayrenc et al. 2003). MEGA 5 software (Tamura et al. 2011) was used to compute a neighbor-joining tree based on Jaccard distance matrix.

RESULTS AND DISCUSSION All samples produced positive amplification of fragments of expected length, ca 200 bp for eubacteria and ca 550 bp for Archaea. DGGE produced a clear separation of the amplified fragments, generating distinct community fingerprints. Bands within those fingerprints were identified and matched across all samples. Overall number of discernible bands was used as a proxy for species richness of planktonic bacteria or archaea. From the DGGE patterns, 18 unique bands were identified in archaeal community fingerprints and 17 in the eubacterial ones across all sites. Those fingerprints were highly similar in case of the eubacterial fragments, yet substantially different site to site for the Archaea (Figs. 2 and 3).

Based on the identified band patterns, Jaccard distances among the samples ranged from 0 to 0.125 for eubacterial community fingerprints and 0.077 to 0.773 for archaeal ones. Notably, Archaea- and Eubacteria-based tree topologies were drastically different (Fig. 4)

The number of groups identifiable from the fingerprint varied site to site; from 12 Gonzalez to 14 in Victoria and Seguin sites for eubacteria and from 5 in Seguin to 13 in Victoria for archaea (Fig. 5). Notably, the two sites that exhibited the greatest apparent eubacterial diversity, also 36

Prokaryotic Community Analysis In A Subtropical Coastal Plain River: Do Archaea and Bacteria Respond to Same Signals? exhibited both extremes of apparent diversity of Archaea, with minimal number of bands in archaeal community fingerprints detected in Seguin and maximum in Victoria site.

Positive amplification of the archaeal 16S rRNA gene fragment from all of the samples indicates that Guadalupe River water supports a mesophilic planktonic archaeal community in all locations surveyed. While the exact role of those organisms remains to be determined, one could hypothesize that at least some of them are autotrophic ammonia oxidizers detected in a variety of other systems (Francis et al. 2007). Greater number of detected eubacterial 16S markers, compared to archaeal ones indicates that in the aquatic microbial community, Archaea are relegated to a small handful of fairly limited niches.

Although approximately the same number of unique bands identified in the 5 samples, the site- to-site differences both in community diversity and community composition were significant, at least for Archaea. The total number of bands detected in the archaeal community analysis never exceeded 11 in any of the samples, out of total 18 unique bands found in all sites, with as few as 5 bands detected in Seguin samples. Eubacterial community exhibited greater uniformity and greater apparent species richness, with as many as 15 bands detected in Victoria and Seguin sites (Fig. 5).

Site-to-site variations of the eubacterial community, as evidenced by the Jaccard index, were fairly minor. This shows a great uniformity of this community throughout the river stretch surveyed, suggesting relative uniformity of habitats from the standpoint of that community. That apparent uniformity can be brought about by a single dominant factor that bacteria readily and uniformly respond to, such as, e.g., massive inputs of labile organic material. Such inputs would select for a group of rapidly-growing organisms, exhibiting relatively minor site-to-site variation. According to the eubacterial community fingerprint, Victoria and Seguin sites were identical (zero Jaccard distance), whereas according to the archaeal community analysis, the distance between those two sites was the second highest (0.615) . This observation suggests that the archaeal and eubacterial communities occupy different "habitats" (in the broadest possible sense), responding to different cues within them.

Compared to bacteria, Archaea are generally known for a slow growth (Delbès et al. 2001; Herndl et al. 2005) As such, they would not necessarily respond, or have the opportunity to respond to the stimuli leading to the abundance of the selected subgroups of eubacteria consistently observed at different sites.

Alternatively, it is possible that, due to their lower growth rate, archaeal community failed to respond to the rapidly changing conditions fast enough. As a result, archaeal community may reflect a longer-term conditions, whereas eubacteria react to short-term changes. This possibility also implies that in a flowing river, slow-growing planktonic organisms are indicative of conditions significantly higher upstream, than their faster-growing counterparts.

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Abundant archaeal communities that included members of both Crenarchaeota and Euryarchaeota have been detected previously as a part ov various planktonic microbial communities (Crump and Barros 2006, Galand et al. 2006; Herfort et al. 2009) from arctic to tropical rivers. Those observations indicate that Archaea may play a substantial role in the functioning of the river microbial community, although, with the exception of a handful of physiological groups, such as methanotrophs (Orphan et al. 2001) or ammonia oxidizers (Francis et al, 2005), the link between phylogeny and physiology of the free-living archaea remains to be studied.

Archaeal community, just as the bacterial one is known to be influenced by anthropogenic factors (Cao et al. 2012). Such influence, coupled with the ubiquitous presence of those organisms throughout the course of the river suggests their utility as indicator organisms for detecting environmental changes, independently or in connection with the traditional eubacterial community analysis.

The dramatic differences in eubacterial and archaeal community variations among the sites suggests that traditional monitoring of the eubacterial community for the purpose of detecting and assessing environmental change may not present a full picture of environmental response. Our findings suggest that both archaeal and eubacterial communities must be monitored, as the former may respond to stimuli the latter is indifferent to (as in our work); theoretically, the reverse situation is also possible.

ACKNOWLEDGEMENTS This work was supported in part by the University of Houston-Victoria Office of the Provost Junior Faculty Summer Research Grant to author. Matthew R. Boyett completed most of the sample and data collection. Data processing, image manipulation and poster production was accomplished by use of free open source software; authors are indebted to Ubuntu, Open Office, MEGA and GIMP development communities.

REFERENCES Cao, H., Hong, Y., Li, M., and Gu J.-D. (2012) Community shift of ammonia-oxidizing bacteria along an anthropogenic pollution gradient from the Pearl River Delta to the South China Sea. Appl. Microbiol. Biotechnol., 94:247-259 Crump, B. C. and Baross J.A. (2000). Archaeaplankton in the Columbia River, its estuary and the adjacent coastal ocean, USA. FEMS Microbiol. Ecol., 31: 231–239 Dahllöf, I. (2002) Molecular community analysis of microbial diversity. Curr. Op. Biotechnol., 13:213-217 Delbès, C., Moletta, R. Godon and J.-J. (2001) Bacterial and archaeal 16S rDNA and 16S rRNA dynamics during an acetate crisis in an anaerobic digestor ecosystem. FEMS Microbiol. Ecol., 35:19-26. doi: 10.1111/j.1574-6941.2001.tb00784.x DeLong E.F. (1998) Archaeal means and extremes. Science, 280:542-543

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Francis, C. A., Beman, J.M and Kuypers M.M.M. (2007). New processes and players in the nitrogen cycle: the microbial ecology of anaerobic and archaeal ammonia oxidation. ISME J., 1:19-27 Francis C.A., Roberts K.J., Beman J.M., Santoro A.E., Oakley B.B. (2005) Ubiquity and diversity of ammonia-oxidizing archaea in water columns and sediments of the ocean. Proc. Natl. Acad. Sci. 102:14683–14688 Fuhrman, J. and Davis A. (1997) Widespread Archaea and novel Bacteria from the deep sea as shown by 16s rRNA gene sequences. Mar. Ecol. Prog. Ser., 150:275-285 Galand, P.E., Lovejoy, C. and Vincent W. F. (2006) Remarkably diverse and contrasting archaeal communities in a large arctic river and the coastal Arctic Ocean. Aquat. Microb. Ecol., 44-115-126 Griffiths, R.I., Whiteley, A.S., O'Donnell, A.G. and M.J. Bailey. (2000) Rapid method for coextraction of DNA and RNA from natural environments for analysis of ribosomal DNA- and rRNA-based microbial community composition. Appl. Environ. Microbiol., 66:5488- 5491 Herfort, L., Kim, J.-H., Coolen, M. J. L., Abbas, B., Schouten, S., Herndl, G. J. and Sinninghe Damste J. S. (2009) Diversity of Archaea and detection of crenarchaeotal amoA genes in the rivers Rhine and Têt. Aquatic Microbial Ecol., 55: 189-201 Herndl, G.J., Reinthaler, T., Teira, E., van Aken, H., Veth, C., Pernthaler, A. and Pernthaler J. (2005) Contribution of Archaea to total prokaryotic production in the deep atlantic ocean. Appl. Environ. Microbiol., 71: 2303-2309 Hori, T., Haruta, S., Ueno, Y., Ishii M. and Igarashi Y. (2006) Direct comparison of single- strand conformation polymorphism (SSCP) and denaturing gradient gel electrophoresis (DGGE) to characterize a microbial community on the basis of 16S rRNA gene fragments. J. Microbiol. Methods, 66:165-169 Jackson, C. R., Roden, E. and Churchill P. F.. (1998) Changes in bacterial species composition in enrichment cultures with various dilutions of inoculum as monitored by denaturing gradient gel electrophoresis. Appl. Environ. Microbiol., 64: 5046-5048 Kozdrój, J. and van Elsas J. D. (2000) Application of polymerase chain reaction-denaturing gradient gel electrophoresis for comparison of direct and indirect extraction methods of soil DNA used for microbial community fingerprinting. Biol. Fertility of Soils, 31:372-378 Muyzer, G., de Waal, E.C. and Uitterlinden, A.G. (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol., 59:695-700 Nguyen, K.B.T and Sobolev D. (2013) Enrichment of nitrous oxide reducing bacteria from coastal marsh sediments. Open J. Ecol., 3:296-300 Orphan, V.J., House. C.H., Hinrichs, K.-U., McKeegan, K.D., and DeLong E.F.. (2001) Methane-consuming Archaea revealed by directly coupled isotopic and phylogenetic analysis. Science, 293: 484-487 DOI: 10.1126/science.1061338 Siboni N, Ben-Dov E, Sivan A, and Kushmaro A (2008) Coral-associated ammonium oxidizing Crenarchaeota and their role in the coral holobiont nitrogen cycle. Proc. 11th Int Coral Reef Symp., Session 8:252–256

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Sobolev, D., Boyett, M.R. and E. Cruz-Rivera (2013) Detection of ammonia-oxidizing Bacteria and Archaea within coral reef cyanobacterial mats. J. Oceanogr., 5:591-600 Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M. and Kumar S. (2011) MEGA5: molecular evolutionary genetics analysis using likelihood, distance, and parsimony methods. Molecular Biol. and Evolution, 8:2731-2739 doi: 10.1093/molbev/msr121 Tibayrenc,M., Neubauer,K., Barnabé, C., Guerrini, F., Skarecky, D. and Ayala F.J. (1993) Genetic characterization of six parasitic protozoa: parity between random-primer DNA typing and multilocus enzyme electrophoresis. Proc. Nat. Acad. Sci., 90:1335-1339

Figure 1: Map of sampling locations. Arrows indicate sampling sites. Full extend of Goff Bayou not shown.

Prokaryotic Community Analysis In A Subtropical Coastal Plain River: Do Archaea and Bacteria Respond to Same Signals?

Figure 2: DGGE-based eubacterial community fingerprints. Principal bands are marked and numbered.

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Figure 3: DGGE-based archaeal community fingerprints. Principal bands are marked and numbered.

Prokaryotic Community Analysis In A Subtropical Coastal Plain River: Do Archaea and Bacteria Respond to Same Signals?

Figure 4: Relationship between the sites based on eubacterial (top) and archaeal (bottom) community fingerprints. Note different scale and different tree topologies.

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Figure 5: Total number of bands detected in bacterial and archaeal community fingerprints at various locations.

