Evaluating E-learning systems success: An empirical study. (January 2020)

• Record Type: Journal Article
• Authors: Al-Fraihat, Dimah; Joy, Mike; Masa'deh, Ra'ed; Sinclair, Jane
• Is Part Of: Computers in human behavior. Volume 102(2020)
• Page Start: 67
• Page End: 86
• Publication Date: 2020-01
• Subjects: E-Learning -- E-learning success -- E-learning evaluation -- DeLone and McLean information systems success model -- TAM -- E-learning satisfaction; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2019.08.004
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: E-learning, as a direct result of the integration of technology and education, has emerged as a powerful medium of learning particularly using Internet technologies. The undeniable significance of e-learning in education has led to a massive growth in the number of e-learning courses and systems offering different types of services. Thus, evaluation of e-learning -systems is vital to ensure successful delivery, effective use, and positive impacts on learners. Based on an intensive review of the literature, a comprehensive model has been developed which provides a holistic picture and identifies different levels of success related to a broad range of success determinants. The model has been empirically validated by fitting the model to data collected from 563 students engaged with an e-learning system in one of the UK universities through a quantitative method of Partial Least Squares - Structural Equation Modelling (PLS-SEM). The determinants of e-learning perceived satisfaction are technical system quality, information quality, service quality, support system quality, learner quality, instructor quality, and perceived usefulness, which together explain 71.4% of the variance of perceived satisfaction. The drivers of perceived usefulness are technical system quality, information quality, support system quality, learner quality, and instructor quality, and these explain 54.2% of the variance of perceived usefulness. Four constructs were found to be the determinants of e-learning use, namely educational system quality, support system quality, learner quality, and perceived usefulness, and together they account for 34.1%. Finally, 64.7% of the variance of e-learning benefits was explained by perceived usefulness, perceived satisfaction, and use. Highlights: Study on evaluating e-learning systems success in one of the UK universities. Four approaches for evaluating e-learning systems success. A comprehensive model based on DeLone & McLean IS model, TAM, e-learning satisfaction models and e-learning quality models. Seven quality factors are success determinants: system, information, service, educational, support, learner, and instructor. Determinants of e-learning benefits are: perceived usefulness, perceived satisfaction, and use.