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論文名稱(中文) 探討高等教育中影響數位遊戲式學習接受度之因素-以資料庫課程為例
論文名稱(英文) Explore the impact of digital game-based learning acceptance factors in higher education-An example of the database management course
校院名稱 成功大學
系所名稱(中) 資訊管理研究所
系所名稱(英) Institute of Information Management
學年度 98
學期 2
出版年 99
研究生(中文) 王建喬
研究生(英文) Chien-Chiao Wang
學號 R7697112
學位類別 碩士
語文別 中文
論文頁數 170頁
口試委員 指導教授-王維聰
口試委員-王育民
口試委員-林彣珊
中文關鍵字 數位遊戲式學習  科技接受模式  遊戲品質  學習動機  資訊回饋  認知學習成效 
英文關鍵字 Digital game-based learning  Technology acceptance model  Game quality  Learning motivation  Information feedback  Cognitive learning effectiveness 
學科別分類
中文摘要 數位遊戲式學習近幾年受到廣泛的討論,被認為可以增加學生學習的動機,輔助學生學習,提升教學的品質與成效。但數位遊戲式學習亦面臨了使用者不接受的問題,被認為是非正式學習活動和害怕學習目標無法達到,因此不常使用數位遊戲式學習於課堂上。
本研究的目的於瞭解影響數位遊戲式學習接受度的關鍵因素,提出重要的可行性政策,令學習者更能接受數位遊戲式學習系統,進而使教育者能常使用數位遊戲式學習於課堂上。過去的研究鮮少探討數位遊戲式學習使用者意圖層面的議題,也較少從高等教育角度來探討數位遊戲式學習對學習者的影響,而整理文獻後發現較少學者探討數位遊戲系統的品質因素和系統所提供的回饋對學習者所產生的使用行為影響,僅探討數位遊戲式學習所產生的學習動機。因此本研究以學生為研究主體並以科技接受模式為理論基礎,再以遊戲品質、資訊回饋和學習動機理論當外部變數,探討這些變數與學生的認知學習成效之間關係,以建構出一個延伸型科技接受模式。
本研究針對各學校學過資料庫並玩過本研究之數位遊戲式學習系統的學生進行問卷調查,共收集322份有效問卷,且以結構方程模式分析調查結果。研究成果為瞭解除了學習動機外,資訊回饋程度也會影響學習者對系統意識到有用及好用的程度,並間接的影響使用意圖;意識到有用對於認知學習成效有直接顯著影響;意識到好用對於意識到有用有直接顯著的影響,但對於認知學習成效無顯著影響;認知學習成效則對於使用意圖有直接顯著的影響;另外遊戲本身的品質也會影響學習者想要再使用數位遊戲式學習系統的意圖,以及提高學習者的認知學習成效。整體而言,以延伸型科技接受模式為理論探討數位遊戲式學習者接受程度的基礎架構具有良好的解釋力,並能透過學生本身的學習動機、系統的資訊回饋程度和系統的遊戲品質瞭解促進使用意圖的因素,且驗證遊戲品質對於認知學習成效具有正向影響。本研究結果彌補過去文獻不足之處,提出可行性政策,使數位遊戲式學習能常使用於課堂上,並提供數位遊戲式學習相關領域在進行使用者意向與行為相關實務分析之依據。
後續的研究者可針對其他類型數位遊戲式學習課程進行額外探討,或針對認知娛樂性因素做進一步探討,也可隨著使用時間的增加,對數位遊戲式學習系統的使用意圖和實際使用進行探討。
英文摘要 Digital game-based learning has been widely discussed in recent years, and is thought to increase student’s learning motivation, support student learning, and improve teaching quality and effectiveness. However, digital game-based learning is facing a problem of user acceptance. It is considered as too informal and there is a fear that learning objectives can not be achieved, and so digital game-based learning is rarely used in the classroom.
This study aims to understand the impact of key factors of digital game-based learning acceptance, to feasibility of proposed policies and to make learners more receptive to such methods and thus enable educators to always use it in the classroom. Few previous studies investigate digital game-based learning user intention issues, and even fewer adopt a higher education perspective to examine digital game-based learning effects in learners.In addition, there is little research into the quality of the games in such learning systems, or the impact on learners use behavior from the feedback the systems provide, with most studies, only investigating learning motivation. Therefore, this study uses students and the Technology Acceptance Model, along with game quality, information feedback and learning motivation theory as external variables, to investigate the relationship among these variables and student’s cognitive learning effectiveness, in order to establish an extension of the Technology Acceptance Model.