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JOURNAL OF APPLIED GLOBAL RESEARCH

IMPACT OF INTERACTIVE GAMES ON INTRINSIC AND EXTRINSIC MOTIVATION, ACHIEVEMENT, AND SATISFACTION

Yun Huang1 and Jianjun Yin2 1Nantong University, China and 2Jackson State University, USA

ABSTRACT eople who have played games have often experienced the process of being fully absorbed by the task, or Flow. Engaged students experience aroused pleasure that is synonymous with intrinsic motivation. This study (N=160) Plooks at whether the game-derived motivation continues to impact students’ interest toward the subject matter at the end of the course, and whether it impacts their extrinsic motivation. In several college level courses where learning technology is the focus in class, we found a significant difference between the students’ intrinsic motivation and achievement scores when they have had game-based activities in class as compared to traditional non-game-based learning activities. Authors discuss the corresponding implications, as well as the implications for our results showing no significant difference in the participants’ extrinsic motivation and course satisfaction.

Keywords: Interactive Games; Intrinsic Motivation; Extrinsic Motivation, Flow

INTRODUCTION Literature suggests that using games in learning can significantly increase learners’ level of engagement, interest, competitiveness, achievement, motivation, teamwork, and learning (Evans, Pruett, Chang, & Nino, 2013-2014; Lim, Nonis, & Hedberg, 2006; Herrington, Oliver, & Reeves, 2003; Prensky & Thiarajan, 2007; Ketelhut, Dede, Clarke, & Nelson, 2006; Azriel, Erthal, & Starr, 2005).

Often, the student is emotionally charged, thereby increasing retention and learning, even if only indirectly for students who are not conscious of that learning process can be difficult (Brehm & Self, 1989). According to Prensky and Thiarajan (2007), games not only support different learning styles, but also provide instructional coaching that help reinforce learning.

Researchers for decades synthesized why and how individuals are motivated in schools, work, sports, and other settings. The desire to experience competence and avoid experiencing

Impact of Interactive Games on Intrinsic and Extrinsic Motivation, Achievement, and Satisfaction incompetence, as well as for pleasure arousal, are inherent in human nature. People sometimes select to engage in certain activities for their inherent enjoyment and satisfaction of human needs for competence. Several researchers found that these pleasures and the feeling of fulfilment increases participants' intrinsic motivation (Cameron, Pierce, Banko, & Gear, 2005; Charoenying, 2010; Wang, Lockee, & Burton, 2011-2012).

Games provide the platform for people to experience pleasure, and feelings of competence, which lead to increased intrinsic motivation toward the gaming activity. To date, however, we are still not clear whether using interactive games in the classroom can lead to increased intrinsic motivation toward the subject matter, as well as increased course satisfaction. In other words, would students find the subject matter more “inherently” interesting and enjoyable as a result of playing interactive games in the class? Is there positive correlation between interactive games played in the class and the course evaluations? Finally, would they perform better in class? In this paper, we seek to clarify this relationship between games and the type of motivation that it develops, and ultimately achievement and satisfaction.

THEORETICAL PERSPECTIVES Csikszentmihalyi (1990) used the concept of “flow” to refer to mental processes that are fully absorbed in a task, characterized by personal experiences of concentration, energy and success. This framework has been used by some researchers (Konradt & Sulz, 2002; Lim, Nonis, & Hedberg, 2006) to explain the intrinsic motivation felt by students when they are immersed in the game-based learning environment. Based on this concept, we believe that interactive game-based learning can increase intrinsic motivation. However, whether “flow” transfers intrinsic motivation from the task to the subject matter has yet been systematically studied.

Csikszentmihalyi (1990) also believed that the point system used for rewarding players in these game-based environments is a form of feedback that enhances flow. Games often use a system of extrinsic achievement-based rewards, such as praise, promotion, recognition, or points, to motivate participants. The most commonly used in-class games convert popular TV games into interactive games, such as Jeopardy, Who wants to be a Millionaire, Wheel of Fortune, and Hollywood Squares. These games feature money, praise, and promotion as part of the play. Even in more complex simulation games, there is a system of external reward system that recognizes the success of the player. As a point of clarification, these “external rewards” are not tangible or intangible rewards given by teacher to students, such as candy, or extra credits; these rewards refer to the point system and praises that are inherently a part of the games. When participants demonstrate their subject matter learning and knowledge, they accumulate these points. As such, they are considered achievement-based rewards. Some studies have found that the use of external rewards actually decreased motivation for a task for which the student initially was motivated. Meta-analytic studies have concluded that rewards can lead to increased intrinsic motivation, if they are informational, and tied to their achievement or standards or goals (Deci, Ryan, &Keostner, 1999).

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In a line of research on achievement-based rewards, Cameron, Pierce, Banko, and Gear (2005) found that achievement-based rewards during learning or testing can increase participants’ intrinsic motivation. Although Cameron et al. (2005) did not use game-based learning in their research studies, we believe that the concept can be applied to interactive games, since the games offer participants rewards for success. In fact, some researchers think that intrinsic motivation increases as rewards are tied to increasingly demanding tasks (Pierce, Cameron, Banko, & So, 2003) – a very similar scenario in gaming where tasks often become increasingly demanding as players progress through stages.

As early as 1987, Marlone and Lepper have researched on fostering intrinsic motivation through learning environments to inform us on how digital games could affect intrinsic motivation. Marlone and Lepper (1987) used the addictive nature of computer games as a platform to suggest that intrinsic motivation can be fostered through learning environments that encourage challenge, curiosity, fantasy, and control. Their taxonomy leads us to believe that the use of digital games could promote these factors, thus increase intrinsic motivation. However, Marlone and Lepper’s studies suggest that people are intrinsically motivated to play computer games, but did not specify whether the use of game-based learning was able to sustain intrinsic motivation toward the subject matter.

In more recent studies, literature has consistently showed a positive correlation between playing games in class and students’ achievement (Huizenga, Admiraal, Akkerman, & Dam, 2009; Tuzun, Yilmaz-Soylu, Karakus, Inal, & Kizilkaya, 2009), but has not shown consistency in predicting games’ impact on students’ intrinsic and extrinsic motivation to learn. In one study, Huizenga, Admiraal, Akkerman, and Dam (2009) found that students who used mobile games in classes performed significantly better than those who engaged in project-based instruction, though their motivation for the subject matter was not significantly different. In another study on game-based activities on primary school students’ achievement and motivation (Miller, Shell, Khandaker, & Soh, 2010-2011;Tuzun, Yilmaz-Soylu, Karakus, Inal, & Kizilkaya 2009), it was found that game-based environment increased students’ achievement, and intrinsic motivation, and interestingly, decreased students’ extrinsic motivation to learn geography. Particularly, the students had decreased their focus on getting grades.

In this study, we are curious as to whether playing interactive games during the learning process can lead to students becoming inherently interested in the subject matter, or whether students remain extrinsically motivated. We contend that since game-based learning utilizes achievement-based rewards and increases flow, it will ultimately lead to increased intrinsic motivation, as well as achievement, and course satisfaction.

While the effects of educational games in classes are well studied, there is little attempt made in researching game-based learning, especially in the higher education (Ebner & Holzinger, 2007). This study takes some of the most popular and easily available games on the internet, such as Jeopardy, and proposes that the use of these games in class would increase students' motivation to learn, their course satisfaction, and learning achievement in comparison with

Impact of Interactive Games on Intrinsic and Extrinsic Motivation, Achievement, and Satisfaction non-game based tasks. These games are chosen for a number of reasons. Not only do they have widespread popularity, but they can also be easily brought into the classroom due to the accessibility of the internet and other application software. It is conceivable for most classrooms to be able to access these materials on the internet, and to align them with specific lesson objectives. In addition, they have clearly structured achievement-based rewards built into the games in terms of the points and praises that participants can accumulate through demonstrating that they have learned the subject matter.

The research is conducted in four different undergraduate level classes. Traditionally, students from these classes have used lecture, group projects, class discussions, and individual assignments as learning activities. With the consistent use of more well-designed, interactive games which are aligned with course objectives, we believe that it would increase students' motivation to learn, their course satisfaction, and achievement in comparison with more traditional class assignments. Therefore, we propose the following research questions:

1) What are the effects of interactive game-based learning on students’ intrinsic and extrinsic motivation to learn? 2) What are the effects of interactive game-based learning on students’ achievement? 3) What are the effects of interactive game-based learning on students’ overall satisfaction with the course?

METHOD This study utilizes a quasi-experimental design involving four undergraduate classes, two of which are treatment groups, and the other two are control groups. The control group received traditional forms of in-class assignments such as worksheets or class discussions. The treatment groups received various interactive games specifically designed for student learning aligned with course objectives. The participants received four interactive game activities during the second half of the semester. These treatments were given in computer labs after each chapter was covered by the instructors.

The participants of this study were chosen from four undergraduate classes in two subject areas: Management Information Systems from Business College (65 students) and Computer Technology/Instructional Media from educational college (40 students), at the mid-sized state university in southeast United States. These two courses cover somewhat similar contents in that both classes cover topics related to application of computer and information technology. However, the emphases were placed on different fields; business in the MIS classes whereas teaching for instructional technology classes.

At the beginning of the semester, participants were asked to rate their expectation of the course on several aspects (measure by 7-point Likert scale) and rate their motivation level to learn the subject. Academic Motivation Scale (AMS) was adopted (Vallerand, Pelletier, Blais, Briere, Senecal, & Vallieres, 1992) and modified to measure students’ motivational state. The AMS (Vallerand et al., 1992) is a 28-item scale designed to assess autonomous and extrinsic 48

Y. Huang and J. Yin JAGR - Volume 7, Issue 20 (2014), pp. 45-54 regulatory styles. It intends to measure seven underlying constructs of motivation: three types of intrinsic motivation (to experience stimulation, to know, and to accomplish), three types of extrinsic motivation (identified regulation, introjected regulation, external regulation), and amotivation. Extra question regarding overall motivation was added and rated on the same 7- point Likert scale.

Satisfaction was measured at the end of the semester. The survey used multi-items adapted from Kleen & Shell (2001). Participants responded to each statement on a 7-point Likert scale. The pre-test and post-test are composed of 30 true and false and multiple choices questions. Half of the questions (15) were identical for all 4 sections, and the other half was course content-specific. We conducted a t-test on pre-test scores to check differences in students’ basic computer-related knowledge competency. The test shows that there was significant difference in two groups (t (103)=2.45, p=.02): the mean pre-test score of business classes was 18.25 (SD=.57) whereas that of education classes was 16.20 (SD=.51). This was an expected result because business class is upper level class with computer related pre-requisite while the education class is lower level class without any pre-requisite.

The motivation survey was conducted twice for each class, before and after the treatment of interactive games. At the end of the semester, we collected data on student satisfaction, and achievement score. These are compared across groups to see the treatment effect (interactive games).

RESULTS From the original data set of 199, thirty nine (39) influential points were removed, resulting in 160 valid data. Missing data were replaced with series means.

The results of factor-analysis (Principle Component Analysis with varimax rotation) on AMS suggested a 3 factor model. Eigenvalue over 1 was used for cutoff points for the decision. This model explained 70% of total variance of motivation. KMO measure of adequacy was .89 showing the data were appropriate for factor analysis. Eleven (11) ambiguous and cross loaded items were removed, and17 items were retained for final model. Those 17 items are presented in Appendix1. All three motivational factors showed acceptable reliability, with Cronbach’s alpha value of 0.89 or above. Factor scores were retained using regression method. Retained factor scores were used for further t-tests, to determine the impact of interactive games. Result of EFA is presented in Table 1.

Impact of Interactive Games on Intrinsic and Extrinsic Motivation, Achievement, and Satisfaction

Table 1: EFA Results

Item Extrinsic Intrinsic Amotivation EX1 .852 EX2 .817 EX3 .803 EX4 .770 EX5 .740 EX6 .772 IN1 .793 IN2 .792 IN3 .745 IN4 .725 IN5 .704 IN6 .669 IN7 .535 AM1 .905 AM2 .902

AM3 .879 AM4 .860 Eigenvalues 7.047 3.495 1.352 % of variance explained 26.177 23.849 19.946 Cronbach’s Alpha .916 .887 .919 Note: EX refers to extrinsic motivation, IN refers to intrinsic motivation, and AM refers to amotivation.

