In higher education institutions, virtual learning systems (VLSs) have been adopted, and are becoming increasingly popular among educators. However, despite this ubiquity of VLS use, there has not been widespread change in pedagogic practice to take advantage of the functionality afforded by VLSs. Knowledge of the actual usage of e-learning systems is limited in terms of what specific feature sets are deemed useful, and how this influences system usage. VLSs have a suite of tools with associated functions/features and properties, as well as non-functional system characteristics. In addition, these systems incorporate pedagogic features to cater for online teaching. Educators in higher education, who are the chief agents of e-learning, are confounded by system-related, pedagogic, organisational, user difference and demographic factors that influence VLS usage. Virtual learning system usage involves system feature usage extent and frequency, total system usage and usage clusters. The aim of this study is to develop a model representing the factors that influence usage of VLSs in higher education. The links between system usage and system-related factors, pedagogic factors, organisational factors, user-difference and demographic factors is researched. This research incorporated a literature study, a pilot study, interviews and surveys. A case study research strategy was combined with a mixed methods research design. The results of the qualitative analysis was triangulated with the findings of the quantitative analysis and compared to the findings of the literature study. The study was conducted at two residential higher education institutions (HEI), namely, University of KwaZulu-Natal and Durban University of Technology. The main contribution of this study is the Virtual Learning System Usage Model (VLSUM) representing the factors that influence VLS usage in residential higher education institutions. The proposed VLSUM is based on the empirical results of this study. VLSUM can be used by managers of educational technology departments and instructional designers to implement interventions to optimize usage. The constructs of VLSUM confirmed existing theories, replicated and synthesised theories from different fields, and extended existing models to produce a new model for understanding the factors that influence VLS usage in higher education. / Computing / D. LITT. et. Phil. (Information Systems)