Govender, Desmond Wesley.Aboderin, Olukayode Solomon.2020-04-022020-04-0220172017https://researchspace.ukzn.ac.za/handle/10413/17467Doctoral Degree. University of KwaZulu-Natal, Edgewood.The emergence of technologies of learning, and recently the use of Open Educational Resources and the increased awareness of the “DotNet (or Y) Generation” have made demands on traditional education and learning systems to be more open, flexible and customised towards what students expect. E-learning has increasingly been used in most parts of the world as a viable alternative to conventional education. It is believed that that the potential of information and communication technology (ICT), and more so e-learning, would bring positive impacts to teaching and learning by providing students and teachers with flexibility, accessibility, more opportunities for participation and collaboration and better outcomes. Any change in teaching and learning strategies is always evaluated by its impact on academic performance. Previous studies have focused mostly on academic performance of traditional on-campus students, but not many on distance e-learners within the Nigerian educational system. The researcher observed from the literature that there was limited research on the effects of e-learning on academic performance of distance e-learners. Most studies on e-learning in Nigeria focused on the problems, challenges, attitudes, prospects and awareness of e-learning. The rationale for this study resulted from this limited research in Nigeria on the effects of e-learning on academic performance of distance e-learners. This study focused on this research gap as identified in the literature. The purpose of the study was to critically examine the effects of e-learning on academic performance of distance e-learners in a Nigerian university. To achieve this overall aim, the study set out to determine the best predictors of academic performance of distance e-learners and thereby propose a model to enhance academic performance. This study adopted a mixed-method approach in its data collection process; however, the study was dominated by a quantitative approach, while the qualitative approach was used to consolidate the findings of the quantitative study. A questionnaire was used to collect quantitative data while focus group interviews were used to collect qualitative data. The study was conducted in four selected study centres of the university and a total of 1,025 participants completed the survey-based questionnaire. The researcher used Spearman’s correlation coefficient, ANOVA, T-Test and post-hoc Test in order to determine the effects of each of the factors on academic performance. Ordinal regression was used to determine the best predictors of academic performance of distance e-learners. The quantitative data was analysed using Statistical Package for Social Sciences (SPSS) while qualitative data was transcribed before analysis. The conceptual framework used in the study was made up of the variables identified in literature and the 3P model of Teaching and Learning. The 3P model of Teaching and Learning was then used to further explain the result of the study. The findings of this study indicated that there are eight factors which influence academic performance of distance e-learners. These are students’ ICT literacy level, frequency of engagement with ICT, marital status, previous academic performance, hours spent on the Internet per day, hours spent on social media per day, hours spent on a computer for studies per day and family size. In addition, the findings indicated that age, employment, gender, previous qualification, learner-content interaction, learner-instructor interaction, learner-learner interaction, learning style, work experience, family income, home background and parent education do not influence academic performance of distance e-learners. However, when the data was split based on gender, the result revealed that learner-content interaction and learner-instructor interaction only influence academic performance of female distance e-learners. Finally, the model developed for this study revealed that frequency of engagement with ICT, students’ ICT literacy level, marital status, previous academic performance and previous qualification are the best predictors of distance e-learners’ academic performance. This serves as the contribution of the study to the body of knowledge. Based on the findings of the research, recommendations have been made which will assist Nigerian university policy makers and course developers with a view to improving the academic performance of distance e-learners.enE-learning.Distance e-learners.Academic performance.Nigeria.University.Thesis