Next, a series of paired t-test was conducted to examine if playing interactive games would affect students’ intrinsic, extrinsic, and overall motivation to learn about the subject. Secondly, another paired t-test was conducted on pre and post test scores in order to examine the impact of interactive games on students’ achievement. Finally, students’ satisfaction with the course was accessed using t-test. See Table 2 for the results of paired t-tests.

Table 2: T-test Results Mean score after playing Mean score before playing games games t-value N Mean Intrinsic motivation 3.28** 77 .349 -.2998 Extrinsic motivation 1.04 77 .078 -.0668 Overall motivation 2.15* 78 5.79 5.42 Post-Pre test scores 3.20** 72 22.94 17.31 Satisfaction 3.18 (0.73) 78 5.77 5.70 *p<.05, **p<.01, ***p<.001

The results show that interactive games significantly increased students’ intrinsic motivation, t=3.281, p<.01 as well as overall motivation, t=2.15, p<.05. Interestingly, however, the

Y. Huang and J. Yin JAGR - Volume 7, Issue 20 (2014), pp. 45-54 increase in the amount of extrinsic motivation was not statistically significant for treatment and control groups.

In addition, a paired t-test on students’ post and pre test scores showed that playing interactive games has a significant impact on student achievement score, t= 3.20, p < .01. However, there was only a marginal increase in students’ overall satisfaction due to playing interactive games, t=1.81, p=0.73. The difference was not statistically significant.

DISCUSSION Our findings corroborate previous studies that also showed the impact of game-based learning on students’ intrinsic motivation toward the subject matter. The games inherently have a system that rewards achievement, leading to Flow, a state in which learners are fully absorbed by the goals of the activity – to learn the subject matter. In this state, the learners are engaged in the subject matter because they find intrinsic pleasure in doing so. The fact that the participants’ intrinsic motivation toward subject matter is significantly higher) after game-based learning activities suggests that there is a very direct and close tie between participants’ flow during the game and their motivation toward the subject matter. In other words, the flow that they experience during the interactive games is not limited to the game environment, but is extended or transferred onto the subject matter.

Our results are contrary to some studies. For example, Tuzun et al. (2009) suggested that mobile games do not increase motivation. Perhaps the difference between digital computer- based games, and interactive game-based classroom activities is much more significant than the literature suggests. This is reasonable, given that the two environments are drastically different. The interactive games used in our study are different from other computer-based games because the game or the “action” happens in the actual classroom as opposed to the “action” happening on the computer in most digital games. This difference might have caused one to be more closely associated with the subject matter than the other. Another reason may be the interactive and collaborative nature of our games versus the ones used in other studies. Future studies will have to research this more closely to be more definitive in explaining the difference.

Consistent with most other literature, our study shows that there is a significant increase in students’ test scores when treated with game-based learning activities. There seems to be a direct link between the increase in intrinsic motivation and the increase in students’ achievement. As suggested by the flow theory, students can become so engaged and involved in the activities that they can forget about time; and they can take so much pleasure in learning the subject that they could learn more than they otherwise would have.

What was interesting was the extrinsic motivation remained about the same. Even though much of the motivation driven by the games could be arguably more extrinsic in nature, changes in participants’ extrinsic motivation remained statistically insignificant despite the treatment. This substantiates literature on achievement based rewards, which have been

Impact of Interactive Games on Intrinsic and Extrinsic Motivation, Achievement, and Satisfaction theorized to increase students’ intrinsic motivation. The achievement based rewards that the participants experienced while playing those games have likely increased their pleasure toward the subject matter, but have made no difference in their extrinsic motivation toward the subject matter. It is highly probable that the students’ increased pleasure toward the subject matter does not change the likelihood that the subject matter may offer them extrinsic rewards, such as finding a better job in the future or graduating from college. This suggests that intrinsic motivation is not the opposite of extrinsic motivation, but rather, they operate on separate continuums.

Although the participants of games were more intrinsically motivated toward the subject matter, their course satisfaction with the course was not statistically different than the non-game-based counterpart. The mean increased from 5.70 to 5.77, but this increase was not statistically significant at the 0.05 level. This suggests that increase in overall motivation may not be correlated with higher course satisfaction scores. In fact, one might argue that students who are more motivated take more interest in the subject matter and are likely to be more critical during course evaluations, or pay more attention to instructor’s organizational skills or personality, as opposed to those who are less interested in the subject matter. Again, this is another area for future research.

CONCLUSION Literature has established that games can be a very powerful tool in increasing student engagement and motivation. This study has attempted to fill in some gaps by finding out the type of motivation that game-based learning fosters, and whether the motivational results can be generalized or transferred to the learning of the subject matter, and whether that ultimately result higher achievement scores and course satisfaction. Currently, there is limited research in this area, especially in the higher-education classrooms (Ebner & Holzinger, 2007).

The empirical evidence from this study provides some insight this topic by suggesting that intrinsic motivation derived from digital games does generalize to the learning of the subject matter. In addition, our results support the literature that has expounded on the benefits of interactive game-based learning. Further, our results validate the use of practical and easily obtainable interactive games for learning, by showing that they could result in significantly higher achievement scores. These results are likely to be highly relevant to other researchers and educators.

REFERENCES Azriel, J A.; Erthal, M. J.; Starr, E. (2005). Answers, Questions, and Deceptions: What Is The Role of Games In Business Education? Journal of Education for Business, 81(1), 9-14. Brehm, J. W. & Self, E. A. (1989) The Intensity of Motivation. Annual Review of Psychology, 40, 109-131

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Cameron, J., Pierce, W. D., Banko, K. M., & Gear, A. (2005). Achievement-based rewards and intrinsic motivation: a test of cognitive mediators. Journal of Educational Psychology, 97(4), 641-655. Charoenying, T. (2010). Accountable game design: Structuring the dynamics of student learning interactions. Journal of Educational Computing Research, 43 (2), 135-163. Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York: Harper and Row. Ebner, M., and Holzinger, A. (2007) Successful implementation of user-centered game-based learning in higher education: An example from civil engineering. Computers and Education, 49(3), 873-890. Evans, M. A., Pruett, J., Chang, M., & Nino, M. (2013- 2014). Designing personalized learning products for middle school mathematics: The case for networked learning games. Journal of Educational Technology, 42 (3), 235-254. Huizenga, J.; Admiraal, W.; Akkerman, S.; Dam, G. ten (2009) Engagement, Motivation and Learning in a Mobile City Game. Journal of Computer Assisted Learning, 25 (4), 332-344. Herrington, J., Oliver, R. & Reeves, T.C. (2003). Patterns of engagement in authentic online learning environments. Australian Journal of Educational Technology, 19(1) 59-71. Ketelhut, D. J., Dede, C., Clarke, J., & Nelson, B. (2006). A multi-user virtual environment for building higher order inquiry skills in science. Paper presented at the American Educational Research Association, San Francisco, CA. Kleen, B., & Shell, W. L. (2001). Servqual-based measurement of student satisfaction with classroom instructional technologies: A 2001 update. Proceedings of the 16th Annual Conference of the International Academy for Information Management, New Orleans, LA., 226-235. Konradt, U. & Sulz, K. (2001). The experience of flow in interacting with a hypermedia learning environment. Journal of Educational Multimedia and Hypermedia, 10(1), 69-84. Lim, C. P., Nonis, D., & Hedberg, J. (2006). Gaming in a 3D multiuser virtual environment: engaging students in Science lessons. British Journal of Educational Technology. 37(2), 211-231. Marlone, T. W., & Lepper, M. R. (1987). Making Learning Fun: A Taxonomy of Intrinsic Motivations for Learning, in Aptitude, Learning and Instruction: III. Conative and affective process analyses, In Snow, R.E. and Farr, M.J., (Eds.) Erlbaum: Hilsdale, NJ. P. 223-253. Miller, L. D., Shell, D., Khandaker, N., & Soh, L. (2010-2011). Teaching using computer games. Journal of Educational Technology Systems, 39 (3), 321-343. Pierce, W. D., Cameron, J., Banko, K. M., & So, S. (2003). Positive Effects of rewards and performance standards on intrinsic motivation. Psychological Record, 53, 561-579. Prensky, M., & Thiagarajan, S. (2007). Digital Game-Based Learning. St. Paul, MN: Paragon House. Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68-78. Tuzun, H., Yilmaz-Soylu, M., Karakus, T. Inal, Y., Kizilkaya, G. (2009). The effects of computer games on primary school students’ achievement and motivation in geography learning. Computers & Education, 52 (1), 68-77.

Impact of Interactive Games on Intrinsic and Extrinsic Motivation, Achievement, and Satisfaction

Vallerand, R. J., Pelletier, L.G., Blais, M. R., Briere, N. M., Senecal, C., & Vallieres, E. F. (1992). The academic motivation scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52, 1003-1017. Wang, F., Lockee, B. B., & Burton, J. K. (2011-2012). Computer game-based learning: Perceptions and experiences of senior Chinese Adults. Journal of Educational Technology System, 40 (1), 45-58.

APPENDIX Extrinsic Motivation EX1 Because eventually it will enable me to enter the job market in a field that I like. EX2 In order to obtain a more prestigious job later on. EX3 In order to have a better salary later on. EX4 Because this will help me make a better choice regarding my career orientation. EX5 Because without knowing information technology I would not find a high-paying job later on. EX6 Because I believe that learning information technology is will improve my competence as a worker.

Intrinsic Motivation IM1 For the intense feelings I experience when I am communicating my own ideas to others. IM2 For the pleasure I experience while surpassing myself in my studies. IM3 For the pleasure that I experience while I am surpassing myself in one of my personal accomplishments. IM4 Because I experience pleasure and satisfaction while learning new things. IM5 For the pleasure that I experience in broadening my knowledge about subjects which appeal to me. IM6 For the pleasure that I experience when I feel completely absorbed by what certain authors have written. IM7 For the "high" feeling that I experience while reading about various interesting subjects.

Amotivation AM1 I don't know; I can't understand what I am doing in this class. AM2 I can't see why I am going to the class and frankly, I couldn't care less. AM3 I once had good reasons for going to the class; however, now I wonder whether I should. AM4 Honestly, I don't know; I really feel that I am wasting my time in this class.

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Full Article Available Online at: Intellectbase and EBSCOhost │ JAGR is indexed with Cabell’s, JournalSeek, etc.

JOURNAL OF APPLIED GLOBAL RESEARCH

VIRTUAL COMMUNICATION IN BUSINESS

V. Joy Rose Saint Leo University, USA

ABSTRACT ommunication is the heart of a business. Today, we have many different ways in which we communicate. One of those ways is virtual communication. Define what C is necessary for management to act as change agents to bring the organization into communicating on a virtual scale. Examine and demonstrate effective communication as it relates to virtual versus brick and mortar establishments. According to the American Heritage Dictionary of the English Language, information technology is defined as “The development, installation, and implementation of computer systems and applications” (2000). Information technology (IT), is further defined in the World Economic Outlook as “…computers, computer software, and telecommunications equipment” (2001, p. 105). IT enables consumers and businesses to do things that were impossible even in the recent past, but recent history is also replete with examples of failures to understand the real benefits of new information technologies. There is also a mix of evidence on how information technology affects social behavior (Thompson & Nadler, 2002).

Keywords: Internet, World Wide Web, Virtual, Technology, Information Technology (IT).

