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

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.

• Ahmed Shuhaiber

• E-Learning
• Student willingness
• UTAUT
• Virtual Lectures
• Web-based learning systems.

[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.