| dc.description.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. | en_US |