INTRODUCTION The new "Information Age," is changing the structure of businesses worldwide. New communication technologies are causing businesses to change in many aspects: location requirements, protocol, interpersonal relationships, training and many other aspects, down to the smallest details. Communication innovations are rapidly infiltrating business and just as rapidly being adopted and replacing older methods.

There are advantages and disadvantages to this influx of new technology. As with most innovations, it takes time to discard the old methods and adjust to the new methods. Often during the transition period problems arise that need to be addressed and resolved.

With the advent of cellular phones, faxes, e-mails and personal computers companies are focusing on how to use the new technology properly to obtain the best results.

Virtual Communication in Business

Several trends have emerged in recent years due to the rise in communications technology, changing the face of the traditional businesses, which brought workers together in groups to achieve the company's purpose.

Location requirements for many businesses today have changed. The new technology has allowed some businesses to decentralize, having a smaller central office with corresponding units in separate areas. New communication tools, such as video conferencing, e-mail and the Internet enable teams to correspond without the need to physically meet. This reduces the cost of meetings and saves time, which is often correlated to spending money (Amor, 2004).

BACKGROUND AND OVERVIEW Today, the trend is clear that there is an explosion in growth of peer-to-peer applications to facilitate online communications. These new technologies, for example, will allow customers to not only access businesses via computers, wireless customers could access potentially access a Web site from a Nintendo machine, a personal digital assistant (PDA), or a pager. Similarly, people may communicate directly with companies via satellite. High-speed, broadband networks will allow users to transmit enormous amounts of data to each other, including audio and moving images. Dearstyne says it is this capability which will help to improve peer-to-peer communication, which will in effect serve to ultimately reduce the input companies and their Web servers have in the communication loop. From this perspective, information technology may be considered as a potentially enormous driver of change, but the challenge is to identify the social responsibilities of the software engineers involved, and to ensure these considerations are incorporated into the design from the outset. In this rapidly changing and growing environment, it is important to develop an understanding of the level of technical versus human support needed in an online community. Dearstyne adds that the labor required to support a rapidly growing online community and maintain quality interactions is intense and represents one of the biggest challenges to companies seeking effective IT alternatives. Therefore, all companies must make arrangements for appropriate training for the IT functions deemed priorities, with such training being accomplished in-house if possible or outsourced if necessary. As a result, well-established enterprises whose brand names are consistently associated with efficient, reliable service are being viewed as even more desirable among up- and-comers as well as seniors in the United States today.

Among younger consumers, this advantage may represent little more than a “foot in the door”; however, as time for shopping continues to diminish in the future, e-commerce will clearly have a growing advantage over many types of traditional brick-and-mortar stores. Furthermore, the types of transactions that companies can undertake in an e-commercial environment are virtually the same as in its traditional brick-and-mortar outlets, including payment, with the sole exception of “cash-and-carry” order fulfillment that are otherwise addressed in an brick-and- mortar approach.

Any type of e-commerce sales channel generally includes all of the traditional elements required to conduct business in a brick-and-mortar establishment such as marketing, customer

V. Joy Rose JAGR - Volume 7, Issue 20 (2014), pp. 55-67 services, credit card arrangements, and so forth; however, the virtual enterprise must also have the following elements to conduct e-commerce:

 A product.  A place to sell the product - in the e-commerce case a web site displays the products in some way and acts as the place.  A way to get people to come to the web site  A way to accept orders (normally an on-line form of some sort).  A way to accept money (normally a merchant account handling credit card payments).  A fulfillment facility to ship products to customers.  A way to accept returns.  A way to handle warrantee claims if necessary.  A way to provide customer service (Brain, 2001).

In their article, “E-Loyalty: Your Secret Weapon on the Web,” Frederick Reichheld and Phil Schefter write, “In the rush to build Internet businesses, many executives mistakenly concentrate all their attention on attracting customers rather than retaining them. But chief executives at the cutting edge of e-commerce--from eBay's Meg Whitman to Vanguard's Jack Brennan--know that customer loyalty is an economic necessity: acquiring customers on the Internet is very expensive, and unless customers stick around and make lots of repeat purchases, profits will remain elusive” (Reichheld & Schefter, 2000). These authors studied e- loyalty over a 2-year period and determined that, contrary to the popular perception that on-line customers are fickle by nature, they found that most of today's on-line consumers exhibit a clear proclivity toward loyalty, and Web technologies, if used correctly, reinforce that inherent loyalty (Reichheld & Schefter, 2000). In this article, the authors explain how the enormous advantages of retailing on-line can benefit buyers and describe what Grainger, Dell, America Online, and other Internet leaders are doing to secure their customers' trust and earn their loyalty.

Recognizing that existing customers are a great deal easier to keep than recruiting new ones, these authors point out that by encouraging repeat purchases among a core of profitable customers, companies can initiate a spiral of economic advantages. This on-going e-loyalty effect provides these companies with the ability to compensate their employees more generously, provide investors with superior cash flows, and reinvest more aggressively to further enhance the value delivered to customers (Reichheld & Schefter, 2000). As Internet users gain greater online experience, they also become more demanding in their expectations of website capabilities. In several of the surveys followed by eMarketer, website visitors consistently indicated their preference for websites that are easy to navigate, with a minimum of distracting or self-serving content. The e-commerce industry continues to experience the effects of rapid growth combined with changes in how consumers view the medium and technological advances which make it even easier for people to shop online. Further, many businesses are taking advantage of these advances to improve their ability to deliver goods and services in a timely and efficient manner. In their analysis, “How IT Enables Productivity 58

Virtual Communication in Business

Growth,” McKinsey & Company points out that in an environment of economic uncertainty, skepticism about the new economy, and stingy capital spending, managers need to know how IT does (and does not) enable managerial innovation of the sort that drove productivity growth in the U.S. during the 1990s. “IT's role was important for productivity growth but was no silver bullet. IT's impact, rather, has been diverse and complex depending on when, where, and how it has been deployed” (How IT Enables Productivity Growth, 2003). Competitive advantage through the application of various information technologies in isolation from other marketing techniques, though, is clearly difficult or impossible to sustain. “However, IT investments can be effective when coupled with advantages of scale, proven business processes, and the ability to apply learning from one IT project to the next” (How IT Enables Productivity Growth, 2003, p. 3).

IDENTIFYING APPLICATION AND FUNCTION PRIORITIES According to Yi (2002), enterprise resource planning (ERP) systems provide two applications that traditional IT systems do not. The first aspect is that ERP systems link standalone systems into an integrated whole in order to share information. For example, the procurement component can check to make sure that a purchase request has sufficient funds in the account to purchase the system. On the other hand, the human resource system is allowed to pull data from the budget component to assure that all positions are budgeted prior to hiring a new employee. Therefore, through an integrated system, public officials and managers can make more informed, timely, and accurate decisions based on a comprehensive view of the organization.

The second aspect is that ERP’s also connect standalone departments; for instance, many governmental agencies have independent units that often work independent of other units. A local government redevelopment agency is an example of such an independent unit. By linking all component units of an agency through ERP, it would be reasonably expected to provide managers with more centralized control over the various components through financial and process controls and uniform policies and procedures. According to Yi (2002), ERP programs have both risks and concerns relative to its use. One worry is that it can be an expensive program to implement. The cost of implementation is generally separate from the software cost. A risk involved in the program is the amount of custom code built into the architecture. The more custom code, the more difficult and costly it is to maintain, operate, and upgrade.

DEVELOPING EFFECTIVE STRATEGIES FOR PRIORITIZING THE IT PROJECTS All types of businesses today are faced with the challenges and opportunities represented by emerging information technologies. According to Vancelette (2002), all types of business, organization or enterprise, large or small, profit making or not-for-profit, are simply processes that can be understood, evaluated and changed for the better when needed. In process management, transformed resources in operations are viewed as being some mixture of

V. Joy Rose JAGR - Volume 7, Issue 20 (2014), pp. 55-67 materials, information and customers. The important issue to keep in mind, though, is that most types of operation process all three types of transformed resource with one generally being the most important.

The assumed benefits of IT strategy formulation are better alignment with business needs, gaining of top management support and involvement, improved setting of priorities, more efficient budgeting and distribution of resources, and overall competitive advantage (Earl 1990; Ward et al., 1990). Many organizations claim to have their own approaches to the creation of business and IT strategies (Premkumar & King 1991). While the methods used to develop strategic plans vary in their details, the first step is the identification of a firm's business objectives and corporate strategy (O'Connor, 1993). For instance, a fundamental principle of strategic information planning is “if the business objectives do not change then the data the organization needs to use and the functions it needs to carry out will not change . . . therefore we can model the enterprise” (Goldsmith, 1991, p. 70). If no strategy is apparent, corporate planners are advised to create one (Remenyi, 1991).

Prioritizing the IT function therefore requires a careful assessment of which IT components are regarded as being the most important to the respective internal and external customers who are actually going to be using the system. For instance, if email is reported to be an overwhelming criterion for a successful IT application by a majority of the university’s customers, this should be given a high degree of priority within the IT goals. According to Mansell and Wehn (2000), email is simply an electronic transmission and reception of text based message, with attachments being included if they are required or desired. Email is “Computer-based messaging. The transmission of letters and messages from computer to computer over a network” (p. 276). Email uses an email gateway to communicate, which is generally a personal computer (PC) that is being operated on a local area network (LAN) (Mansell & Wehn, 2000).

The PC usually has one or more modem and/or fax/modem cards that are used to facilitate online communications. Computers employ these cards to send or receive e-mails and faxes for everyone who uses the LAN. The most popular email protocols today are the Simple Mail Transfer Protocol (SMTP) and the Post Office Protocol 3 (POP3). These protocols enable the server to send and route text messages over the Internet; further, the POP3 is beneficial for offline Email usage. Another important e-mail protocol is the Internet Mail Access Protocol (IMAP4). This protocol provides users with the ability to access their e-mail on the server ass if they are having local access. ECDN is an application network that allows firms high-speed access to deliver static, streaming, and dynamic content to the end-users. These types of deliveries must be performed over secure networks, in a reliable and scalable fashion (Vancelette, 2002).

Based on the needs identified in any similarly situated institutions, the following functions can therefore be assumed to be the most desirable and necessary for a company’s IT function: 1) email; 2) intranet; 3) ERP.

Virtual Communication in Business

All of these major projects can be evaluated by applying the following criteria:

1. The project drives (or creates) more revenue for the corporation. 2. The project cuts the cost of doing business. 3. The project is mandated by federal, state, county, or local laws or executive orders. 4. The competitor has undertaken a similar project.

This type of evaluation will help almost any type of company identify its priorities, but email would be a high priority for almost any enterprise given its cost-effectiveness and ease of use by almost anyone. The ability to transfer documents and data in a virtually instantaneous manner makes this an indispensable part of any IT function. The intranet function will likely come in a close second, but there will be constraints involving the added expense of purchase, implementation and training involved in this component. Finally, the ERP function could be viewed as potentially the most valuable IT function for almost any type of business, but this would be long-term since there would be a transition period involved that would make this function the most complicated and expensive of these IT initiatives.

While the overall picture for pure Web-based retailing is fairly grim, the grimness varies a great deal by the industry involved. For the most part, it would appear that total performance gains enabled by IT have clearly outweighed the costs involved. Clearly, though, the results from IT investments could be much better in many cases. While some 80 percent of the companies interviewed in an NRC study believed that they had received anywhere from adequate to high returns from IT performance, less than 30 percent demonstrated that they had actually thoroughly developed IT strategies. More than 70 percent of the surveyed companies had customer-based metrics for measuring quality performance, but these companies were unable to convert them into true financial measurements. Likewise, a number of companies also admitted that they made early errors by not reengineering various processes prior to installing IT, but this shortsightedness was rectified in most cases (Bailey & Quinn, 1997).