This study surveyed students of a database management course who used a digital game-based system. It collected 322 valid questionnaires, and analyzed the results by SEM. The research results showed that, besides learning motivation, the information feedback will affect the learners perceived usefulness and ease of use, and indirectly affect intention to use. In addition, perceived usefulness will directly affect cognitive learning effectiveness, cognitive learning effectiveness will directly affect intention behavior, and game quality will directly affect intention behavior and cognitive learning effectiveness. Generally speaking, the extended Technology Acceptance Model had good explanatory power, and through examining how student learning motivation, the system of information feedback and game quality affect intention behavior, it verified that the game quality will positive affect cognitive learning effectiveness. The results of this study fill gaps in the literature, propose more feasible policies, so that digital game-based learning can always be used in the classroom, and provide a practical anaylsis of digital game-based learning with regard to user intention and behavior.
Future research can examine other types of digital game-learning courses, or further investigate cognitive entertainment factors, and can also increased with the use of time to investigate the intention use and actual use of digital game-based learning systems.
論文目次 中文摘要 i
Abstract iii
致謝 v
目錄 vi
表目錄 viii
圖目錄 x
第一章 緒論 1
第一節 研究動機 2
第二節 研究目的 3
第三節 研究範圍 4
第四節 研究流程 5
第二章 文獻探討 7
第一節 數位遊戲式學習(DGBL) 7
2.1.1 遊戲品質與特徵 8
第二節 科技接受模式(TAM) 12
第三節 認知學習成效 (Cognitive Learning Effectiveness) 15
第四節 資訊回饋(Information Feedback; IF) 18
2.3.1 結果回饋(Outcome Feedback) 18
2.3.2 前饋控制(Feedforward) 19
2.3.3 認知回饋(Cognitive Feedback) 19
第五節 學習動機(LM) 20
第六節 其他影響TAM之相關研究 22
2.5.1 TAM各構面與認知學習成效之間關係 23
2.5.2 遊戲品質與認知學習成效和TAM之間關係 24
2.5.3 資訊回饋與TAM之間關係 25
2.5.4 學習動機與TAM之間關係 27
第七節 小結 29
第三章 研究方法 32
第一節 系統介紹 32
3.1.1 系統架構 32
3.1.2 系統介面 36
第二節 研究模型 42
第三節 研究假說 44
第四節 衡量變項 51
第五節 問卷設計與前測 53
第六節 資料收集方式 60
第七節 資料分析方式 61
第四章 資料分析 72
第一節 敘述性統計分析 72
4.1.1 問卷回收概況 72
4.1.2 基本資料敘述性統計分析 72
4.1.3 研究變項敘述統計分析 74
4.1.4 研究構面的同質性檢定 78
4.1.5 研究變項的常態性檢定 83
第二節 信度分析 86
第三節 相關分析 90
第四節 結構方程模式-衡量模式 90
4.4.1 收斂效度分析 91
4.4.2 區別效度分析 111
4.4.3 整體配適度 112
第五節 結構方程模式-結構模式 114
4.5.1 結構模式整體適合度 114
4.5.2 路徑分析與假說檢定 115
第五章 結論與建議 125
第一節 研究發現與結論 125
第二節 研究貢獻 129
第三節 研究限制與未來研究方向 131
5.3.1 研究限制 131
5.3.2 未來研究方向 132
參考文獻 134
附錄一 前測問卷 142
附錄二 正式問卷 148
附錄三 衡量模式第一次刪題修正 154
附錄四 衡量模式第二次刪題修正 154
附錄五 衡量模式第三次刪題修正 155
附錄六 衡量模式第四次刪題修正 155
附錄七 衡量模式第五次刪題修正 156
附錄八 數位遊戲式學習系統操作情境 157
參考文獻 林子凱(2002)。線上遊戲『天堂』之使用者參與動機與滿意度研究。未出版之碩士論文,國立成功大學企業管理學系碩博士班,台南。
邱皓政(2003)。結構方程模式:LISREL的理論技術與應用。台北市:雙葉。
高豫(1996)。迎接電腦遊戲時代,新新人類新新文化-電腦遊戲在兒童教育的新角色。新幼教,9(1),4-8。
彭台光、高月慈、林鉦棽(2006)。管理研究中的共同方法變異:問題本質、影響、測試和補救。管理學報,23(1),77-98。
蕭文龍(2007)。多變量分析最佳入門實用書-SPSS+LISREL(SEM)。台北市:碁峰資訊。
Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16(2), 227-247.
