Predictors of academic performance of distance e-learners in a Nigerian University

Abstract

This study was designed to analyze the predictors of the academic performance of distance e-learners. The population consisted of all distance learners in the university study centers in the South-West geopolitical zone. The sample of the study was made up of 1025 respondents from the university, which were selected using a purposive sampling technique. A mixed-method approach was used for the collection of data. This study applied ordinal regression analysis in searching for the best predictors among the variables under investigation in predicting the academic performance of distance e-learners. A quantitative approach was used to determine the best predictors. In contrast, a qualitative approach was used to support the quantitative results and reveal other variables not covered in the questionnaire. Results showed that five variables best predicted academic performance, and together they explained 10% of the variance in academic performance after considering all the rules that guide ordinal regression analysis. Frequency of engagement with information and communication technology (ICT) was found to be the strongest predictor, followed by students’ ICT literacy levels, marital status, previous academic performance and entry qualification. Based on the study's findings, it was recommended that policymakers and educational stakeholders fully support the implementation of e-learning in Nigerian universities.