More than 50 percent of the companies had experimented with new organizational forms at the time they implemented their new IT systems; however, few of them had followed through completely by developing new performance measurement and reward systems in support of those expensive IT investments. Furthermore, in spite of the current inability to measure in financial terms the productivity growth caused by IT use, both in government and in industry, by nearly all accounts, IT has facilitated performance in service-based companies in profound ways. While many companies are still far from perfect in achieving their implementation of IT in their organizations, better managed companies evaluate and allocate IT investments in ways that appear very comparable to those that are used for other technologies and in other industries (Bailey & Quinn, 1997).

V. Joy Rose JAGR - Volume 7, Issue 20 (2014), pp. 55-67

IMPLEMENTATION OF IT INNOVATIONS Effective IT solutions will ultimately provide managers with more timely information for decision-making purposes. Some examples of IT innovations include installation of a new human resource information system or a materials requirements planning system (Krumwiede & Roth, 1997). In order to successfully implement any IT innovation, though, corporate leaders must gain an understanding of the stages of the implementation process. Various organizational change models have been proposed, with a notable stage model having been refined to describe specific instances of best practices in IT innovation (Cooper & Zmud, 1990). These authors’ proposed stages for IT implementation are classified as follows:

(1) Initiation. This stage of the initiation process begins when there is either external or internal pressure to change an existing system or function. This pressure leads to analyzing organizational problems and possible solutions. Most companies do not consider changing major systems very easily or very often. Generally, someone from upper management ends up driving the change because of a belief that a particular information need is not being met.

The initiation stage may also be generated by someone who is lower in the organization, someone who may be more intimately familiar with various system limitations or possible solutions. Assuming that there are good reasons for a firm to desire a better IT system, there also must be a sense of urgency to provide the impetus to go through the effort and expense of making a change.

(2) Adoption. When an agreement has been reached that the new IT innovation is a potential solution for a company's unique set of needs, the next step is to gain approval and negotiate for the resources required for implementing the system. In this stage, proponents’ campaign for the resources needed to implement the change. This stage of development requires a "champion" in the top management echelon, someone that has significant budgetary and organizational influence and who can (and will) push the project forward and secure the necessary funding and cooperation from this associates.

(3) Adaptation. Once the resources are approved and secured, IT implementation enters the adaptation, or analysis stage. In this stage, the implementation team studies the resource costs and links them directly to activities and cost objects (e.g., products, customers, etc.). The team's focus should be on identifying the drivers for overhead costs. Standard TQM (Total Quality Management) principles of teamwork, customer satisfaction, and process analysis are helpful at this stage.

The organization should be divided into self-managed teams made up of information users and information providers for a given process that will be affected by the IT innovation. Team members must have the time and training that is required to document, measure, and improve

Virtual Communication in Business upon the process being addressed. A critical barrier that can arise at the analysis stage is a failure to clearly define the objectives and scope of the project.

An elaborate and well-designed new IT process will not be used if it provides information that is irrelevant to management. Clearly defining the objectives and scope of the IT project very early in the analysis stage is an essential factor for implementation success. Another barrier at the analysis stage can be the complexity of many business processes. Many cost drivers may be identified by the team members, but if too many drivers are used, the model quickly becomes too complicated for easy understanding.

(4) Acceptance. At the acceptance stage, members of the organization are induced to commit to use the new IT innovation. The goal of this stage is to get key decision makers to agree that the relevant IT information should be used in their decisions. Acceptance will absolutely not occur if these individuals do not understand or agree with the information. The key to overcoming barriers at this stage is to educate managers and employees about the value of the new system. Specific data must be provided to upper management and key information users in order to illustrate that the new IT system meets the original objectives.

(5) Routinization. During this stage of implementation, the usage of the IT innovation takes place as an everyday, normal activity. The routinization (or action) stage occurs when the IT system finally begins making an impact in an organization. The cost model is accepted by at least a few key managers, who start to consider it a normal part of the company's management information system.

The most significant barrier to achieving the action stage is gaining overall acceptance of the model. Once this is achieved, there are still a few roadblocks to overcome. If new information is added to what is already available, users of the information may suffer from "information overload." Additionally, information providers may not be able to handle the extra maintenance requirements of the new system.

Another common reason cited by these authors for lack of action based on IT information is that the environment is altered after the adoption or analysis stages. If a company is suddenly plunged into a state of crisis or industry upheaval, the IT model may no longer meet its needs. Sometimes it is necessary to go back to the analysis stage, to avoid attempting to implement a model that meets a low-priority purpose and leading to a lack of action.

(6) Infusion. Finally, at the infusion stage, an increased organizational effectiveness is gained by using the IT application to support higher-level organizational tasks. Most IT innovations end at the routinization stage, if they even get that far. On occasion, though, a new system is implemented that has a huge impact on a company’s effectiveness. Instead of just performing the old tasks faster or more efficiently, whole new levels are reached as the new system is used in an integrated and

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comprehensive manner. When this stage is reached, the innovation is considered to be infused in the organization.

The lines between these stages are not always so clear and distinct, but a general understanding of the stages themselves is important because the factors that affect forward progress in implementing IT innovations do tend to differ from stage to stage. As with anything new, barriers to implementing IT may occur. These barriers are generally caused more frequently by behavioral and organizational issues than by environmental and technical considerations (Krumwiede & Roth, 1997).

HUMAN RELATIONS CONSIDERATIONS IN A VIRTUAL SETTING Today, most information systems are computer systems designed to assist businesses, government agencies, and other organizations in accomplishing their goals in a number of ways. Businesses have long relied on computers to handle basic bookkeeping jobs, such as payroll and billing; however, computer-related information systems, popularly known as “management information systems,” actually help managers make complex business decisions and better plan for potential developments in market conditions. The industry is dynamic and while the outlook for some industries may be dim, the research shows that by and large, almost every industry will benefit to some extent or another through an intelligent application of information systems (Information systems, 2004).

Based on the pervasiveness of negotiation as a form of social interaction, together with the rising prominence of information technologies as a communication mechanism, the question of how negotiation is conducted via e-mail is of great theoretical and practical importance (Turban, Lee, King, & Chung, 2000). People will have to become more proficient in how they craft their emails, then. Likewise, while more effective management styles have also been advanced to help managers oversee new virtual workers, Robbins says these programs are only likely to improve productivity when virtual workplace employees are willing to accept increased responsibilities, are group oriented, and have good interpersonal skills. In addition, a company's chances of success are improved when the organization’s culture is characterized by trust, risk taking, and a focus on employee participation, when employees have been trained in empowerment skills and provided with the necessary resources; and when management has ensured there was a comprehensive control system in place that monitored employees' actions and alerted management quickly of major problems (Robbins, 2001).

Today, even brick-and-mortar organizations are creating virtual environments for their employees; for instance, intranet provides their members with Internet and World Wide Web features, such as e-mail and Web pages. By sealing the intranet off from the larger Internet, however, a company can protect the information on the intranet from unwanted and possibly criminal intrusion. As security issues have arisen on the Internet, intranets have gained in popularity, particularly among large businesses. “This control helps to avoid the long delays that can occur when multiple users attempt to access a page or site. Furthermore, intranets incorporate the multimedia features of the World Wide Web. These features enable 64

Virtual Communication in Business companies to post information pages for their employees with pictures, sound, and even video or animation” (Ferrell, 2000, p. 2). An innovator in the intranet field is Jakob Nielsen, who holds more than 50 patents on web usability. This expert says that he believes the intranet is “one of the most important developments an organization can make in terms of improving its productivity and efficiency. Today it falls under many guises, from Enterprise Information Portal to knowledge management, but the principal remains the same; an intranet is just an internal network of information” (Nielson, 2001, p. 3). According to Stannie Holt’s “Helping workers help themselves,” one such intranet application takes advantage of these benefits and has major implications for human resource managers today. Holt says that, “Thanks to the Web; today's employees can handle many of the errands they used to take to the human resources department. Employee self-service, or ESS, applications enable workers to check on how much vacation time they have left or apply for a promotion online, saving time and making record keeping easier” (Holt, 1999, p. 93). The corporate website for SAP at http://www.sap.com/solutions/ess/ proudly states that “The new, New Economy is all about customer service. But if employees don't have the information and tools they need to do their jobs, how can they advance your customer-service agenda? Enter Employee Self-Service. The solution that enables your employees to be successful. So your company can be successful” (Employee Self-Service, 2002, p. 3). The vendor reports that its ESS system will allow every employee in a company to view, create, and maintain information related to their jobs. “Human resources information such as skills profiles, assessment, and training. Financial data such as salary, bank information, and tax withholding.

Other types of computer-mediated communications include bulletin boards, threaded discussions, chat rooms, gaming room lobbies, facsimile and voice mail (Allen, 1995, p. 557).

However, choosing the time and place and the appropriate avenue of communication is of paramount importance in providing feedback to employees in any situation. This means that some things just have to be done in person because people communicate mainly by speaking and writing; however, we all also communicate by means of gestures, facial expressions, and even positions of the body. Some programs which have been traditionally used to solicit feedback in the communication process which could be assisted by IT applications include employee suggestion programs. Employee suggestion programs are one motivational tool which has proven particularly useful over the years both in terms of generating more efficient methods of doing business, but also as a morale builder for employees with good ideas who are frustrated by an organization’s bureaucratic inertia. One company reported that as a result of a simple contest which offered a modest reward, employees submitted “many excellent suggestions that not only served as a check to see that everyone was sharing the same vision, but it also provided its employees an opportunity to make meaningful contributions to the business” (Hersey et al, 1996, p. 510).

In the final analysis, then, in order for an IT alternative to work to a company’s advantage, it must focus on providing services that will enhance its relationship with its customers and suppliers. Regardless of the product or service involved, a significant competitive advantage

V. Joy Rose JAGR - Volume 7, Issue 20 (2014), pp. 55-67 can likely be achieved through a developed and carefully integrated IT system. It is important to keep in mind, though, that expectations should be realistic and that competitive advantage could very well be limited, given the dynamic marketplace in which all businesses must compete today.

AUTHOR INFORMATION Dr. V. Joy Rose is the recipient of the Doctor of Philosophy in Organizational Management from Capella University and the Masters of Human Resources Management from National- Louis University. She has also completed 18 MBA credit hours in Marketing from Saint Leo University. She is an Assistant Professor at Saint Leo University in Morrow, Georgia. Dr. Rose’s expertise comes in the field of human resources, marketing, business and management.

REFERENCES Allen, B. J. (1995). Gender and computer-mediated communication. Sex roles, 32(7/8), 557- 63. Amor, Daniel. "Living and Working in an Interconnected World." The E-Business (R)Evolution by 02 March 2004 Bailey, M. N. and Quinn, J. B. (1994). Information Technology: The Key to Service Performance. Brookings Review, 12 (3), 36. Barsh, J., Crawford, B. & Grosso, C. (2000). How E-Tailing Can Rise from the Ashes. The McKinsey Quarterly, 98. Brain, John. (2001). How e-Commerce Works. Howstuffworks.com, Inc. Available: http:// www.howstuffworks.com/ecommerce.htm. Cooper, R. B. & Zmud, R. W. (1990). Information technology implementation research: A technological diffusion approach. Management Science, 123-139. Dearstyne, Bruce W. (April 1, 2001). The view from the fast lane. Information Management Journal, 11(3). Employee self-service. (2002). SAP: The best run businesses run SAP. Available: http://www.sap.com/solutions/ess/businessbenefits.asp. Goldsmith, N. (1991). Linking IT Planning to Business Strategy. Long Range Planning, 24 (6), 67-77. Hersey, P. Blanchard K. H., & Johnson, D. E. (1996). Organizational behavior. Upper Saddle River, NJ: Prentice Hall. How IT Enables Productivity Growth. (2003). McKinsey & Company. Available: http:// www.mckinsey.com/knowledge/mgi/IT/index.asp. Information systems. (2004). Encyclopedia britannica.com [premium service]. Kolb, D. A., Osland, J. S. & Rubin, I. M. (1995). Organizational behavior: An experiential approach, 6th ed. Englewood Cliffs, NJ: Prentice Hall. Krumwiede, K. R. and Roth, H. P. (1997). Implementing Information Technology Innovations: The Activity-Based Costing Example. SAM Advanced Management Journal, 62 (4), 4.