Adomavicius, G., Curley, S. P., Gupta, A., & Sanyal, P. (2007). User perceptions in continuous combinatorial auctions: Effects of information feedback. Paper presented at the Twelfth INFORMS Conference on Information Systems and Technology(CIST).
Alessi, S. M., & Trollip, S. R. (2001). Multimedia for learning: Methods and Development. Boston: Allyn and Bacon.
Alshare, K. A., Freeze, R., & Kwun, O. (2009). Student intention to use expert systems: An exploratory study. Journal of Computer Information Systems, 49(4), 105-113.
Au, N., Ngai, E. W. T., & Cheng, T. C. E. (2008). Extending the understanding of end user information systems satisfaction formation: An equitable needs fulfillment model approach. MIS Quarterly, 32(1), 43-66.
Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human Relations, 45(7), 659-686.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
Bajaj, A., & Nidumolu, S. R. (1998). A feedback model to understand information system usage. Information & Management, 33(4), 213-224.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147.
Banerjee, A., Banerjee, P., Ye, N., & Dech, F. (1999). Assembly planning effectiveness using virtual reality. Presence: Teleoperators & Virtual Environments, 8(2), 204-217.
Barendregt, W., & Bekker, M. M. (2004). Towards a framework for design guidelines for young children's computer games. Paper presented at the The 2004 ICEC Conference, Netherlands.
Barendregt, W., Bekker, M. M., & Speerstra, M. (2003). Empirical evaluation of usability and fun in computer games for children. Paper presented at the Human-Computer Interaction-INTERACT'03, Switzerland.
Björkman, M. (1972). Feedforward and feedback as determiners of knowledge and policy: Notes on a Neglected Issue. Scandinavian Journal of Psychology, 13(1), 152-158.
Brinkerhoff, R. O. (1998). An integrated evaluation model for HRD. In D. L. Kirkpatrick (Ed.), Another Look at Evaluating Training Programs (pp. 78-80). Alexandria, Virginia: American Society for Training & Development.
Bushell, T. (2001). The role of the business game in management education. Paper presented at the Proceedings of the Conference Reflections On Teaching: Maintaining Quality in Changing Times, Low Wood, Lake Windermer.
Bushnell, D. S. (1990). Input, process, output: A model for evaluating training. Training & Development Journal, 44(3), 41-43.
Cagiltay, N. E. (2007). Teaching software engineering by means of computer-game development: Challenges and opportunities. British Journal of Educational Technology, 38(3), 405-415.
Cazier, J., Dowling, K., Santanam, R., & Louis, R. S. (2001). The effects of cognitive feedforward and feedback on the perceived usefulness and ease-of-use of complex models. Paper presented at the Proceedings of the Seventh Americas Conference on Information Systems (AMCIS 2001), Boston, USA.
Chenoweth, T., Dowling, K. L., & Louis, R. D. S. (2004). Convincing DSS users that complex models are worth the effort. Decision Support Systems, 37(1), 71-82.
Chiu, C. M., & Wang, E. T. G. (2008). Understanding Web-based learning continuance intention: The role of subjective task value. Information & Management, 45(3), 194-201.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
Davis, D. (2004). Business Research for Decision Making (6th ed.). Pacific Grove, California: Duxbury Press.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
Davis, F. D., & Kottemann, J. E. (1995). Determinants of decision rule use in a production planning task. Organizational Behavior and Human Decision Processes, 63(2), 145-157.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum.
Dinev, T., Qing, H., & Yayla, A. (2008). Is there an on-line advertisers' dilemma? A study of click fraud in the Pay-Per-Click model. International Journal of Electronic Commerce 13(2), 29-59.
Dondi, C., & Moretti, M. (2007). A methodological proposal for learning games selection and quality assessment. British Journal of Educational Technology, 38(3), 502-512.
