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An Integrative Model to Predict the Continuance Use of Electronic Learning Systems: Hints for Teaching
Article
Jiinpo Wu, Tamkang University, Taiwan ; Ray J. Tsai, St. Cloud State University, United States ; Charlie C. Chen, Appalachian State University, United States ; Yachen Wu, Tamkang University, Taiwan
International Journal on E-Learning, ISSN 1537-2456 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Abstract
There is an increased expectation about the usefulness of electronic learning (e-learning) to complement or substitute traditional face-to-face learning. However, the growth rate of the e-learning market has not properly reflected the high expectation. Researchers began to direct their attention to the assessment of e-learning effectiveness in order to solve the issue. However, little has been known about why some users stop adopting e-learning after their initial experience. Our work focuses on investigating the continuance usage problems in the field of information technology. A theoretical framework is proposed to address the continuance issue. This integrative framework makes three major contributions. First, it integrates the frameworks of computer self-efficacy (CSE) and the expectation-confirmation model (ECM). Second, it theorizes the causal relationship between the factors of perceived usefulness, confirmation, satisfaction, and information system (IS) continuance in the e-learning context. Finally, it explains users' online learning behaviors through a field survey. The results indicate that, in the context of learning conceptual knowledge in undergraduate education, there are significant relationships among the CSE of online learners, their perceived usefulness, confirmation, and satisfaction levels.
Citation
Wu, J., Tsai, R.J., Chen, C.C. & Wu, Y. (2006). An Integrative Model to Predict the Continuance Use of Electronic Learning Systems: Hints for Teaching. International Journal on E-Learning, 5(2),. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved August 15, 2024 from https://www.learntechlib.org/primary/p/5781/.
© 2006 Association for the Advancement of Computing in Education (AACE)
Keywords
References
View References & Citations Map- Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of emprical research. Psychological Bulletin, 84, 888-918.
- Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12(2), 125-143.
- Bandura, A. (1977). Social learning theory. N.J.: Englewood Cliffs: Prentice-Hall.
- Barki, H., & Huff, S. (1985). Change, attitude to change, and decision support success. Information and Management, 9(5), 261-268.
- Barling, J., & Beattie, R. (1983). Self-efficacy beliefs and sales performance. Journal of Organizational Behavior Management, 5, 41-51.
- Betz, N. E., & Hackett, G. (1981). The relationship of career-related self-efficacy expectations to perceived career options in college women and men. Journal of Counseling Psychology, 28, 399-410.
- Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation confirmation model. MIS Quarterly, 25(3), 351-370.
- Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19, 189-211.
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982-1003.
- Gist, M. E., & Mitchell, T. R. (1992). Self-efficacy: A theoretical analysis of its determinants and malleability. Academy of Management Review, 17(2), 183-211.
- Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectation in predicting the decision to use advanced technologies: The case of computers. Journal of Applied Psychology, 72(2), 307-313.
- Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption benefits. MIS Quarterly, 23(2), 183-213.
- Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support Systems, 29, 269-282.
- Locke, E. A. (1976). The nature and causes of job satisfaction. Chicago: Rand McNally. Mathieson, K. (1991). Predicting user intentions: Comparing the theory of planned behavior. Information Systems Research, 2(3), 173-191.
- Oliver, R. L. (1980). A cognitive model for the antecedents and consequences of satisfaction. Journal of Marketing Research, 17, 460-469.
- Oliver, R. L. (1993). Cognitive, affective, and attributes bases of the satisfaction response. Journal of Consumer Research, 20, 418-430.
- Patterson, P. G. Johnson, L. W., & Spreng, R. A. (1997). Modeling the determinants of customer satisfaction for business-to-business professional services. Journal of the Academy of Marketing Science, 25(1), 4-17.
- Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational Psychology, 26, 207-231. Spreng, R. A., & Olshavsky, R. W. (1993). A desires congruency model of consumer satisfaction. Journal of the Academy of Marketing Science, 21(3), 169-177.
- Stumpf, S. A., Brief, A. P., & Hartman, K. (1987). Self-efficacy expectations and coping with career-related events. Journal of Vocational Behavior, 31(2), 91-108.
- Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561-570.
- Venkatesh, V., and Davis, F. D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27(3), 451-481.
- Webster, J., and Martocchio, J. J. (1992). Microcomputer Playfulness: Development of a Measure With Workplace Implications. MIS Quarterly, 16(2), 201-226.
- Wood, R. E., and Bandura, A. (1989). Impact of Conceptions of Ability on Self-regulatory Mechanisms and Complex Decision-making. Journal of Personality and Social Psychology, 56, 407-415.
- Zhang, Y., and Espinoza, S. (1998). Relationships Among Computer Self-efficacy, Attitudes Toward Computers, and Desirability of Learning Computing Skills. Journal of Research on Computing in Education, 30(4), 420-437.
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-
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