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Mansell, R. & Wehn, U. (1998). Knowledge societies: Information technology for sustainable development. Oxford: University of Oxford. Miranda, R. (2001). ERP and financial management systems. Chicago, Il: Government Finance Officers Association. Nadler, J. & Thompson, L. (2002). Negotiating Via Information Technology: Theory and Application. Journal of Social Issues, 58(1), 109. Nielsen, J. (December 3, 2001). Interview: Jakob Nielsen on usability and Intranets. Available: http://www.it-director.com/. O'Connor, A. D. (1993). Successful Strategic Information Systems Planning. Journal of Information Systems, 3, 71-83. Online Selling & eCRM. (2003). eMarketer. Available: http://www. emarketer.com. Phillips, R. 2000, June. Digital technology and institutional change from the gilded age to modern times: the impact of the telegraph and the internet. Journal of Economic Issues, 267-85. Premkumar, G. and King, W. R. (1991). Assessing Strategic Information Systems Planning. Long Range Planning, 24 (5), 41-58. Reichheld, F. F. & Schefter, P. E. (2000). Loyalty: Your Secret Weapon on the Web. Harvard Business Review, 78, 105, 113. Robbins, S. P. (2001). Organizational Behavior: e-business updated edition. Upper Saddle River, NJ: Prentice Hall. Remenyi, D. (1991). Introducing Strategic Information Systems Planning. Manchester and Oxford: National Computing Centre/Blackwell. Turban, E., Lee, J., King, D., & Chung, H. M. (2000). Electronic commerce: A managerial perspective. Upper Saddle River, NJ: Prentice Hall. U.S. Productivity Growth, 1995-2000. (2003). McKinsey & Company. Available: http://www.mckinsey.com/knowledge/. Vancelette, B. (2002). Improving journal quality with process improvement methods. Leawood, KS: The Sheridan Press. Yi, H. (2002, Winter). ERPs: The promise and the peril. The Public Manager, 31, 55-57. .

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Full Article Available Online at: Intellectbase and EBSCOhost │ JAGR is indexed with Cabell’s, JournalSeek, etc.

JOURNAL OF APPLIED GLOBAL RESEARCH

ECOTOXICOLOGICAL USE OF TERRESTRIAL, FRESHWATER, AND MARINE ORGANISMS TO QUICKLY DETECT POLLUTION AND EVALUATE REMEDIATION EFFORTS OF DIESEL CONTAMINATION

Tatiana Tatum Parker and Rebecca Rosenthal Saint Xavier University, USA

ABSTRACT hemical analysis of polluted sites is insufficient in evaluating environmental risk and the efficiency of remediation. We preformed ecotoxicological tests to monitor C the effects of diesel exposure. We examined phytotoxicity on germination rates, radicle length and plumule length of Kochia prostrate, Raphanus sativus, Pisum sativum, Phaseolous lunatus, and Zea mays. Acute toxicity was examined for aquatic bioindicators, Daphnia magna and Artemia salina. In addition, hatching rates and oxygenation were evaluated for Artemia. There was a fifty percent reduction in germination rates at 2% diesel, radicle length at 4% diesel, and plumule length at 3.5% diesel. D. magna had a 24 hour LC50 of < 0.1% diesel. Artemia had a 24 hour LC50 of ~0.75% diesel. The addition of oxygen only had an effect on mortality after 12 hours (p=0.098). The integration of analytical, toxicological and bioremediation data is necessary to properly assess the ecological risk of contamination and bioremediation processes.

Keywords: Diesel Contamination; Ecotoxicological Tests; Phytotoxicity Tests

INTRODUCTION Diesel fuel is the lifeblood of global industry, from agriculture to manufacturing to transportation. Society is reliant on diesel and other fossil fuels for energy. The increasing use of fossil fuels, especially diesel, in diesel engines of cars, industrial trucks and generators has led to an increased demand for diesel (Ogbo, 2009). Pollution of the soil with petroleum derivatives is observed in municipal soils around industrial plants, in areas where petroleum and natural gas are obtained (Adam and Duncan., 2002) and areas where petroleum hydrocarbons are processed and distributed (Ayotamuno et al., 2006). In addition to these, and other accidental discharges, diesel is also intentionally released into the environment. It has been used as dust control measures on dirt roads, and as an herbicide. Diesel was once used in the fight against malaria to control mosquitoes by spraying a thin layer over the surface of the water (Rathburn, et al., 1965). This method is quite suitable for mosquito abatement in

Ecotoxicological Use of Terrestrial, Freshwater, and Marine Organisms To Quickly Detect Pollution and Evaluate Remediation Efforts of Diesel Contamination environments not disturbed by wind or vegetation, which happen to be the ideal site for mosquito proliferation (Xue, et al., 2013).

Whether accidentally or intentionally released into the environment diesel fuel has a great impact on the entire ecosystem. These fuels reduce soil fertility and soilmicroflora population (Torstenssen et al., 1998). The addition of diesel to the soil leads to significant reduction of organic carbon content of the soil, is phytotoxic to plants at relatively low concentrations, and decreases germination rates of various species (Ogbo, 2009). Changes in soil properties due to contamination with petroleum-derived substances can lead to water and oxygen deficits as well as a shortage of available forms of nitrogen and phosphorus (Wyszkowska and Kucharski, 2000). Contamination of the soil environment can also limit its protective function, upset metabolic activity, unfavorably affect its chemical characteristics, reduce fertility and negatively influence plant production (Wyszkowski et al., 2004; Wyszkowski and Wyszkowska, 2005). This threatens both human health and that of all organisms that are dependent on the soil. Through contaminations, oil spills, and runoff, diesel fuel is found in every body of land and water (Fingas, 2000).

Cleanup of contaminated land and water is tedious and expensive. Remediation procedures can be through bioremediation or through chemical methods. One problem with remediation is the growing pool of entrepreneurs seeking to exploit the publicity of high tech remediation processes by offering all manner of treatments they call "bioremediation." These treatments-- usually sold for tens of thousands of dollars by individuals who demanded advance payment from owners of heavily-polluted industrial and commercial properties--often involved little more than water and a cheap surfactant sprayed across the surface of the ground. In some instances these scam artists claim their "treatments" will eliminate all petroleum pollution in a few days, with some even promising rapid results. Unfortunately, this sort of unscrupulous hucksterism has resulted in a large number of failed bioremediation projects and a growing sense of general skepticism about the process.

True bioremediation involves the use of microbes or other biological methods of remediation. In oil-polluted ecosystems, it is usually microorganisms that are used for the bioremediation. The process takes advantage of the knowledge that biological degradation is the main process by which nonvolatile factions of oils are removed from the environment (Moran et al., 2000). These techniques accelerate the naturally occurring biodegradation by optimizing the conditions favorable for microorganisms they add to the effected area.

There are also non-biological methods of remediation. These methods rely on various sorts of chemicals, like solvents and industrial-grade fertilizers that are sprayed into the environment to either assist indigenous microbes in the degradation process or break up the oil and disperse it. The actual chemical substances can be as toxic and dangerous as the initial spill itself. For instance, during the clean up of the Exxon Valdez spill in Alaska, a major test of such materials resulted in chemical burns and blisters on the arms and faces of the workers who applied them to polluted beaches. In one clinical study, rats were treated orally with weathered crude oil and

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Corexit 9527 to determine impacts on "intestinal microbial metabolism and associated populations" (George et al. 2001). The study found undiluted dispersant was lethal to the rats, and changes in weight were observed relative to the amount of dilution; Corexit 9527 was also toxic in vitro at a dilution of 1:1000 (George et al. 2001). According to the authors, this study suggests that "prolonged exposure of mammals to oil, dispersant, or in combination impacts intestinal metabolism, which ultimately could lead to altered detoxification of oil constituents and coexposed constituents" (George et al. 2001). Surfactants can also be used, breaking up the oil and dispersing in throughout the water column. For example surfactants were used to help deal with the aftermath of the Deep Well Horizon spill in 2010. Studies have shown that the use of dispersants broke the oil into droplets small enough to easily enter the food chain. Evidenced of this was "orange blobs" found under the shells of crab larvae in "almost all" of the larvae collected from over 300 miles (480 km) of coastline stretching from Grand Isle, Louisiana, to Pensacola, Florida (De Hoop, 2013). Another study found that dispersants may have killed microscopic plankton and disrupted the food chain, however this experiment only spanned 5 days so the effect could be greater in the future (Ortmann, et al., 2012).

To preserve human health and environmental quality, it is important to assess the ecotoxicological effects of contamination and evaluate remediation techniques to ascertain the overall health of the system. The evaluation of soil or water quality after a fuel spill solely based on chemical data does not include the effects of toxic substances in organisms. Thus ecotoxoiclogical assays should be utilized to assess the effects of toxic substance in organisms according to their sensitivity. Most of the procedures used in both regulated and unregulated toxicology are carried out on mammals, but public pressure to minimize the use of vertebrates in ecotoxicity testing (Walker et al., 1998) and scientific interest in promoting the study of the effects of chemicals on both terrestrial organisms (including plants) and aquatic environments, is growing. The recognition that a precise LD50 for mammals is not required to determine the toxicity of chemicals has led to the development of alternative methods to the traditional LD50 test for acute oral toxicity determination. One of the most promising alternatives in environmental toxicology is the use of lower organisms with limited sentience including bacteria, fungi, algae, plants, and invertebrate animals (Repetto, 1995; Balls, 1998).

There is a concern that using lower organisms with limited sentience provides results that are not relevant for higher level organisms. However, Khangarot and colleagues (Khangarot and Ray, 1988; Khangarot et al., 1987) found a high correlation between the acute toxicity of some metals to the crustacean cladoceran Daphnia magna and the corresponding LD50 values for mice and rats. And a study published by Calleja and Persoone (1992) reports the predictive screening potential of some aquatic invertebrate tests for acute oral toxicity in humans better than the rat LD50 test for some chemicals. If the concern is the ecosystem at large, it matters little which piece of the ecosystem is destroyed. Each piece impacts the whole.

The purpose of our study was to find ecotoxoiclogical assays which could be quickly, and cost effectively, deployed to assess the effects of toxic substance in organisms. Since diesel fuel spills effect terrestrial and aquatic systems, we utilized organisms from terrestrial, fresh water,

Ecotoxicological Use of Terrestrial, Freshwater, and Marine Organisms To Quickly Detect Pollution and Evaluate Remediation Efforts of Diesel Contamination and marine environments. For the terrestrial system, we examined the effects of various diesel fuel concentrations on the germination sensitivity of five agricultural plant species. The plant species examined are crop species based upon research done by Ogbo (2009) representing dicots (Kochia prostrate, Raphanus sativus), legumes (Pisum sativum, Phaseolous lunatus), monocots (Zea mays) to see how these varieties differ in their tolerance of the fuel contaminants. For the freshwater, we examine acute toxicity on Daphnia magna. They are an important link in the food chain in aquatic ecosystem, highly sensitive to toxic substances, have a short generation time, multiplies very rapidly, easily acclimatizes in laboratory condition, can be cultured in a small space and can be measured in a relatively short period (APHA, 1998 and GSM, 1989). The use of D. magna in toxicology is accepted in several countries to monitor wastewater treatment systems, to establish quality criteria to determine permissible concentrations of pollutants, limits of impurity in water from natural effluents, and to determine the efficacy of a good sanitation method (Villegas- Navarro et al., 1999). And for the marine system, we used the marine bioindicator is Artemia salina, which have long been considered to be an indicator species in marine aquatic environments. The organism has been widely used to examine potency of toxicity of insecticides, of heavy metal salts and antibiotics, and testing the inhibitory effects of carcinogens on hatching rates (Delcambe, 1955; Michael, et al. 1956; Brown, et al., 1968; Robinson et al., 1965; Grosh, 1967).

