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Title: Factors affecting students’ acceptance of e-Learning environments in developing countries: A Structural Equation Modeling approach
Authors: Tarhini, Ali
Hone, Kate
Liu, Xiaohui
Keywords: Structural Equation Modeling;Technology Adoption;Information System;Social Science;TAM;Developing countries
Issue Date: 1-Feb-2013
Publisher: International Journal of Information and Education Technology
Citation: Tarhini, A., Hone, K., & Liu, X. (2013). Factors affecting students’ acceptance of e-learning environments in developing countries: A structural equation modeling approach. International Journal of Information and Education Technology, 3 (1), 54-59.
Abstract: A number of studies have shown that e-learning implementation is not simply a technological solution, but a process of many different factors such as social and behavioural contexts. Yet little is known about the important rule of such factors in technology adoption and use in the context of developing countries such as Lebanon. Therefore, the main objective of our study is to empirically validate an extended Technology Acceptance Model (TAM) (to include Social Norms and Quality of Work Life constructs) in the Lebanese context. A quantitative methodology approach was adopted in this study. To test the hypothesized research model, data were collected from 569 undergraduate and postgraduate students studying in Lebanon via questionnaire. The collected data were analysed using structural equation modeling (SEM) technique based on AMOS methods and in conjunction with multi-group analysis. As hypothesized, the results of the study revealed perceived usefulness (PU), perceived ease of use (PEU), social norms (SN) and Quality of Work life (QWL) to be significant determinants of students’ behavioral intention (BI). This provides support for the applicability of the extended TAM in the Lebanese context. Implications to both theory and practice of this study are discussed at the end of the paper.
DOI: 10.7763/IJIET.2013.V3.233
ISSN: 10.7763/IJIET.2013.V3.233
Appears in Collections:Computer Science

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