An empirical investigation into factors influencing the adoption of an e-learning system

Purpose – The purpose of this research is to investigate the factors affecting the adoption of the e‐learning system (ELS) in mandatory and voluntary settings, through an extension of the technology acceptance model (TAM).Design/methodology/approach – Regression analysis was used to observe the associations of proposed constructs.Findings – The results of the study confirm the original TAM findings. In mandatory settings, students would only intend to use the ELS. Computer self‐efficacy demonstrated significant influence on perceived ease of use. Effects of course attributes on perceived usefulness were negatively significant. Effects of content quality on perceived usefulness were significant. This study found that the effects of subjective norm significantly influenced perceived usefulness in both settings. Also, perceived network externality exerts a significant direct effect on usage intentions, perceived usefulness, and perceived ease of use. This research implied that, first of all, mandatory usage ...

[1]  Deborah Compeau,et al.  Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study , 1999, MIS Q..

[2]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[3]  Doris Lee,et al.  Web‐based Learning in Corporations: who is using it and why, who is not and why not? , 2002 .

[4]  C. Iwasiw,et al.  The effects of computer-assisted instruction on the self-efficacy of baccalaureate nursing students. , 1999, The Journal of nursing education.

[5]  Louis Raymond,et al.  Organizational Characteristics and MIS Success in the Context of Small Business , 1985, MIS Q..

[6]  Eric T. G. Wang,et al.  Electronic data interchange: competitive externalities and strategic implementation policies , 1995 .

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

[8]  Mark Stansfield,et al.  Facilitating Online Learning , 2004 .

[9]  David Gefen,et al.  TAM or Just Plain Habit: A Look at Experienced Online Shoppers , 2003, J. Organ. End User Comput..

[10]  Bassam Hasan,et al.  An Empirical Examination of a Model of Computer Learning Performance , 2004, J. Comput. Inf. Syst..

[11]  Gordon B. Davis,et al.  Testing the Determinants of Microcomputer Usage via a Structural Equation Model , 1995, J. Manag. Inf. Syst..

[12]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

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

[14]  Denis M. S. Lee.  Usage Patterns and Sources of Assistance for Personal Computer Users , 1986, MIS Q..

[15]  C. Shapiro,et al.  Network Externalities, Competition, and Compatibility , 1985 .

[16]  Chorng-Shyong Ong,et al.  Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies , 2004, Inf. Manag..

[17]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[18]  M. Deutsch,et al.  A study of normative and informational social influences upon individual judgement. , 1955, Journal of abnormal psychology.

[19]  Diane M. Strong,et al.  Perceived critical mass effect on groupware acceptance , 2000, Eur. J. Inf. Syst..

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

[21]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[22]  David A. Harrison,et al.  Volunteer Motivation and Attendance Decisions: Competitive Theory Testing in Multiple Samples From a Homeless Shelter , 1995 .

[23]  Pin-Yu Chu,et al.  Factors influencing household waste recycling behavior: Test of an integrated model , 2003 .

[24]  Thomas W Peterman.  Elements of success at a traditional/virtual university: lessons learned from three years of growth in cyberspace , 2000 .

[25]  VenkateshViswanath.  Determinants of Perceived Ease of Use , 2000 .

[26]  Detmar W. Straub,et al.  The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption , 2000, J. Assoc. Inf. Syst..

[27]  Chin-Lung Hsu,et al.  Why do people play on-line games? An extended TAM with social influences and flow experience , 2004, Inf. Manag..

[28]  Keng Siau,et al.  Measuring information quality of web sites: development of an instrument , 1999, ICIS.

[29]  Ritu Agarwal,et al.  The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies , 1997 .

[30]  Janet Burns,et al.  UNDERSTANDING OF UNDERSTANDING: IMPLICATIONS FOR LEARNING AND TEACHING , 1991 .