MATERIALS & METHODS Crop Lines Seeds for Raphanus sativus, Pisum sativum, Phaseolous lunatus, and Zea mays were purchased from Ward’s Scientific. Seeds for Kochia prostrate were obtained from the Washington State seed lab. All seeds were kept in the dark at – 4oC. Seeds were soaked in water for 24 h prior to experimentation.

Plant growth parameters measurement The experiment was a completely randomized block design with each treatment replicated three times. The experiment was conducted in glass petri dishes containing Whatman No.1 filter paper on the base of dishes. A modification of the methods described by Erute (2009) was adopted. Six different levels of diesel treatment were prepared with distilled water 1%, 2%, 3%, 4% and 5% diesel and distilled water was used as control. Five seeds were placed in each Petri dish containing filter paper moisten with diesel contaminated water. Seeds were regarded germinated with the emergence of radicle and plumule. Moisture levels were monitored daily. Seed germination was monitored daily for cumulative percentage germination for three days and total germination (%) were recorded. Radicle and plumule length (cm) were recorded daily, and tallied after three days. Data from the tests were analyzed using analysis of variance (ANOVA) to detect differences between treatment and control.

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Parent Animals All freshwater invertebrate experiments were carried out with adult D. magna obtained from Carolina Biological Supply Company and Ward’s Science Ltd. Culture media was aged water, and fed Roti-Rich liquid invertebrate diet (1 drop per gallon). The photoperiod was 16 h L:8h D and the temperature was 20 + 2oC.

All marine invertebrate experiments were carried out with adult A. salina purchased from Carolina Biological Supply Company. Culture medium was Instant Ocean sea salt mix (3T per L), and fed Roti-Rich liquid invertebrate diet (1 drop per gallon). The photoperiod was 16 h L: 8h D and the temperature was 20 + 2oC.

Acute Daphnia toxicity tests The experiment was a completely randomized block design with each treatment replicated three times. All experiments were carried out with animals from clone A (Baird et al., 1989) and initiated with third to fifth brood neonates (<24 h old). Test medium was aged water, and animals were not fed during the tests. Test organisms appeared vigorous and in good condition before testing, and were placed below the test surface due to a slight sheen of some test samples observed. Ten animals per treatment in groups per 100 ml of test solution were used. Nine concentrations of diesel fuel were created at the following concentrations: 0%, .10%, .25%, .5%, 1%, 2%, 3%, 4%, and 5%. The fuel was stirred into the water before the D. magna were introduced into the test chamber. Temperature and photoperiod were as described above. The pH levels were determined 0, 24, and 48 h after the start of the test. Tests were conducted under static conditions with no renewal of the test solution. The samples were checked every 12 h for 48 h measured effect was death recognized as immobilization for 15 s after stimulation by bright light.

Fecundity Artemia toxicity tests The experiment was a completely randomized block design with each treatment replicated four times. To determine the effect of the toxicant on the fecundity of the Artemia Petri dishes containing 250 eggs each had individual concentrations of 0.1%, 0.25%, 0.5%, 1%, 2%, 3%, 4%, 5%, 10%, and 20% and a control dish with a 0% concentration. The fuel was stirred into the water before the eggs were introduced into the test chamber. Tests were conducted under static conditions with no renewal of the test solution. The pH levels were determined 0, 24, and 48 h after the start of the test. Petri dishes were maintained at a constant temperature of 26ºC+. After 24 h, petri dishes were examined using a dissecting microscope and pictures were taken from three different fields of view. Photos were taken every 12 h for 48 h and number of hatched individuals calculated.

Acute Artemia toxicity tests The experiment was a completely randomized block design with each treatment replicated three times. Test medium was Instant Ocean sea salt mix (3T per L), and animals were not fed

Ecotoxicological Use of Terrestrial, Freshwater, and Marine Organisms To Quickly Detect Pollution and Evaluate Remediation Efforts of Diesel Contamination during the tests. Test organisms appeared vigorous and in good condition before testing, and were placed below the test surface due to a slight sheen of some test samples observed. Ten animals per treatment in groups per 100 ml of test solution were used. Nine concentrations of diesel fuel were created at the following concentrations: 0%, .10%, .25%, .5%, 1%, 2%, 3%, 4%, and 5%. The fuel was stirred into the water before the A. salina were introduced into the test chamber. Temperature and photoperiod were as described above. Tests were conducted under static conditions with no renewal of the test solution. The pH levels were determined 0, 24, and 48 h after the start of the test. The samples were checked every 12 h for 48 h measured effect was death recognized as immobilization for 15 s after stimulation by bright light. Then, the percent mortality was determined and data from the tests were analyzed using analysis of variance (ANOVA) to detect differences between treatment and control.

Oxygen Deprivation Artemia toxicity tests The experiment was a completely randomized block design with each treatment replicated three times. We investigated whether Artemia are dying due to lack of oxygen as a result of the diesel fuel forming a film over the surface of the water or as a result of the toxins released by the diesel fuel. This part of experiment only used the lowest concentration of diesel fuel, 0.1%, to determine the cause of death of Artemia. Ten fully grown Artemia were placed inside a San Francisco Bay Brand™ Brine Shrimp Hatchery, an Elite 801 aerator was used to create a circulation of oxygen. Artemia were added, to an air circulating 0.1% concentration of diesel fuel. Tests were conducted under static conditions with no renewal of the test solution. Every 12 h for 48 h, the surviving Artemia in the hatchery were counted and the percent mortality was determined. Then, the percent mortality was determined and data from the tests were analyzed using analysis of variance (ANOVA) to detect differences between treatment and control.

RESULTS Effects on Crop Plants The greatest amount of seed germination of the plants occurred in the control group, deionized water. All the plants tolerated diesel fuel contamination at 1-2% levels, with seed germination between 98 - 55%. There was no significant difference between percentage germination of the seeds in the control of the five crop plants. There was no significant difference between percentage germination of the seeds in 1% level of contamination in Z. mays, K. prostrate, and P. sativum and the 2% level of P. lunatus. There was significant reduction (P<0.05) in percentage germination recorded for R. sativus and P. lunatus at 1.0% level of contamination (Table 1). As contamination levels increased, there was significant reduction in percentage seed germination. However there were exceptions, with P. sativium having no germination at 3.0% but germination at 4.0% and R. sativus not having germination at 4.0% but germination at 5.0%.

Diesel fuel contamination caused a reduction in the length of the radicle of the five crop plants. The longest racicle (3.0 cm) in P. lunatus was recorded in 1.0% level contamination and the shortest (0.7 cm) in Z. mays at 5% level of contamination (Table 2). Increasing levels of

Tatiana Tatum Parker and Rebecca Rosenthal JAGR - Volume 7, Issue 20 (2014), pp. 68-80 contamination negatively effected the radicle length of all plants, except R. sativus. Diesel fuel contamination also effected the plumule length of Z. mays and K. prostrate, but not P. sativum (Table 2). For P. lunatus and R. sativus the plumules remained within the cotyledons so lengths were not recorded.

Table 1: Percentage seed germination of five crop plants at different levels (%) of diesel oil contamination. Crop Control 1% 2% 3% 4% 5% plant 100± R. sativus 66±0.0b 55±3.8c 33±3.6d 00±0.0f 22±6e 0.00a P. 100± 0.00a 90± 10.5a 56±5c 00±0.0f 45±6c 00±0.0f sativum 100± P. lunatus 78± 9.7b 98±4.5a 78±4.1b 22±4.6e 11±3.5e 0.00a 100± Z. mays 90± 10.5a 56±5c 45±6c 44±6c 22±4e 0.00a K. 100± 0.00a 90± 8.4a 56±3c 45±6c 45±4c 33±6d prostrate Figures with the same letters (superscripts) are not significantly different (P<0.05).

Table 2: Length of radicle and plumule of five crop plants in response to levels (%) of diesel oil contamination.

Figures with the same letters (superscripts) are not significantly different (P<0.05).

Effects on Daphnia The greatest amount of survivability occurred in the control group. There was survivability in all of the concentrations after 12 h, with only 6.67% mortality in the control group and 87% in the 5% diesel fuel contamination. There were only survivors in the 0% and 0.1% at 24 h, with 10% and 96% mortality rates respectively. At 36 h the control had 27% mortality, and 33% mortality at 48 h. All other concentrations had 100% mortality after 24 h (Figure 1).

Ecotoxicological Use of Terrestrial, Freshwater, and Marine Organisms To Quickly Detect Pollution and Evaluate Remediation Efforts of Diesel Contamination

Figure 1: Percent mortality of Daphnia magna in response to levels (%) of diesel oil contamination after 12, 24, 36, 48 h

Effects on Artemia Changing the concentration of diesel fuel did not have a statistically significant impact on the fecundity of the Artemia (p=0.43) (Table 3). The changing concentrations did, however, have significant impacts on their mortality (p=0.0009), with the greatest amount of survivability occurred in the control group. There was survivability in all of the concentrations all the way through 24 h. For the 12 h reading, there was 10% mortality in the control group and 74% in the 5% diesel fuel. After 24 h there were only survivors in the control group with 24% mortality at 36 h and 26% mortality at 48 h (Figure 2). The addition of oxygen did have a statistically significant effect on mortality after 12 h (p=0.098). However, the addition of oxygen did have not have a statistically significant effect on mortality (p=0.59) after 24 h.

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Table 3: Total hatching percentage of Artemia salina in response to levels (%) of diesel oil contamination. Concentration Total Hatched % Hatch After 48 H 0 198.75 ± 5.13b 79.5b 0.1 214.25 ± 4.11b 85.7b 0.25 211 ± 4.55b 84.4b 0.5 160 ± 20.83c 64c 1 219 ± 21.15a 87.6a 2 207 ± 14.67b 82.8b 3 194 ± 5.48c 77.6c 4 217.75 ± 8.76a 87.1a 5 226.5 ± 4.7a 90.6a 10 215.5 ± 6.6a 86.2a 20 212 ± 5.2b 84.8b Figures with the same letters (superscripts) are not significantly different (P<0.05).

Figure 2: Percent mortality of Artemia salina in response to levels (%) of diesel oil contamination after 12, 24, 36, 48 h

Ecotoxicological Use of Terrestrial, Freshwater, and Marine Organisms To Quickly Detect Pollution and Evaluate Remediation Efforts of Diesel Contamination

DISCUSSION The ecotoxicological monitoring of diesel-contamination was accomplished by assessing the damage to biota living in soils and water contaminated by diesel spills. Rapid, inexpensive, and simple methods were evaluated, to examine the phytoxocicity on five crop species and acute toxicity on two aquatic organisms. Although there was germination of all the crops, with the exception of P. sativum, at 5% diesel contamination, there was a significant reduction in germination rates as well as a strong negative effect on radicle and plumule length. These results have been observed my numerous others (Luhach & Chaudry, 2013; Anoliefo & Vwioko 1995; Ogobo, 2009; Miyoshi and Sato, 1997; Njoku, et al., 2009; Salehi, et al., 2008). In these previous studies some species withstood up to 6% contamination, where as in this study we found a 50% reduction in germination rates in concentrations as low as 2%. The reductions in plumule and radicle length by 50% in this study occurred at approximately 3.5%. The plants most suitable for use in bioassays were R. sativus and P. lunatus, due to their sensitivity to contamination. The reaction of these plants could be used to reflect the level of pollution in an environment and monitor pollution levels throughout the remediation process. Zea mays, R. sativus, and K. prostrate exhibited better growth and germination even at high concentrations of diesel, which could allow for these plants to be used for phytoremeditation of diesel contaminated soils. D. magna showed a significant response to diesel fuel with a 12 h LC50 at 1% and a 24 h LC50 of less than 0.1%. These findings are consistent with other studies, with 48 h LC50 of 3.5 mg/L (Molina-Barahona, et al., 2004). Artemia appear to be a bit more robust with a 12 h LC50 at 2% and a 24 h LC50 of approximately 0.75%. These findings are consistent with other studies, with 48 hr LC50 of 7.01 mg/L (French-McCay, 2002).

