Students’ Willingness to Accept Virtual Lecturing Systems: An Empirical Study by Extending the UTAUT Model

Authors: Ahmed Shuhaiber

Abstract:

The explosion of the World Wide Web and the electronic trend of university teaching have transformed the learning style to become more learner-centered, which has popularized the digital delivery of mediated lectures as an alternative or an adjunct to traditional lectures. Despite its potential and popularity, virtual lectures have not been adopted yet in Jordanian universities. This research aimed to fill this gap by studying the factors that influence students’ willingness to accept virtual lectures in one Jordanian University. A quantitative approach was followed, by obtaining 216 survey responses and statistically applying the UTAUT model with some modifications. Results revealed that performance expectancy, effort expectancy, social influences, and self-efficacy could significantly influence students’ attitudes towards virtual lectures. Additionally, Facilitating conditions and attitudes towards virtual lectures were found with significant influence on students’ intention to take virtual lectures. Research implications and future work were specified afterwards.

Keywords: E-Learning, Student willingness, UTAUT, Virtual Lectures, Web-based learning systems.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1100292

References:

[1] M. D. Roblyer. Integrating educational technology into teaching, 4th ed. Upper Saddle River, New Jersey: Pearson Education, Inc., 2006.
[2] R. Gilstrap, & W. Martin. Current strategies for teachers. Pacific Palisades, California: Goodyear Publishing Company, Inc., 1975.
[3] J.E. Stephenson, C. Brown, & D.K. Griffin, 2008. Electronic delivery of lectures in the university environment: An empirical comparison of three delivery styles. Computers & Education, vol. 50, no. 3, pp.640-651.
[4] A. Inglis, P. Ling, & V. Joosten. Delivering digitally: Managing the transition to the knowledge media, 2nded, London: Kogan Page, 2002.
[5] C. Evans, N.J. Gibbons, K. Shah, & D.K. Griffin, 2004. Virtual learning in the biological sciences: Pitfalls of simply ‘‘putting notes on the web’’. Computers & Education, vol. 43, no. 1, pp.49–61.
[6] V. Venkatesh, M.G. Morris, F.D. Davis, & G.B. Davis, 2003. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, vol. 27, pp.425-478.
[7] D. Jong, & T.S. Wang. “Student acceptance of web-based learning system”. In Proceedings of the 2009 International Symposium on Web Information Systems and Applications (WISA’09), Nanchang, P. R. China, pp. 533-536, 2009.
[8] D.W. Straub, 1989. Validating instruments in MIS research. MIS Quarterly, vol. 13, no. 2, pp.147-169.
[9] J. Hair, R. Tatham, R. Anderson, & W. Black. Multivariate Data Analysis (5th Edition): Prentice Hall,1998.
[10] W. L. Neuman. Social research methods: Quantitative and qualitative approaches, 6 ed., Boston, MA Allyn & Bacon, 2005.
[11] A. P. Field. Discovering statistics using SPSS: (and sex, drugs and rock 'n' roll), London: SAGE Publications, 2005.
[12] C. Fornell, & D. Larcker, 1981. Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, vol. 18, no. 1, pp.39-50.