Development and Validation of a Model to Investigate the Impact of Individual Factors on Instructors’ Intention to Use E-learning Systems

Abstract

E-learning is becoming an increasingly important part of higher education institutions. However, instructors’ use of e-learning systems in community colleges in the United States is relatively sparse. Thus, the purpose of this study was to investigate some individual factors that may affect instructors’ intention to use e-learning systems in community colleges. In this study, we proposed a theoretical model predicting instructors’ intention to use e-learning systems in community colleges based on their resistance to change, perceived value of e-learning systems, computer selfefficacy, and attitude toward e-learning systems. The sample for this study included 119 (over 41% response rate) full-time, part-time, and adjunct instructors in different academic departments at a community college. Our findings indicate that the theoretical model developed was able to predict instructors’ intention to use e-learning systems. All four predictive variables have significant effects on intention to use e-learning systems. Two statistical methods were used to formulate and test predictive models: Multiple Linear Regression (MLR) and Ordinal Logistic Regression (OLR). Results of both models were consistent on resistance to change as having the greatest weight on predicting instructors’ intention to use e-learning systems, while computer self-efficacy in both analyses was found to have the least weight. We conclude the paper with a discussion, which includes a summary of the results, limitations of this research study, as well as implications for practice and future research.