You are here:

Critical factors affecting e-learner’s satisfaction an empirical study PROCEEDINGS

, University of Tehran, Iran (Islamic Republic Of) ; , AmirKabir University of Technology, Iran (Islamic Republic Of) ; , University of Tehran, Iran (Islamic Republic Of)

EdMedia + Innovate Learning, in Toronto, Canada ISBN 978-1-880094-81-5 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC

Abstract

With the increasingly growth of demand for higher education in the last decade, the role of E-learning technology as a new pedagogy that empowered by digital technology drastically developed. The challenge for the education enterprise now is how to attract learners to their e-learning services. Results from several studies show that students’ satisfaction with e-learning is a key indicator in student’s decision to remain or dropout from e-learning courses. In this study we first reviewed related researches then applied local hypothesis. Testing these assumptions, we conclude some factors to be more impressive in student’s satisfaction. Finally meaningful factors were suggested to establish successful E-learning education and more satisfaction

Citation

Khodabandeh, A., Afshari, H. & Manian, A. (2010). Critical factors affecting e-learner’s satisfaction an empirical study. In J. Herrington & C. Montgomerie (Eds.), Proceedings of ED-MEDIA 2010--World Conference on Educational Multimedia, Hypermedia & Telecommunications. Toronto, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved November 19, 2018 from .