Dweck, C. S., & Leggett, E. L. (1988). A Social-Cognitive approach to motivation and personality. Psychological Review, 95(2), 256-273.
Ebner, M., & Holzinger, A. (2007). Successful implementation of user-centered game based learning in higher education: An example from civil engineering. Computers & Education, 49(3), 873-890.
Finegan, P. (2006). Games: quality, localization and the world market. MultiLingual, 17(8), 56-61.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equations models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Fowler, F. J. (2002). Survey research methods (3rd ed.). Thousand Oaks, California: Sage Publications, Inc.
Fullerton, G. (2005). How commitment both enables and undermines marketing relationships. European Journal of Marketing, 39(11/12), 1372-1388.
Gardner, R. (2003). Games for business and economics (2nd ed.). Hoboken, New Jersey: John Wiley & Sons.
Garris, R., Ahlers, R., & Driskell, J. E. (2002). Games, motivation, and learning: A research and practice model. Simuation & Gaming, 33(4), 441-467.
Gonzalez, C. (2005). Decision support for real-time, dynamic decision-making tasks. Organizational Behavior and Human Decision Processes, 96(2), 142-154.
Graham, C., Cagiltay, K., Lim, B. R., Craner, J., & Duffy, T. M. (2001). Seven principles of effective teaching: A practical lens for evaluating online courses. The Technology Source March/April. Retrieved July 29, 2009, from http://www.technologysource.org/article/seven_principles_of_effective_teaching/
Greene, B. A., DeBacker, T. K., Ravindran, B., & Krows, A. J. (1999). Goals, values, and beliefs as predictors of a chievement and effort in high school mathematics classes. Sex Roles, 40(5-6), 421-458.
Guetl, C., Dreher, H., Williams, R., & Maurer, H. (2005). Game-based E-Learning applications by applying the E-Tester: A tool for auto-generated questions and automatic answer assessment. Paper presented at the World Conference on Educational Multimedia, Hypermedia and Telecommunications, Montreal, Canada.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2006). Multivariate data analysis. Upper Saddle River, New Jersey: Prentice Hall.
Hamblin, A. C. (1974). Evaluation and control of training. England: McGraw-Hill.
Ho, P. C., Chung, S. M., & Tsai, M. H. (2006). A case study of game design for e-learning. In Z. Pan (Ed.), Technologies for E-Learning and Digital Entertainment, Proceedings (Vol. 3942, pp. 453-462). Germany: Springer-Verlag Berlin Heidelberg.
Hogarth, R. M. (1981). Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics. Psychological Bulletin, 90(2), 197-217.
Holsapple, C. W., & Wu, J. (2008). Building effective online game websites with knowledge-based trust. Information Systems Frontiers, 10(1), 47-60.
Hsiao, N. (2000). Exploration of outcome feedback for dynamic decision making. Unpublished Ph.D.'s dissertation, State University of New York, Albany, New York, United States.
Hsu, W. K., & Huang, S. H. (2006). Determinants of computer self-efficacy- An examination of learning motivations and learning environments. Journal of Educational Computing Research, 35(3), 245-265.
Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
Huang, S. M., Wei, C. W., Yu, P. T., & Kuo, T. Y. (2006). An empirical investigation on learners' acceptance of e-learning for public unemployment vocational training. International Journal of Innovation and Learning, 3(2), 174-185.
Jacoby, J., Mazursky, D., Troutman, T., & Kuss, A. (1984). When feedback is ignored: Disutility of outcome feedback. Journal of Applied Psychology, 69(3), 531-545.
Jia, S., & Eder, L. B. (2009). Intentions to use virtual worlds for education. Journal of Information Systems Education, 20(2), 225-233.
Johnson, R. D., Hornik, S., & Salas, E. (2008). An empirical examination of factors contributing to the creation of successful e-learning environments. International Journal of Human-Computer Studies, 66(5), 356-369.
Juriševi, M., Glažar, S. A., Puko, C. R., & Devetak, I. (2008). Intrinsic motivation of pre-service primary school teachers for learning chemistry in relation to their academic achievement. International Journal of Science Education, 30(1), 87-107.
Kirkpatrick, D. L. (1998). Evaluating training programs: The four levels (2nd ed.). San Francisco, California: Berrett-Koehler.