Since many of the esters found in diesel fuel are not soluble in water, they form a sheen on the surface. This property made diesel useful as an insecticide on small ponds due to its ability to prevent oxygen transfer across the water/air interface (Aquatext, 2009). To avoid having the D. magna trapped in this film they were released below the water surface, which resulted in significantly fewer organisms trapped. While both D. magna and A. salina are generally tolerant of poor water quality, we conducted an experiment with A. salina adding aeration. The addition of oxygen to Daphnia was not done due to the fact that small oxygen bubbles could get under their carapace and kill them. There was a significant improvement at 12 h, but it was negated by 24 h. This indicates that the film itself is not the agent causing the majority of the death, but that the soluble components are.

Diesel has a profound effect on terrestrial, fresh water, and marine organisms. Although we have shown ranges of tolerances within and between these groups, the risk of this fuel on the environment is quite substantial. This range of sensitivity allows these organisms to be used to reflect biologically significant levels of pollution in their environment. These organisms can be used as an inexpensive quick method to ascertain the efficacy of remediation efforts post contamination by exposing them to soil or water samples from contaminated areas pre and post remediation and comparing the results. Even if it is a purely terrestrial environment that has been effected, soil samples can be soaked and then the leachant used to test on both the fresh and marine aquatic organisms. If it is an aquatic spill the water can be used on the

Tatiana Tatum Parker and Rebecca Rosenthal JAGR - Volume 7, Issue 20 (2014), pp. 68-80 seedlings. These kinds of experiments allow for an evaluation of damage done by an unintended release so that remediation efforts can be informed. Results from our microcosm study suggest that in addition to the evaluation of the bioremediation processes efficiency, toxicity testing is different with organisms representative of diverse phylogenic levels. The integration of analytical, toxicological and bioremediation data is necessary to properly assess the ecological risk of contamination and bioremediation processes.

ACKNOWLEDGMENT The authors acknowledge the Department of Biological Sciences, Saint Xavier University, Chicago, Illinois for providing facilities for this research work. They also acknowledge work done by undergraduate research assistants Summar Hussain and Grazyna Urbanczyk in the collection of data.

REFERENCES Adam, G. and Duncan, H. J. (2002). Influence of Diesel Fuel on Seed Germination. Environ. Pollut., (120) 363-370. Apha, Awwa, Wef (1998). Standards methods for the examination of water and wastewater, 20th edition, American Public Health Association, American Water Works Association and Water Environmental Federation, Washington, DC 2005- 2605. Ayotamuno, M.J., Kogbaraa, R.B., and Agunwamba, J.C. (2006). Bioremediation of a pertorleum-hydrocarbon polluted agricultural soil at various levels of soil tillage in Portharcourt, Nigeria. Nigerian Journal of Techonlogy. 25(1); 44-51. Baird, D.J., Soares, A.M.V.M., Girling, A., Barber, M.C., Calow, P., (1989). The long term maintenance of Daphnia magna Straus for use in ecotoxicity tests: problems and prospects. In: Lokke, H., Tyle, H., Bro-Rasmussen, F. (Eds.), Proceedings of the First European Conference on Ecotoxicology. Lyngby, Denmark, 144–148. Balls M. (1998) Why is it proving to be so difficult to replace animal tests? Lab Animal, 27, 44- 47. Brown, R. F., J. D. Wildman, and R. M. Eppley. (1968). Temperature-dose relationships with aflatoxin on the brine shrimp, Artemia salina. J. Ass. Offic. Anal. Chem. 51, 905-906. Calleja, M. C., and Persoone, G. (1992). Cyst-based toxicity tests. IV. The potential of ecotoxicological tests for the prediction of acute toxicity in man as evaluated on the first ten chemicals of the MEIC program. A¹¸A 20, 396}405.Chanh, P-H., and G. Mamy. 1963. A simple biological reagent for toxicity tests: the eggs of "Artemia salina". Rev. Agressol, 4, 599-603. DeHoop, L., Juijbregts, M.A.J., Schipper, A.M., Veltman, K., De Laender, F., Viaaene, K.P.J., Klok, C., & Hendriks, A.J. (2013). Modelling bioaccumulation of oil constituents in aquatic species. Marine Pollution Bulletin, 76 (1-2), 178-186. Delcambe, L. (1955). Activites biologiques des Actinomycines de Streptomyces S-67. Arch. Int. Pharmacodyn. Ther,101, 358-366.

Ecotoxicological Use of Terrestrial, Freshwater, and Marine Organisms To Quickly Detect Pollution and Evaluate Remediation Efforts of Diesel Contamination

Erute, M. O. (2009): Effects of diesel fuel contamination on seed germination of grows crops plants-Arachis hypogaea, Vigna unguiculate, Sorghum bicolour and Zea mays. Afr. J. Biotech., 8(2), 250-253. French-McCay, D.P. (2002). Development and application of an oil toxicity and exposure model, oiltoxex. Environmental Toxicology and Chemistry , 21(10), 2080-94 Fingas, M. F. (2000). The Basics of Oil Spill Cleanup (2nd ed.). Boca Raton, FL: CRC Press. George, S.E., G.M. Nelson, M.J. Kohan, S.H. Warren, B.T. Eischen, L.R. Brooks. 2001. Oral Treatment of Fischer 344 Rats with Weathered Crude Oil and a Dispersant Influences Intestinal Metabolism and Microbiota. J. Toxicol. Environ. Health, 63(4), 297-316. GSM (1989). Examination of Water, Wastewater and Sludge, Bio-assays (Group L) Determining Tolerance of Daphnia to Toxicity of Wastewater by way of a Dilution Series, GSM(German Standard Methods)(L-30), DIH-38412, Part 30, March 1989 Grosh, D. S. (1967). Poisoning with DDT: effect on reproductive performance of Artemia. Science, 155, 592-593. Hall, J.K., R.O. Mumman and D.W. Watta. (1991). Leaching and runoff herbicides in tilled and untilled field. Agric. Ecosyst. Environ., 37, 303 – 314. Jyoti Luhach, J., and Chaudhry, S. (2012). Effect of diesel fuel contamination on seed germination and growth of four agricultural crops. Universal Journal of Environmental Research and Technology, 2(4), 311-317 Khangarot, B. S., and Ray, P. K. (1988). The confirmation of a mammalian poison classification using a water flea (Daphnia magna) screening method. Arch. Hydrobiol. 113, 447}455. Khangarot, B. S., Ray, P. K., and Chandra, H. (1987). Daphnia magna as a model to assess heavy metal toxicity: Comparative assessment with mouse system. Acta Hydrochem. Hydrobiol, 15, 427-432. Michael, A. S., C. G. Thompson, and M. Abramovitz. 1956. Artemia salina as a test organism for bioassay. Science, 123, 464. Miyoshi, K., Sato, T. (1997). “The Effects of Ethanol on the Germination of Seeds of Japonica and Indica Rice (Oryza sativa L.) under Anaerobic and Aerobic Conditions.” Annals of Botany, 79, 391-5. Molina-Barahona, L., Vega-Loyo, L., Guerrero, M., Ramírez, S., Romero, I., Vega-Jarquín, C. and Albores, A. (2005). Ecotoxicological evaluation of diesel-contaminated soil before and after a bioremediation process. Environ. Toxicol., 20, 100–109. Njoku, K. L., Akinola, M. O., and B. G. Taiwo. (2009). Effect of gasoline diesel fuel mixture on the germination and the growth of Vigna unguiculata (Cowpea). African Journal of Environmental Science and Technology, 3(12), 466-471. Ogbo, E.M. (2009). Effects of diesel fuel contamination on seed germination of four crop plants - Arachis hypogaea, Vigna unguiculata, Sorghum bicolor and Zea mays. African Journal of Biotechnology, 8(2), 250-3. Ortmann, A.C., Anders, J., Shelton, N., Limin, G., Moss, A.G., and Condon, R.H. (2012). Dispered oil disrupts microbial pathways in pelagic food webs. PLOS July 31. DOI: 10.1371/journal.pone.0042548

Tatiana Tatum Parker and Rebecca Rosenthal JAGR - Volume 7, Issue 20 (2014), pp. 68-80

Rathburn, C.E., Clements, B.W., and Rogers, A.J. (1965). Comparative tests of fog oils and diesel oil as thermal aerosols for control of adult mosquitoes. Mosquito News, 25(2), 101- 106. Repetto G, Repetto M. 1995. Métodos alternativos: estudios toxicológicos in vitro. In: Repetto M, editor. Toxicología Avanzada. Editorial Diaz de Santos, Barcelona. pp. 37-59. Robinson, A. B., K. F. Manley, M. P. Anthony, J. F. Catchpool,and L. Pauling. (1965). Anesthesia of Artemia larvae:method for quantitative study. Science, 149, 1255-1258. Salehi, M.R. , F. Ashiri and H. Salehi. (2008). Effect of different ethanol concentrations on seed germination of three turfgrass genera.” Adv. in Nat. Appl. Sci., 2(1), 6-9. Torstenssen, L., O. Mikaelpell and C. Bostenberg, (1998). Need of a strategy for evaluation of arable soil quality. Environ. Pollut., 27, 4-7. Villegas- Navarro, A , Romero Gonzalez, MC and Rosas Lopez, E (1999). Evaluation of Daphnia magna as an indicator of toxicity and treatment efficacy of textile wastewater. Environmental International, 25, 619- 624. Walker CH. (1998). Biomarker strategies to evaluate the environmental effects of chemicals. Environ Health Perspect . 106 Supp., 2, 613-620. Willis, G. H., L.L. McDowell, S. Smith and L.M. Southwick. (1986). Permethrin washoff from cotton plants by simulated rainfall. J. Environ. Qual,. 15, 116 – 120. Willis, G.H., L.L. McDowell, S. Smith and L.M. Southwick. (1988). Rainfall amount and intensity effects on carbaryl washoff from cotton plants. Trans ASAE, 31, 86 – 90. Wyszkowska, J. and J. Kucharski, (2000). Biochemical properties of soil contaminated by petrol. Polish J.Environ. Stud., 9(6), 476-485. Wyszkowski, M. and J. Wyszkowska, (2005). Effect of enzymatic activity of diesel oil contaminated soil on the chemical composition of oat (Avena sativa L.) and maize (Zea maize L.) Plant Soil Environ., 51(8), 360-367 Wyszkowski, M., J. Wyszkowska and Zoilkowska, (2004). Effect of soil contamination with diesel oil on yellow lupine yield and macroelements contents. Plant Soil Environ., 50(5), 218-226. Xue, R.D., Smith, M.L., and Qualls, W.A. (2013). Field evaluation of truck-mounted thermal fog of DUET and Aqualuer using different solvents against Aedes albopictus. J. Am Mosq. Control Assoc., 29(3), 303-303.

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