What is it about?
The success of an e-learning intervention depends to a considerable extent on student acceptance and use of the technology. Therefore, it has become imperative for practitioners and policymakers to understand the factors affecting the user acceptance of e-learning systems in order to enhance the students’ learning experience. Based on an extended Technology Acceptance Model (TAM), the main aims of this study are to investigate the factors affecting students’ behavioral intention to adopt e-learning technology and to explore the moderating effect of age and gender on the relationships among the determinants affecting e-learning acceptance. This study is based on a total sample of 604 students who used a Web-based learning system at Brunel University in England. Confirmatory Factor Analysis (CFA) was used to perform reliability and validity checks, and structural equation modeling (SEM) was used to test the research model. The results indicate that perceived ease of use, perceived usefulness, social norm, and self-efficacy were critical factors for students’ behavioral intention to use e-learning, with the effect of perceived usefulness found to have the highest magnitude among the main determinants. We also found that age moderates the effect of PEOU, PU, and SE on BI, and that gender moderates the effect of PEOU and SN on BI. However, surprisingly, no significant moderating effect of age on the relationship between SN and BI was found; results also revealed no moderating of gender on PU or SE and BI. Overall, the proposed model achieves acceptable fit and explains 62% of its variance, which is higher than that explained by the original TAM. Based on these findings, implications to both theory and practice are discussed.
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This paper has many implications for theory and practice
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This page is a summary of: 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, September 2014, SAGE Publications, DOI: 10.2190/ec.51.2.b.
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