Modeling Key Drivers of E-Learning Satisfaction among Student Teachers

This study explored the key drivers of student teachers' e-learning satisfaction. Three hundred and eighty-seven participants completed a survey questionnaire measuring their self-reported responses to six constructs (tutor quality, perceived usefulness, perceived ease of use, course delivery, facilitating conditions, and course satisfaction). Data analysis was performed using structural equation modeling. The results of this study showed that, apart from facilitating conditions, all constructs were significant predictors of e-learning satisfaction. However, facilitating conditions was found to be a significant mediator of perceived ease of use and satisfaction. Some implications for e-learning and teacher education were discussed.

[1]  Ahmad Fauzi Mohd Ayub,et al.  A review of the literature: determinants of online learning among students , 2009 .

[2]  Raafat George Saadé,et al.  Web-Based Educational Information System for Enhanced Learning, EISEL: Student Assessment , 2003, J. Inf. Technol. Educ..

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

[4]  Timothy Teo,et al.  Modelling technology acceptance in education: A study of pre-service teachers , 2009, Comput. Educ..

[5]  J. Arbaugh,et al.  Technological and Structural Characteristics, Student Learning and Satisfaction with Web-Based Courses , 2002 .

[6]  Daniel W. Surry,et al.  A model for integrating instructional technology into higher education , 2005, Br. J. Educ. Technol..

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

[8]  Joseph S. Valacich,et al.  E-Learning as an Emerging Entrepreneurial Enterprise in Universities and Firms , 2003, Commun. Assoc. Inf. Syst..

[9]  Ed Smeets,et al.  Does ICT contribute to powerful learning environments in primary education? , 2005, Comput. Educ..

[10]  Jung Wan Lee Online support service quality, online learning acceptance, and student satisfaction , 2010, Internet High. Educ..

[11]  Jay F. Nunamaker,et al.  Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness , 2006, Inf. Manag..

[12]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[13]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[14]  Carlene Reinhart How To Leap over Barriers to Performance. , 2000 .

[15]  A. Romiszowski How's the E-learning Baby? Factors Leading to Success or Failure of an Educational Technology Innovation , 2004 .

[16]  Won-Gyu Lee,et al.  Assistance and possibilities: Analysis of learning-related factors affecting the online learning satisfaction of underprivileged students , 2011, Comput. Educ..

[17]  Timothy Teo,et al.  Investigating the Technology Acceptance among Student Teachers in Malaysia: An Application of the Technology Acceptance Model (TAM) , 2009 .

[18]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[19]  Yi-Shun Wang,et al.  Assessment of learner satisfaction with asynchronous electronic learning systems , 2003, Inf. Manag..

[20]  Timothy Teo,et al.  Understanding pre-service teachers' computer attitudes: applying and extending the technology acceptance model , 2007, J. Comput. Assist. Learn..

[21]  Peter Shea,et al.  Learning presence: Towards a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments , 2010, Comput. Educ..

[22]  Ismail Yuksel Instructor Competencies for Online Courses , 2009 .

[23]  Brigitte Maier,et al.  Students' expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction , 2010, Comput. Educ..

[24]  T. Teo,et al.  Understanding Technology Acceptance in Pre-Service Teachers: A Structural-Equation Modeling Approach , 2009 .

[25]  J. Laffey,et al.  Social Influence for Perceived Usefulness and Ease-of-Use of Course Delivery Systems. , 2006 .

[26]  David A. Bradbard,et al.  Technical Note: Desktop Management in Practice , 2003, Commun. Assoc. Inf. Syst..

[27]  Keenan A. Pituch,et al.  The influence of system characteristics on e-learning use , 2006, Comput. Educ..

[28]  Gurmak Singh,et al.  Implementing eLearning Programmes for Higher Education: A Review of the Literature , 2004, J. Inf. Technol. Educ..

[29]  V. A. Thurmond,et al.  Evaluation of Student Satisfaction: Determining the Impact of a Web-Based Environment by Controlling for Student Characteristics , 2002 .

