Investigating university academics behavioural intention in the adoption of e-learning in a time of COVID-19
subject: e-learning, fourth industrial revolution, structural equation modelling, information communication technology, behavioural intention to use, teo’s model
description: Background: The coronavirus disease of 2019 (COVID-19) has extensively impacted various sectors globally, including higher education. The indefinite closure of Universities has necessitated the need to introduce alternative teaching and learning methods and tools. E-learning a disruptive innovation has provided an opportunity to allow for continuity of teaching and learning in Universities during these closures. Objectives: The study adopts Teo's model as the analytical tool to investigate factors that influence University lecturers to adopt e-learning platforms in South Africa. Method: The study followed a quantitative research approach with stratified sampling as a data collection approach using a sample size of 132 respondents. Structural Equation Modelling (SEM) was adopted to deduce factors that influence the behavioural Intention (BIU) to adopt e-learning as well as to test the Model fit of Teo's model in the South African context. Results: The study revealed that the lecturer's attitude towards the use (ATU) of e-learning is the most influential construct towards lecturers behavioural Intention to use (BIU) e-learning platforms. The empirical evidence also revealed that Teo's model is a reasonable fit to the data to understand the adoption of e-learning by lecturers in South African universities. Conclusion: The empirical evidence from this study supports the viewpoint that in order for lecturers to successfully adopt e-learning platforms, their attitude towards the use of these platforms is a critical factor. In order to understand lecturer’s adoption of e-learning platforms successfully, Teo's model is a reasonably good framework to use.
creator: Joseph N. Jere
source: South African Journal of Information Management
publisher: AOSIS
date: 2020
coverage: Management information systems, Information theory