The Role of Information Technology in motivating students to accept e-learning adoption in universities: A case study in Jordanian universities
The present study aimed to develop a theoretical framework toward e-learning adoption in universities through conducting a comprehensive review of literature, and empirical studies. Based on the technology acceptance model, the researchers developed a model designed to measure the impact of ease of use, perceived usefulness, and training on e-learning usage on the actual use of e-learning systems via the initial trend towards the use of e-learning systems and the intention towards the use of e-learning systems as mediating factors. The researchers also developed a survey questionnaire that will be distributed to a selected sample study on the students at the Jordanian public and private universities in order to answer the research questions and test its hypotheses by applying structural equation modeling.
Allehaibi, M. (2001). Faculty adoption of Internet technology in Saudi Arabian universities. PhD, Florida State University. Available: http://www.sssgrp.com/Menu/Di ssAbstracts /InnovationDiffusion/Allehaibi.htm. Retrieved on 12/4/2015.
Allen, I., and Seaman, J. (2004). Entering the mainstream: The quality and extent of online education in the United States, 2003 and 2004. Retrieved April 15, 2005 from: http://sloan-c.org/resources/entering_mainstream.pdf.
Clark, Jr. T.D., Jones, M.C., and Zmud, R.W. (2006). Post adoptive ERP system analysis: A system dynamic modeling approach, Working Paper,
Compeau, D.R., Higgins, C.A., and Huff, S.L. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Davis, F., Bagozzi, R., and Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
Diana, O. (1992). Teaching and learning with computers. (URL: http://orders.edrs.com).
Doll, W.J., Deng, X., and Scazzero, J.A. (2003). A process for post-implementation IT benchmarking, Information & Management, 41, 199-212.
George, P. (2000). Breaking ranks. Principal Leadership, 1(4), 56-61.
Imel, S. (1998). Myths and realities. (Report No. BBB16032). Columbus, OH. ERICClearinghouse on Adult, Career, and Vocational Education.
Kulik, J. A., and Kulik, C. L. (1991). Effectiveness of computer-based instruction. Computers in Human Behavior, 7(1), 75-94.
Masa’deh, R., Shannak, R., and Maqableh, M. (2013). A structural equation modeling approach for determining antecedents and outcomes of students’ attitude toward mobile commerce adoption. Life Science Journal, 10(4), 2321-2333.
Porter,C and Donthu,N. (2006) . Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59, 999–1007.
Russell, A. I. (1995). Stages in learning new technology: Naïve adult e-mail users. Computers in Education, 25(4), 173-178.
Stoehl, L., and Lee, K. (2003). Modeling the effect of experience on student acceptance of Web-based courseware. Internet Research: Electronic Networking Applications and Policy, 13(5), 364-374.
Tarhini, A., Hone, K., and Liu, X. (2013). Factors affecting students’ acceptance of e-learning environments in developing countries: A structural equation modelling approach. International Journal of Information and Education Technology, 3(1), 54-59.
Tarhini, A., Hone, K., and Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology acceptance model. Journal of Educational Computing Research, 51(2), 163-184.
Theriot, P. (2004). Student values and ethics in an e-learning environment. In D. Christopher & S. Jaderstrom (Eds.), NBEA 2004 Yearbook, 42, 13-25.
Wiersma, W. (2000). Research methods in education: An introduction (7nd ed.). Boston:Allyn and Bacon.
Willis, T (2008). An evaluation of the Technology Acceptance Model as a means of understanding online social networking behaviour, Master thesis, University of South Florida.
Zamfiroiu, A., and Sbora, C. (2014). Statistical analysis of the behavior for mobile E-learning. Procedia Economics and Finance, 10, 237-243.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.