Kirkpatrick, D. L., & Kirkpatrick, J. D. (2006). Evaluating training programs: The four levels (3rd ed.). San Francisco, California: Berrett-Koehler.
Kline, R. B. (1998). Principles and Practice of Structural Equation Modeling. New York: Guilford Press.
Lawrence, M., Goodwin, P., O'Connor, M., & Önkal, D. (2006). Judgmental forecasting: A review of progress over the last 25 years. International Journal of Forecasting, 22(3), 493-518.
Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12(Article 50), 752-780.
Lim, H., Lee, S. G., & Nam, K. (2007). Validating E-learning factors affecting training effectiveness. International Journal of Information Management, 27(1), 22-35.
Lombarts, K. M. J. M. H., Bucx, M. J. L., & Arah, O. A. (2009). Development of a System for the Evaluation of the Teaching Qualities of Anesthesiology Faculty. Anesthesiology, 111(4), 709-716.
Lopez-Nicolas, C., Molina-Castillo, F. J., & Bouwman, H. (2008). An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information & Management, 45(6), 359-364.
Mathieson, K., & Keil, M. (1998). Beyond the interface: Ease of use and task/technology fit. Information & Management, 34(4), 221-230.
Merrill, P. F., Hammons, K., Vincent, B. R., Reynolds, P. L., Christensen, L., & Tolman, M. N. (1996). Computers in education (3rd ed.). Boston: Allyn & Bacon.
Moreno-Ger, P., Burgos, D., Martínez-Ortiz, I., Sierra, J. L., & Fernández-Manjón, B. (2008). Educational game design for online education. Computers in Human Behavior, 24(6), 2530-2540.
Nalanagula, D., Greenstein, J. S., & Gramopadhye, A. K. (2006). Evaluation of the effect of feedforward training displays of search strategy on visual search performance. International Journal of Industrial Ergonomics, 36(4), 289-300.
Neuman, W. L. (2006). Social research methods: qualitative and quantitative approaches (6th ed.). Boston, Massachusetts: Pearson/Allyn and Bacon.
Ngai, E. W. T., Poon, J. K. L., & Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers & Education, 48(2), 250-267.
Nicholls, J. G. (1984). Achievement motivation: Conceptions of ability, subjective experience, task choice, and performance. Psychological Review, 91(3), 328-346.
Nysveen, H., Pedersen, P. E., & Thorbjornsen, H. (2005). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330-346.
O'Neil, H. F., Wainess, R., & Baker, E. L. (2005). Classification of learning outcomes: evidence from the computer games literature. Curriculum Journal, 16(4), 455-474.
Oliver, J. J. (1993, Jan. 4-7). Decision graphs-An extension of decision trees. Paper presented at the Proceedings of the Fourth International Workshop on Artificial Intelligence and Statistics, Fort Lauderdale, Florida, USA.
Oliver, J. J., & Hand, D. (1996). Averaging over decision trees. Journal of Classification, 13(2), 281-297.
Ong, C. S., Lai, J. Y., & Wang, Y. S. (2004). Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies. Information & Management, 41(6), 795-804.
Ozkan, S., & Koseler, R. (2009). Multi-dimensional students' evaluation of e-learning systems in the higher education context: An empirical investigation. Computers & Education, 53(4), 1285-1296.
Papastergiou, M. (2009). Digital Game-Based Learning in high school Computer Science education: Impact on educational effectiveness and student motivation. Computers & Education, 52(1), 1-12.
Pintrich, P. R. (1989). The dynamic interplay of student motivation and cognition in the college classroom. In M. L. Maehr & C. Ames (Eds.), Advance in Motivation and Achievement: Motivation Enhancing Environments (Vol. 6, pp. 117-160). Greenwich: JAI Press.
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire(MSLQ). Ann Arbor: University of Michigan.
Pituch, K. A., & Lee, Y. K. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222-244.
Pivec, M. (2007). Editorial: Play and learn: Potentials of game-based learning. British Journal of Educational Technology, 38(3), 387-393.
Pivec, M., & Kearney, P. (2007). Games for Learning and Learning from Games. Organizacija, 40(6), 267-272.
Prensky, M. (2001). Digital Game-Based Learning. Saint Paul, Minn: Paragon House.
