The adoption of E-learning systems in Zimbabwe’s universities: An integration of theory of planned behaviour and technology acceptance model

Abstract

The education system in Zimbabwe’s universities is rapidly metamorphosing, driven by technological progress, heightened competitiveness among universities, hence the need to find new sources of distinctive competences using e-learning systems. Noncontrollable events such as effects of climatic changes and transboundary pandemic diseases on traditional education have been disrupting the traditional learning systems. As a result, universities are trying to augment traditional teaching and learning processes and practices by embracing e-learning systems. The purpose of this research was to examine factors that influence the probability of adopting of e-learning systems in Zimbabwe’s universities. E-learning systems have steadily risen to become critical tools for effective and inexpensive way of efficient education delivery, knowledge discovery and sharing among lecturers and students. E-learning systems have the potential to improve learning outcomes of users whilst also enriching and perpetuating needed cognitive and effective skills of users. Quantitative data was collected using a structured questionnaire from a randomly selected sample of 50 university students in Harare students. The data was analysed using multinomial logistic regression equation with three dependent variables; Adopt; Not Adopt and Defer Adoption of e-learning systems. The probability of adopting e-learning systems in Zimbabwe’s universities is affected by social influence, perceived control, perceived usefulness, and ease of use, facilitating conditions, performance expectance, attitude and costs. The findings also show perceived usefulness, perceived enjoyment affect the likelihood of deferring the adoption of learning system relative to not adopting. The study recommends crafting of policies that reduce complexity and cost of using e-learning systems whilst at the same time adopting add-ons that enhances relative advantages, compatibility with traditional systems, and performance expectance of users. The study contributes to literature by extending the Technology Acceptance Model and Theory of Planned Behaviour using a polychotomous regression technique to examine factors that enables the probability of using e-learning system.