Keywords

View References & Citations Map

References

  1. Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186−204.
  2. Mark Nichols. (2008). E-Primer Series– E-Learning in Context. Page 2 H.-L. Liao, H.-P. Lu.(2008). The role of experience and innovation characteristics in the adoption and continued use of e-learning websites. Journal of Computers& Education 51, 1405–1416
  3. Wu, J.P., Tsai, R.J., Chen, C.C., & Wu, Y.C. (2006). An integrative model to predict the continuance use of electronic learning systems: hints for teaching. International Journal on E-Learning, 5(2), 287–302.
  4. Flood, G. (2006). Make it specific. Human Resources, 64–66.
  5. Levy, Y. (2003). A study of learners_ perceived value and satisfaction for implied effectiveness of online learning systems. Dissertation Abstracts International 65(03), 1014A. (UMI No. AAT 3126765). Retrieved Oct 13, 2004, from Digital Dissertations database.
  6. Sachs, D., & Hale, N. (2003). Pace university_s focus on student satisfaction with student services in online education. Journal of Asynchronous Learning Networks, 7(2), 36–42.
  7. Chyung, Y., Winiecki, D.J. & Fenner, J.A. (1998). A case study: increase enrollment by reducing dropout rates in adult distance education. In Proceedings of the annual conference on distance teaching& Learning, Madison, WI.
  8. Fredericksen, E., Pickett, A., Shea, P., Pelz, W., & Swan, K. (2000). Student satisfaction and perceived learning with online courses: principles and examples from the SUNY learning network. Journal of Asynchronous Learning Networks, 4(2), 7–41.
  9. Bonk, C., & Cunningham, D. (1998). Searching for learner-centered, constructivist, and sociocultural components of collaborative educational learning tools. In C. Bonk& K. King (Eds.), Electronic collaborators: Learner-centered technologies for literacy, apprenticeship, and discourse (pp. 25 – 50). Mahwah, NJ: Lawrence Erlbaum Associates.
  10. Spiro, R.J., Feltovich, P.J., Jacobson, M.J., & Coulson, R.L. (1991). Knowledge representation, content specification, and the development of skill in situation-specific knowledge assembly: Some constructivist issues as they relate to cognitive flexibility theory and hypertext. Educational Technology, 31 (9), 22 – 25.
  11. Alonso, F., Lopez, G., Manrique, D., & Vines, J.M. (2005). An instructional model for web-based e-learning education with a blended learning process approach. British Journal of Educational Technology, 36 (2), 217 – 235.
  12. Salomon, G. (1983). The differential investment of mental effort in learning from different sources. Educational Psychologist, 18, 42 – 50.
  13. Jonassen, D.H. (2003). Learning to solve problems with technology: A constructivist perspective. Upper Saddle River, NJ: Merrill.
  14. Laurillard, D. (2002). Rethinking university teaching: A framework for the effective use of educational technology (2nd ed.). London: Routledge.
  15. Bransford, J.D., Brown, A.L., & Cocking, R.R. (Eds.) (2000). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press.
  16. Alonso, F., Lopez, G., Manrique, D., & Vines, J.M. (2005). An instructional model for web-based e-learning education with a blended learning process approach. British Journal of Educational Technology, 36 (2), 217 – 235.
  17. Weigel, V.B. (2002). Deep learning for a digital age: Technology‟ s untapped potential to enrich higher education. San Francisco, CA: Jossey-Bass.
  18. Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: a research framework and a preliminary assessment of effectiveness in basic IT skill training. MIS Quarterly, 25(4), 401–426.
  19. Edmonds, R. (2004). Best practices in e-learning. Menlo Park, CA: SRI Business Consulting Intelligence.
  20. Ajzen, I., & Fishbein, M. (1977). Attitude–behavior relations: a theoretical analysis and review of empirical research. Psychological Bulletin, 84, 888–918.
  21. 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.
  22. Oliver, R.L. (1980). A cognitive model for the antecedents and consequences of satisfaction. Journal of Marketing Research, 17, 460–469.
  23. Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation confirmation model. MIS Quarterly, 25(3), 270–351.
  24. Wu, J.P., Tsai, R.J., Chen, C.C., & Wu, Y.C. (2006). An integrative model to predict the continuance use of electronic learning systems: hints for teaching. International Journal on E-Learning, 5(2), 287–302.
  25. Doll, W.J. And Torkzadeh, G. (1988), “The measurement of end-user computing satisfaction”, MIS Quarterly, Vol. 12 No. 2, pp. 259-74.
  26. Arbaugh, J.B. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of Management Education, 24(1), 32–54.
  27. Stokes, S.P. (2001). Satisfaction of college students with the digital learning environment. Do Learners‟ temperaments make a difference? Internet and High Education, 4, 31–44.
  28. Arbaugh, J.B. (2002). Managing the on-line classroom: a study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13, 203–223.
  29. Hong, K.S. (2002). Relationships between students‟ and instructional variables with satisfactionand learning from a Webbased course. Internet and Higher Education, 5, 267–281.
  30. Thurmond, V.A., Wambach, K., & Connors, H.R. (2002). Evaluation of student satisfaction: determining the impact of a web-based environment by controlling for student characteristics. The American Journal of Distance Education, 16(3), 169– 189.
  31. Wang, Y.S. (2003), “Assessment of learner satisfaction with asynchronous electronic learning systems”, Information and Management, Vol. 41 No. 1, pp. 75-86.
  32. Barbeite, F.G., & Weiss, E.M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20, 1–15.
  33. Igbaria, M. (1990). End-user computing effectiveness: A structural equation model. OMEGA, 18(6), 637–652.
  34. Marakas, G.M., Yi, M.Y., & Johnson, R.D. (1998). The multilevel and multifaceted character of computer self-efficacy: Toward clarification of the construct and an integrative framework for research. Information System Research, 9(2), 126 – 163.
  35. Joo, Y.J., Bong, M., & Choi, H.J. (2000). Self-efficacy for self-regulated learning, academic self-efficacy, and Internet self-efficacy in webbased instruction. Educational Technology Research and Development, 48(2), 5–17.
  36. Thompson, L.F., Meriac, J.P., & Cope, J.G. (2002). Motivating online performance: the influences of goal setting and Internet selfefficacy. Social Science Computer Review, 20(2), 149–160.
  37. Wang, A.Y., & Newlin, M.H. (2002). Predictors of web-student performance: the role of self-efficacy and reasons for taking an on-line class. Computers in Human Behavior, 18, 151–163.
  38. Arbaugh, J.B. (2002). Managing the on-line classroom: a study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13, 203–223.
  39. Thurmond, V.A., Wambach, K., & Connors, H.R. (2002). Evaluation of student satisfaction: determining the impact of a web-based environment by controlling for student characteristics. The American Journal of Distance Education, 16(3), 169 – 189.
  40. Amoroso, D.L., & Cheney, P.H. (1991). Testing a causal model of end-user application effectiveness. Journal of Management Information Systems, 8(1), 63–89.
  41. Rivard, S. (1987). Successful implementation of end-user computing. Interfaces, 17(3), 25–33.
  42. Hiltz, S.R. (1993). The virtual classroom: Learning without limits via computer networks. Norwood, NJ: Ablex. Webster, J., & Hackley, P. (1997). Teaching effectiveness in technology-mediated distance learning. Academy of Management Journal, 40(6), 1282–1309.
  43. Isaacs, E.A., Morris, T., Rodriguez, T.K., & Tang, J.C. (1995). A comparison of face-to-face and distributed presentations. In R.R. Katz, R. Mack, L. Marks, M.B. Rosson, & J. Nelson (Eds.), Proceedings of the association for computing machinery (ACM) special interest group on computers and human interaction (CHI) 95 conference (pp. 354 –
  44. Wu, J.P., Tsai, R.J., Chen, C.C., & Wu, Y.C. (2006). An integrative model to predict the continuance use of electronic learning systems: hints for teaching. International Journal on E-Learning, 5(2), 287–302.
  45. Pituch, K.A., & Lee, Y.K. (2006). The influence of system characteristics on e-learning use. Computers& Education, 47, 222–244.
  46. Hong, K.S. (2002). Relationships between students‟ and instructional variables with satisfaction and learning from a Web-based course. Internet and Higher Education, 5, 267–281.
  47. Jiang, M., & Ting, E. (1998). Course design, instruction, and students‟ online behaviors: A study of instructional variables and student perceptions of online learning. In Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA, April 13–17, 1988.
  48. Schwartz, R.A. (1995). The virtual university. American Society for Engineering Education Prism, 5(4), 22–26.
  49. Borbely, E. (1994). Challenges and opportunities in extending the classroom and the campus via digital compressed Video. In R. Mason& P. Bacsich (Eds.), ISDN: Applications in education and training (pp. 65 –82). London: Institution of
  50. Bond, E.U. III and Fink, R.L. (2003), “Customer satisfaction and the marketing-quality interface”, Journal of Business and Industrial Marketing, Vol. 18 No. 3, pp. 204-18.
  51. Nowak, L.I. And Washburn, J.H. (1998), “Antecedents to client satisfaction in business services”, Journal of Services Marketing, Vol. 12 No. 6, pp. 441-52.
  52. Oliver, R.L. (1993), “A conceptual model of service quality and service satisfaction: compatible goals, different concepts”, in Swartz, T.A., Bowen, D.E. And Brown, S.W. (Eds), Advances in Services Marketing and Management: Research and Practice, JAI Press, Greenwich, CT, pp. 1-67.
  53. Zeithaml, V.A., Berry, L.L. And Parasuraman, A. (1996), “The behavioral consequences of service quality”, Journal of Marketing, Vol. 60 No. 2, pp. 31-46.
  54. Shankar, V., Smith, A.K. And Rangaswamy, A. (2003), “Customer satisfaction and loyalty in online and offline environments”, International Journal of Research in Marketing, Vol. 20 No. 2, pp. 153-75.
  55. Su, A.Y.L. (2004), “Customer satisfaction measurement practice in Taiwan hotels”, International Journal of Hospitality Management, Vol. 23 No. 4, pp. 397-408.
  56. Hassenzahl, M., Beau, A., & Burmester, M. (2001). Engineering joy. IEEE Software, 18(1), 70 –76.
  57. Lindgaard, G., & Dudek, C. (2003). What is this evasive beast we call user satisfaction? Interacting with Computers, 15(3), 429–452.
  58. Chin, W.W. (2001). PLS-graph user‟s guide, version 3.0. Soft Modeling Inc.
  59. Alonso, F., Lopez, G., Manrique, D., & Vines, J.M. (2005). An instructional model for web-based e-learning education with a blended learning process approach. British Journal of Educational Technology, 36 (2), 217-235.
  60. Alonso, F., Lopez, G., Manrique, D., & Vines, J.M. (2005). An instructional model for web-based e-learning education with a blended learning process approach. British Journal of Educational Technology, 36 (2), 217-235.
  61. Amoroso, D.L., & Cheney, P.H. (1991). Testing a causal model of end-user application effectiveness. Journal of Management Information Systems, 8(1), 63-89.
  62. Arbaugh, J.B. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of Management Education, 24(1), 32-54.
  63. Arbaugh, J.B. (2002). Managing the on-line classroom: a study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13, 203-223.
  64. Arbaugh, J.B. (2002). Managing the on-line classroom: a study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13, 203-223.
  65. Arbaugh, J.B., & Duray, R. (2002). Technological and structural characteristics, student learning and satisfaction with web-based courses-An exploratory study of two on-line MBA programs. Management Learning, 33(3), 331-347.
  66. Atkinson, M., & Kydd, C. (1997). Individual characteristics associated with WorldWide Web use: an empirical study of playfulness and motivation. DATABASE for Advances in Information Systems, 28(2), 53-62.
  67. Barbeite, F.G., & Weiss, E.M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20, 1-15.
  68. Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation confirmation model. MIS Quarterly, 25(3), 270-351.
  69. Bond, E.U. III and Fink, R.L. (2003), "Customer satisfaction and the marketing-quality interface", Journal of Business and Industrial Marketing, Vol. 18 No. 3, pp. 204-18.
  70. Bonk, C., & Cunningham, D. (1998). Searching for learner-centered, constructivist, and sociocultural components of collaborative educational learning tools. In C. Bonk& K. King (Eds.), Electronic collaborators: Learner-centered technologies for literacy, apprenticeship, and discourse (pp. 25-50). Mahwah, NJ: Lawrence Erlbaum Associates.
  71. Borbely, E. (1994). Challenges and opportunities in extending the classroom and the campus via digital compressed Video. In R. Mason& P. Bacsich (Eds.), ISDN: Applications in education and training (pp. 65-82). London: Institution of Electrical
  72. Chin, W.W. (2001). PLS-graph user's guide, version 3.0. Soft Modeling Inc.
  73. Chyung, Y., Winiecki, D.J. & Fenner, J.A. (1998). A case study: increase enrollment by reducing dropout rates in adult distance education. In Proceedings of the annual conference on distance teaching& Learning, Madison, WI. D.Y. Shee, Y.-S. Wang, (2008) , Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications, Computers& Education 50 , 894-905.
  74. 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.
  75. Doll, W.J. And Torkzadeh, G. (1988), "The measurement of end-user computing satisfaction", MIS Quarterly, Vol. 12 No. 2, pp. 259-74.
  76. Edmonds, R. (2004). Best practices in e-learning. Menlo Park, CA: SRI Business Consulting Intelligence.
  77. Flood, G. (2006). Make it specific. Human Resources, 64-66.
  78. Fredericksen, E., Pickett, A., Shea, P., Pelz, W., & Swan, K. (2000). Student satisfaction and perceived learning with online courses: principles and examples from the SUNY learning network. Journal of Asynchronous Learning Networks, 4(2), 7-41.
  79. Hassenzahl, M., Beau, A., & Burmester, M. (2001). Engineering joy. IEEE Software, 18(1), 70-76.
  80. Hiltz, S.R. (1993). The virtual classroom: Learning without limits via computer networks. Norwood, NJ: Ablex. Webster, J., & Hackley, P. (1997). Teaching effectiveness in technology-mediated distance learning. Academy of Management Journal, 40(6), 1282-1309.
  81. Hong, K.S. (2002). Relationships between students' and instructional variables with satisfaction and learning from a Web-based course. Internet and Higher Education, 5, 267-281.
  82. Hong, K.S. (2002). Relationships between students' and instructional variables with satisfaction and learning from a Web-based course. Internet and Higher Education, 5, 267-281.
  83. Jonassen, D.H. (2003). Learning to solve problems with technology: A constructivist perspective. Upper Saddle River, NJ: Merrill.
  84. Joo, Y.J., Bong, M., & Choi, H.J. (2000). Self-efficacy for self-regulated learning, academic self-efficacy, and Internet self-efficacy in webbased instruction. Educational Technology Research and Development, 48(2), 5-17.
  85. Kydd, C.T., & Ferry, D.L. (1994). Case study: Managerial use of videoconferencing. Information& Management, 27, 369-375.
  86. Lachem, C., Mitchell, J., & Atkinson, R. (1994). ISDN-based videoconferencing in Australian tertiary education. In R. Mason& P. Bacsich (Eds.), ISDN: Applications in education and training (pp. 99-113). London: Institution of Electrical
  87. Levy, Y. (2003). A study of learners_ perceived value and satisfaction for implied effectiveness of online learning systems. Dissertation Abstracts International 65(03), 1014A. (UMI No. AAT 3126765). Retrieved Oct 13, 2004, from Digital Dissertations database. Lin, Cathy S., Wu, S., & Tsai, R.J. (2005). Integrating perceived playfulness into expectation-confirmation model for web portal context. Information& Management, 42, 683-693.
  88. Lindgaard, G., & Dudek, C. (2003). What is this evasive beast we call user satisfaction? Interacting with Computers, 15(3), 429-452.
  89. Marakas, G.M., Yi, M.Y., & Johnson, R.D. (1998). The multilevel and multifaceted character of computer self-efficacy: Toward clarification of the construct and an integrative framework for research. Information System Research, 9(2), 126-163.
  90. Mark Nichols. (2008). E-Primer Series-E-Learning in Context. Page 2 Moez Limayem, Christy M.K. Cheung, Understanding information systems continuance: The case of Internet-based learning technologies, Journal of Information& Management 45 (2008) 227-232.
  91. Nahl, D. (1993). Communication dynamics of a live interactive television system for distance education. Journal of Education for Library and Information Science, 34(3), 200-217.
  92. Oliver, R.L. (1980). A cognitive model for the antecedents and consequences of satisfaction. Journal of Marketing Research, 17, 460-469.
  93. Oliver, R.L. (1993), "A conceptual model of service quality and service satisfaction: compatible goals, different concepts", in Swartz, T.A., Bowen, D.E. And Brown, S.W. (Eds), Advances in Services Marketing and Management: Research and Practice, JAI Press, Greenwich, CT, pp. 1-67.
  94. Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: a research framework and a preliminary assessment of effectiveness in basic IT skill training. MIS Quarterly, 25(4), 401-426.
  95. Pituch, K.A., & Lee, Y.K. (2006). The influence of system characteristics on e-learning use. Computers& Education, 47, 222-244.
  96. Rivard, S. (1987). Successful implementation of end-user computing. Interfaces, 17(3), 25-33.
  97. Sachs, D., & Hale, N. (2003). Pace university_s focus on student satisfaction with student services in online education. Journal of Asynchronous Learning Networks, 7(2), 36-42.
  98. Salomon, G. (1983). The differential investment of mental effort in learning from different sources. Educational Psychologist, 18, 42-50.
  99. Schwartz, R.A. (1995). The virtual university. American Society for Engineering Education Prism, 5(4), 22-26.
  100. Shankar, V., Smith, A.K. And Rangaswamy, A. (2003), "Customer satisfaction and loyalty in online and offline environments", International Journal of Research in Marketing, Vol. 20 No. 2, pp. 153-75.
  101. Spiro, R.J., Feltovich, P.J., Jacobson, M.J., & Coulson, R.L. (1991). Knowledge representation, content specification, and the development of skill in situation-specific knowledge assembly: Some constructivist issues as they relate to cognitive flexibility theory and hypertext. Educational Technology, 31 (9), 22-25.
  102. Stokes, S.P. (2001). Satisfaction of college students with the digital learning environment. Do Learners' temperaments make a difference? Internet and High Education, 4, 31-44.
  103. Thompson, L.F., Meriac, J.P., & Cope, J.G. (2002). Motivating online performance: the influences of goal setting and Internet selfefficacy. Social Science Computer Review, 20(2), 149-160.
  104. Thurmond, V.A., Wambach, K., & Connors, H.R. (2002). Evaluation of student satisfaction: determining the impact of a web-based environment by controlling for student characteristics. The American Journal of Distance Education, 16(3), 169-189.
  105. Thurmond, V.A., Wambach, K., & Connors, H.R. (2002). Evaluation of student satisfaction: determining the impact of a web-based environment by controlling for student characteristics. The American Journal of Distance Education, 16(3), 169-189.
  106. Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  107. Wang, A.Y., & Newlin, M.H. (2002). Predictors of web-student performance: the role of self-efficacy and reasons for taking an on-line class. Computers in Human Behavior, 18, 151-163.
  108. Wang, Y.S. (2003), "Assessment of learner satisfaction with asynchronous electronic learning systems", Information and Management, Vol. 41 No. 1, pp. 75-86.
  109. Weigel, V.B. (2002). Deep learning for a digital age: Technology ' s untapped potential to enrich higher education. San Francisco, CA: Jossey-Bass.
  110. Wu, J.P., Tsai, R.J., Chen, C.C., & Wu, Y.C. (2006). An integrative model to predict the continuance use of electronic learning systems: hints for teaching. International Journal on E-Learning, 5(2), 287-302.
  111. Wu, J.P., Tsai, R.J., Chen, C.C., & Wu, Y.C. (2006). An integrative model to predict the continuance use of electronic learning systems: hints for teaching. International Journal on E-Learning, 5(2), 287-302.
  112. Wu, J.P., Tsai, R.J., Chen, C.C., & Wu, Y.C. (2006). An integrative model to predict the continuance use of electronic learning systems: hints for teaching. International Journal on E-Learning, 5(2), 287-302.
  113. Zeithaml, V.A., Berry, L.L. And Parasuraman, A. (1996), "The behavioral consequences of service quality", Journal of Marketing, Vol. 60 No. 2, pp. 31-46.

These references have been extracted automatically and may have some errors. If you see a mistake in the references above, please contact info@learntechlib.org.

View References & Citations Map

Cited By

  1. A Template to Use Existing Digitised Data for a CALL Program Shell for Indigenous Languages: A Community Centred Approach

    Virginia Westwood, Monash University, Australia

    EdMedia + Innovate Learning 2011 (Jun 27, 2011) pp. 1703–1712

These links are based on references which have been extracted automatically and may have some errors. If you see a mistake, please contact info@learntechlib.org.