[30]  D. Bolliger Key Factors for Determining Student Satisfaction in Online Courses , 2004 .

[31]  Shu-Sheng Liaw,et al.  Investigating students' perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system , 2008, Comput. Educ..

[32]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[33]  Hasan Çakir,et al.  Research in online learning environments: Priorities and methodologies , 2011, Comput. Educ..

[34]  HwangYujong,et al.  Predicting the use of web-based information systems , 2003 .

[35]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[36]  Jan Noyes,et al.  An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach , 2011, Comput. Educ..

[37]  Dowming Yeh,et al.  What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction , 2008, Comput. Educ..

[38]  Charles D. Dziuban,et al.  Student satisfaction with online learning in the presence of ambivalence: Looking for the will-o'-the-wisp , 2013, Internet High. Educ..

[39]  R. Henson Understanding Internal Consistency Reliability Estimates: A Conceptual Primer on Coefficient Alpha , 2001 .

[40]  Michael T. Miller,et al.  Serving Non-Traditional Students in E-Learning Environments: Building Successful Communities in the Virtual Campus , 2003 .

[41]  Cher Ping Lim,et al.  Managing Teachers’ Barriers to ICT Integration in Singapore Schools , 2006 .

[42]  Elmarie Engelbrecht,et al.  Adapting to changing expectations: Post-graduate students' experience of an e-learning tax program , 2005, Comput. Educ..

[43]  Timothy Teo,et al.  Assessing the intention to use technology among pre-service teachers in Singapore and Malaysia: A multigroup invariance analysis of the Technology Acceptance Model (TAM) , 2009, Comput. Educ..

[44]  Melissa M. Groves,et al.  Instructional Technology Adoption in Higher Education: An Action Research Case Study , 2000 .

[45]  Sirkka L. Jarvenpaa,et al.  The Use of Information Technology to Enhance Management School Education: A Theoretical View , 1995, MIS Q..

[46]  A. Yuen,et al.  Exploring teacher acceptance of e‐learning technology , 2008 .

[47]  Richard,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace , 2022 .

[48]  Raymond McNamara,et al.  The Effect of Synchronous and Asynchronous Participation on Students' Performance in Online Accounting Courses , 2012 .

[49]  M. Sobel Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .

[50]  Chien-Hung Liu,et al.  Learning effectiveness in a Web-based virtual learning environment: a learner control perspective , 2005, J. Comput. Assist. Learn..

[51]  Susan Powers,et al.  Technology and Teacher Education: A Guide for Educators and Policymakers , 2002 .

[52]  Tapabrata Maiti,et al.  Principles and Practice of Structural Equation Modeling (2nd ed.) , 2006 .

[53]  Dogan Ibrahim,et al.  Assessing the Success Rate of Students Using a Learning Management System Together with a Collaborative Tool in Web-Based Teaching of Programming Languages , 2007 .

[54]  Karl G. Jöreskog,et al.  Lisrel 8: User's Reference Guide , 1997 .

[55]  Marcia J. Simmering,et al.  E-learning: emerging uses, empirical results and future directions , 2003 .

[56]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[57]  J. Arbaugh Managing the on-line classroom , 2002 .

[58]  Milena M. Head,et al.  Who is Responsible for E-Learning Success in Higher Education? A Stakeholders' Analysis , 2008, J. Educ. Technol. Soc..

[59]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[60]  Blake Ives,et al.  Web-based Virtual Learning Environments: a Research Framework and a Preliminary Assessment of Effectiveness in Basic It Skills Training Author(s): Piccoli Et Al./web-based Virtual Learning Environments Web-based Virtual Learning Environments: a Research Framework and a Preliminary Assessment of Effe , 2022 .

[61]  Robert Andersson,et al.  Examining user acceptance of computer technology: an empirical study of student teachers , 2005, J. Comput. Assist. Learn..

[62]  G. A. Marcoulides,et al.  An Introduction to Applied Multivariate Analysis , 2008 .