Said, L. R. (2005). The influences of cognitive, experiential and habitual factors in online games playing. Unpublished Ph.D.'s dissertation, The University of Western Australia, Perth, Australia.
Schifter, C., & Ketelhut, D. (2009). Teacher Acceptance of Game-Based Learning in K-12: The Case of River City. Paper presented at the Proceedings of Society for Information Technology and Teacher Education International Conference 2009, Chesapeake, VA.
Selim, H. M. (2003). An empirical investigation of student acceptance of course websites. Computers & Education, 40(4), 343-360.
Sengupta, K., & Abdel-Hamid, T. K. (1993). Alternative conceptions of feedback in dynamic decision environments: An experimental investigation. Management Science, 39(4), 411-428.
Shao, Y., & Macari, E. J. (2008). Information feedback analysis in deep excavations. International Journal of Geomechanics, 8(1), 91-103.
Sharma, S. (1996). Applied Multivariate Techniques. New York: J. Wiley.
Shin, D. H. (2007). User acceptance of mobile Internet: Implication for convergence technologies. Interacting with Computers, 19(4), 472-483.
Shin, D. H. (2008). Understanding purchasing behaviors in a virtual economy: Consumer behavior involving virtual currency in Web 2.0 communities. Interacting with Computers, 20(4-5), 433-446.
Small, R. V., & Gluck, M. (1994). The relationship of motivational conditions to effective instructional attributes: A magnitude scaling. Educational Technology, 34(8), 33-40.
Spinath, B., & Spinath, F. M. (2005). Longitudinal analysis of the link between learning motivation and competence beliefs among elementary school children. Learning and Instruction, 15(2), 87-102.
Straub, D., Limayen, M., & Karahanna-Evaristo, E. (1995). Measuring system usage: Implications for IS theory testing. Management Science, 41(8), 1328-1343.
Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202.
Tanaka, J. S. (1987). How Big is Enough? Sample Size and Goodness-of-Fit Structural Equation Models with Latent Variables. Child Development, 58(1), 134-146.
Tao, Y. H., Cheng, C. J., & Sun, S. Y. (2009). What influences college students to continue using business simulation games? The Taiwan experience. Computers & Education, 53(3), 929-939.
Tayie, S. (2005). Research Methods and Writing Research Proposals. Giza, Egypt: Center for Advancement of Postgraduate Studies and Research in Engineering Sciences, Faculty of Engineering - Cairo University (CAPSCU).
Teo, T., & Noyes, J. (2008). Development and validation of a computer attitude measure for young students (CAMYS). Computers in Human Behavior, 24(6), 2659-2667.
Toral, S. L., Barrero, F. J., & Torres, R. M. (2007). Analysis of utility and use of a web-based tool for digital signal processing teaching by means of a technological acceptance model. Computers & Education, 49(4), 957-975.
Turkle, S. (1995). Life on the screen: identity in the age of the Internet. New York: Simon & Schuster.
Tzou, R. C., & Lu, H. P. (2009). Exploring the emotional, aesthetic, and ergonomic facets of innovative product on fashion technology acceptance model. Behaviour & Information Technology, 28(4), 311-322.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
Vredenburg, K. (1999). Increasing ease of use. Communications of the ACM, 42(5), 67-71.
Wheaton, B., Muthen, B., Alwin, D. F., & Summers, G. F. (1977). Assessing reliability and stability in panel models. Sociological Methodology, 8, 84-136.
Wigfield, A. (1994). Expectancy-value theory of achievement motivation: A developmental perspective. Educational Psychology Review, 6(1), 49-79.
Wigfield, A., & Eccles, J. S. (1992). The development of achievement task values: A theoretical analysis. Developmental Review, 12(3), 265-310.
Wigfield, A., & Eccles, J. S. (2000). Expectancy-Value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68-81.
Wu, J., Li, P., & Rao, S. (2008). Why they enjoy virtual game worlds? An empirical investigation. Journal of Electronic Commerce Research, 9(3), 219-230.
Young, M. R., Klemz, B. R., & Murphy, J. W. (2003). Enhancing learning outcomes: The effects of instructional technology, learning styles, instructional methods, and student behavior. Journal of Marketing Education, 25(2), 130-142.
Zapata, C. M., & Awad-Aubad, G. (2007). Requirements game: Teaching software project management. CLEI electronic journal, 10(1), 1-11.
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