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.

Introduction

The development of Information Technology (IT) has motivated improvements in various fields such as finance, business, health, and education. As a result, education has grown rapidly and stimulated the adoption of e-learning, which is a direct result of the integration of education and technology and is deemed to be a powerful medium for learning (Al-Fraihat, Joy, & Sinclair, 2017). E-learning has become mainstream in the education sector and has been massively adopted in higher education. According to Dahlstrom, Brooks, and Bichsel (2014), p. 99% of institutions have Learning Management Systems (LMSs) in place, and 85% of them have been utilized, and in the UK, 95% of higher education institutes have adopted LMSs to support their educational services (McGill & Klobas, 2009). Accordingly, the quality of e-learning systems has received a considerable amount of research attention and a large number of researchers have attempted to identify e-learning success factors to maximize the effectiveness of these systems (e.g., Ali & Ahmad, 2011; Fathema, Shannon, & Ross, 2015; Islam, 2013; B. C. Lee, Yoon, & Lee, 2009; J. K. Lee & Lee, 2008; M. C. Lee, 2010; Mohammadi, 2015; Mtebe & Raphael, 2018; Park, 2009; Wahab, 2008; Wang, 2003)). Broadly, the majority of these studies have examined individual parts of key determinants of e-learning systems success ignoring the synergistic effects of the success variables interacting together (Eom & Ashill, 2018). Another direction of research has dealt with the direct relationships between e-learning quality factors and usage or satisfaction (e.g., Selim, 2003; Ozkan & Koseler, 2009).