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

[32]  Mark H. Davis,et al.  Declines in Major League Batting Performance as a Function of Game Pressure: A Drive Theory Analysis1 , 1992 .

[33]  B. R. Nault,et al.  Adoption, Transfers and Incentives in a Franchise Network with Positive Externalities , 1994 .

[34]  Fatemeh Zahedi,et al.  The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach , 2002, Inf. Syst. Res..

[35]  Bernadette Szajna,et al.  Empirical evaluation of the revised technology acceptance model , 1996 .

[36]  Charles D. Barrett.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[37]  Ke Te Le Mei Ru He Deng Yi.  Marketing management: analysis. planning. implementation and control , 2000 .

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

[39]  Der-Thanq Chen,et al.  Internet-Based Instructional Activities , 2003 .

[40]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[41]  Magid Igbaria,et al.  Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model , 1997, MIS Q..

[42]  Susan L. Holak.  Determinants of innovative durables adoption an empirical study with implications for early product screening , 1988 .

[43]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[44]  Robert A. Reiser,et al.  The Effects of Self-Regulation and Instructional Control on Performance and Motivation in Computer-based Instruction , 2000 .

[45]  Donnie Kirk,et al.  Facilitating Online Learning: Effective Strategies for Moderators , 2003, J. Educ. Technol. Soc..

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

[47]  I. Ajzen.  The theory of planned behavior , 1991 .

[48]  Lisa Boisvert,et al.  Web-Based Learning: The Anytime Anywhere Classroom , 2000, Inf. Syst. Manag..

[49]  Thomas Fox McManus,et al.  Individualizing instruction in a web-based hypermedia learning environment: nonlinearity, advance organizers, and self-regulated learners , 2000 .

[50]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[51]  Terry Ryan,et al.  The Role of Social Presence and Moderating Role of Computer Self-Efficacy in Predicting the Continuance Usage of E-Learning Systems , 2004, J. Inf. Syst. Educ..

[52]  Robin Mason,et al.  Factors affecting students' satisfaction on a web course , 2000 .

[53]  Robert W. Lent,et al.  Relation of self-efficacy expectations to academic achievement and persistence. , 1984 .

[54]  A. Bandura.  Self-efficacy mechanism in human agency. , 1982 .

[55]  A. Bandura.  Self-Efficacy: The Exercise of Control , 1997, Journal of Cognitive Psychotherapy.

[56]  Chew Seong Cheong.  E-learning - a provider's prospective , 2001, Internet High. Educ..

[57]  Mun Y. Yi,et al.  Predicting Computer Task Performance: Personal Goal and Self-Efficacy , 2004, J. Organ. End User Comput..

[58]  Sui Meng Poon,et al.  Factors influencing the types of products and services purchased over the Internet , 2000, Internet Res..

[59]  Hassan M. Selim,et al.  An empirical investigation of student acceptance of course websites , 2003, Comput. Educ..

[60]  J. Arbaugh.  Virtual Classroom Characteristics and Student Satisfaction with Internet-Based MBA Courses , 2000 .

[61]  Detmar W. Straub,et al.  Gender Differences in the Perception and Use of E-Mail: An Extension to the Technology Acceptance Model , 1997, MIS Q..

[62]  Hal R. Varian,et al.  Information rules - a strategic guide to the network economy , 1999 .

[63]  Cathy Goodwin.  A Social Influence Theory of Consumer Cooperation , 1987 .

[64]  P H Abelson,et al.  Lifelong Learning , 2010, Encyclopedia of Machine Learning.

[65]  Steve G. Sutton,et al.  The changing face of accounting in an information technology dominated world , 2000, Int. J. Account. Inf. Syst..

[66]  Dolly Goldenberg,et al.  Effects of computer-based clinical conferencing on nursing students' self-efficacy. , 2004, The Journal of nursing education.

[67]  Dongsong Zhang,et al.  Enhancing E-Learning with Interactive Multimedia , 2003, Inf. Resour. Manag. J..