Artificial Intelligence Applications Adoption and Use in Universities: A SEM Approach
Abstract
ELearning platforms adoption and use by university students has become prevalent worldwide, developing nations still lag behind. This study aims to establish critical paths amongst determinants of “behavioural Intention” and “use behaviour” in eLearning platforms adoption and use by university students. The PLS-SEM method was use to evaluate the modified unified theory of acceptance and use of technology path model. A sample of 520 university students from Zimbabwe was used to collect data using an online survey created on Google Forms. The findings show that “Habit” had the most influence (0.804) on “Behavioural Intention,” followed by “Performance Expectancy” (0.319) and “Effort Expectancy” (0.270). Behavioural Intention had a significant influence (0.831) on “Use Behaviour.” The path model explains 88.8% of “Behavioural Intention,” and 76.1% of “Use Behaviour” variances. This study though limited, it is significant to students in higher education, policy makers and researchers given the importance of technology in the education sector.
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