Student adoption of e-learning at makerere university during COVID-19: A structural equation modelling based on the unified theory of acceptance and use of technology

Abstract

The onset of COVID-19 dealt a severe blow to the education sector in Uganda, leading to the mandatory closure of all learning institutions to mitigate the spread of the virus. Makerere University, a venerable institution in the region, was not exempt from this directive. The initial uptake of e-learning was sluggish due to various factors, including inadequate infrastructure, digital illiteracy among both students and some faculty members, and, most notably, a lack of preparedness in utilizing digital eLearning technologies. The objective of this study was to examine the factors that impacted students’ embrace of eLearning at Makerere University during the COVID-19 pandemic. Employing a quantitative approach, the study utilized questionnaires structured based on the nine constructs of the Unified Theory of Acceptance and Use of Technology model. Between August and December 2021, a questionnaire was distributed to 374 students from two colleges. Structured equation modelling was employed to assess 16 factors that were hypothesized to have an impact on adoption. Effort expectancy emerged as the most robust predictor. Likewise, the behaviour of utilizing eLearning technologies was predominantly impacted by facilitating conditions. Utilizing the UTAUT methodology, this study’s theoretical significance arises from our effort to broaden the existing literature on the utilization of video conferencing software (Zoom) in conjunction with a learning management system (MUELE) during the challenging period of COVID-19, an area that has not been extensively explored. The results offer insights into the embrace and approval of both systems within the framework of a developing nation. This study delivers valuable perspectives for developers of eLearning systems, emphasizing the importance of creating user-friendly platforms that enhance the learner experience. This includes the incorporation of intuitive designs and intelligent features such as chatbots and AI-driven tutoring systems, which adapt to the unique needs of students.