Activate Interaction Relationships Between Students Acceptance Behavior and E-Learning

The purpose and characteristics of e-learning are different from other Web applications. This paper uses an extended Technology Acceptance Model (TAM) to explain the motivation, attitude and acceptance behind participants of e-learning. The factors that determine Web quality include the external variables: system functionality, interface design, pedagogic and contents, as well as community. Perceived enjoyment was also added to this model as a factor. The empirical results indicated that the extended TAM explains the acceptability of on-line learning systems with high reliability, validity, and model fitness. All "beliefs" (user perceptions) - perceived usefulness, ease of use, and enjoyment - are good predictors of attitude and acceptance. Pedagogic, and content as well as community are important external factors that predict e-learning acceptance.

[1]  Richard A. Johnson,et al.  Applying the Technology Acceptance Model to the WWW , 2000 .

[2]  Brett J. L. Landry,et al.  Measuring Student Perceptions of Blackboard Using the Technology Acceptance Model , 2006 .

[3]  S. Mulaik,et al.  EVALUATION OF GOODNESS-OF-FIT INDICES FOR STRUCTURAL EQUATION MODELS , 1989 .

[4]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[5]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[6]  Young-Gul Kim,et al.  Extending the TAM for a World-Wide-Web context , 2000, Inf. Manag..

[7]  Gary Klein,et al.  Measuring Information System Service Quality: SERVQUAL from the Other Side , 2002, MIS Q..

[8]  A. Parasuraman,et al.  SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. , 1988 .

[9]  Hans van der Heijden,et al.  Factors influencing the usage of websites: the case of a generic portal in The Netherlands , 2003, Inf. Manag..

[10]  Mary Jo Bitner,et al.  Self-Service Technologies: Understanding Customer Satisfaction with Technology-Based Service Encounters , 2000 .

[11]  Marc Prensky,et al.  Digital game-based learning , 2000, CIE.

[12]  Peter M. Bentler,et al.  EQS : structural equations program manual , 1989 .

[13]  Richard T. Vidgen,et al.  Measuring Web site quality improvements: a case study of the forum on strategic management knowledge exchange , 2003, Ind. Manag. Data Syst..

[14]  Judy Chuan-Chuan Lin,et al.  Towards an understanding of the behavioural intention to use a web site , 2000, Int. J. Inf. Manag..

[15]  Tracy Chao,et al.  Establishing a Quality Review for Online Courses , 2006 .

[16]  Helmut Schneider,et al.  Web site design benchmarking within industry groups , 2003, Internet Res..

[17]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[18]  R. P. McDonald,et al.  Principles and practice in reporting structural equation analyses. , 2002, Psychological methods.

[19]  Barrie Dale,et al.  Key quality factors in Web site design and use: an examination , 2002 .

[20]  K. Kiili.  Digital game-based learning: Towards an experiential gaming model , 2005, Internet High. Educ..

[21]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .