Abstract
Online learning management systems potentially offer enriched learning environments with higher learner autonomy and more interactions among learners than traditional classrooms. Using learning motivation and individual student characteristics as variables, we developed a user satisfaction model for an online learning network. This model was empirically tested on undergraduate students who were enrolled in online accounting courses that used the Interactive Learning Network (ILN) platform. The results showed that there were significant relationships between learning platform features, accounting (subject) features, and satisfaction, but the relationship between learner motivation and learner satisfaction was not significant. The proposed online learning satisfaction model explained 58 percent of the observed variance. The implications of this model are discussed.
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References
Wang, S.-K., Reeves, T.: The Effects of a Web-Based Learning Environment on Student Motivation in a High School Earth Science Course. Educational Technology Research & Development 54, 597–621 (2006)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13, 319–339 (1989)
Fishbein, M., Ajzen, I.: Belief, Attitude, Intention & Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading (1975)
Bandura, A.: Self-efficacy: Toward a Unifying Theory of Behavioral Change. Psychological Review 84, 191–215 (1977)
Li, S.M., Ma, W.W.K.: Motivational Factors for Accounting Learning – The Development of a Holistic Framework. In: Cheung, S.K.S., Fong, J., Kwok, L.-F., Li, K., Kwan, R. (eds.) ICHL 2012. LNCS, vol. 7411, pp. 243–252. Springer, Heidelberg (2012)
Mayer, R.E.: Models for Understanding. Review of Educational Research 59, 43–64 (1989)
Kozma, R.B.: Learning with Media. Review of Educational Research 61, 179–221 (1991)
Morgan, K.: Predicting and understanding students’ attitudes and behaviour in e-learning. In: Morgan, K., Brebbia, C.A., Sanchez, J., Voiskounsky, A. (eds.) Human Perspectives in the Internet Society: Culture, Psychology and Gender. WIT Press, Southampton (2004)
Schunk, D.H.: Self-efficacy and education and instruction. In: Maddux, J.E. (ed.) Self-efficacy, Adaptation, and Adjustment: Theory, Research, and Application, pp. 281–303. Plenum Press, New York (1995)
Venkatesh, V.: Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research 11, 342–365 (2000)
Turner, J.C., Patrick, H.: How does motivation develop and why does it change? Reframing motivation research. Educational Psychologist 43, 119–131 (2008)
Keller, J.M.: First principles of motivation to learn and e3-learning. Distance Education 29, 175–185 (2008)
ChanLin, L.-J.: Applying motivational analysis in a Web-based course. Innovations in Education & Teaching International 46, 91–103 (2009)
Miltiadou, M., Savenye, W.C.: Applying social cognitive constructs of motivation to enhance student success in online distance education. Educational Technology Review 11 (2003)
Ryan, R.M., Deci, E.L.: Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist 55, 68–78 (2000)
Marton, F., Saljo, R.: Approaches to Learning. In: Marton, F., Hounsell, D., Entwistle, N. (eds.) The Experience of Learning: Implications for Teaching and Studying in Higher Education, pp. 39–58. University of Edinburgh, Centre for Teaching, Learning and Assessment, Edinburgh (2005)
Gonzalez, C.: Conceptions of, and approaches to, teaching online: a study of lecturers teaching postgraduate distance courses. Higher Education 57, 299–314 (2009)
Hall, M., Ramsay, A., Raven, J.: Changing the learning environment to promote deep learning approaches in first-year accounting students. Accounting Education: An International Journal 13, 489–506 (2004)
Schunk, D.H., Pintrich, P.R., Meece, J.L.: Motivation in education: theory, research, and applications. Pearson Merrill Prentice Hall, Upper Saddle River (2008)
Moore, M.G.: Editorial: three types of interaction. The American Journal of Distance Education 3, 1–6 (1989)
Zhang, J., Scardamalia, M., Lamon, M., Messina, R., Reeve, R.: Socio-cognitive dynamics of knowledge building in the work of 9- and 10-years-olds. Educational Technology Research and Development 55, 117–145 (2007)
Hackman, J.R., Oldham, G.R.: Work redesign. Addison-Wesley, Reading (1980)
Adler, R.W., Milne, M.J., Stablein, R.: Situated Motivation: An Empirical Test in an Accounting Course. Canadian Journal of Administrative Sciences 18, 101–115 (2001)
Ma, W.W.K., Yuen, A.H.K.: E-learning system acceptance and usage pattern. In: Teo, T. (ed.) Technology acceptance in education: Research and issues, pp. 201–216. Sense Publishers (2011)
Ma, W.W.K., Yuen, A.H.K.: Understanding Online Knowledge Sharing: An Interpersonal Relationship Perspective. Computers & Education 56, 210–219 (2011)
Biggs, J.B., Kember, D., Leung, D.Y.P.: The revised two-factor study process questionnaire: R-SPQ-2F. British Journal of Educational Psychology 71, 133–149 (2001)
Wang, Y.S.: Assessment of Learner Satisfaction with Asynchronous Electronic Learning Systems. Information & Management 41, 75–86 (2003)
Hair, J.F., Black, B., Babin, B., Anderson, R.E.: Multivariate data analysis: A global perspective. Pearson, Upper Saddle River (2010)
Nunnally, J.C., Bernstein, I.H.: Psychometric Theory. McGraw-Hill, New York (1994)
Lucas, U., Mladenovic, R.: Developing new ‘world views’: Threshold concepts in introductory accounting. In: Meyer, J.H.F., Land, R. (eds.) Overcoming Barriers to Student Understanding: Threshold Concepts and Troublesome Knowledge, pp. 148–159. Routledge, Oxford (2006)
Lucas, U., Mladenovic, R.: The potential of threshold concepts: an emerging framework for educational research and practice. London Review of Education 5, 237–248 (2007)
McGuigan, N., Kern, T.: The Reflective Accountant: Changing Student Perceptions of Traditional Accounting through Reflective Educational Practice. The International Journal of Learning 16, 49–68 (2009)
Duff, A., McKinstry, S.: Students’ Approaches to Learning. Issues in Accounting Education 22, 183–214 (2007)
Trigwell, K., Prosser, M.: Improving the quality of student learning: the influence of learning context and student approaches to learning on learning outcomes. Higher Education 22, 251–266 (1991)
Lord, B., Robertson, J.: Students’ experiences of learning in a third-year management accounting class: Evidence from New Zealand. Accounting Education 15, 41–59 (2006)
Kember, D.: Misconceptions about the Learning Approaches, Motivation and Study Practices of Asian Students. In: Tight, M. (ed.) The Routledge Reader in Higher Education, pp. 39–55. Routledge Falmer, London (2004)
Liaw, S.S., Huang, H.M., Chen, G.D.: Surveying instructor and learner attitudes toward e-learning. Computers & Education 49, 1066–1080 (2007)
Wang, Y.S., Wang, H.Y., Shee, D.Y.: Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior 23, 1792–1808 (2007)
Moore, M.G.: Editorial, What Does Research Say About the Learners Using Computer-Mediated Communication in Distance Learning? American Journal of Distance Education 16, 61–64 (2002)
Swan, K.: Virtual interactivity: design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education 22, 306–331 (2001)
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Ma, W.W.K., Li, S.M. (2013). An Exploration of Student Satisfaction in Online Accounting Courses. In: Cheung, S.K.S., Fong, J., Fong, W., Wang, F.L., Kwok, L.F. (eds) Hybrid Learning and Continuing Education. ICHL 2013. Lecture Notes in Computer Science, vol 8038. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39750-9_15
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DOI: https://doi.org/10.1007/978-3-642-39750-9_15
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