Understanding student adoption of AI technologies in South African higher education: A value-based adoption model approach

Abstract

This study investigates the factors influencing artificial intelligence (AI) adoption among students in South African higher education using the Value-Based Adoption Model (VAM). It contributes to existing literature by extending VAM to AI adoption in the South African higher education context. A quantitative research design was employed, and data were collected through a survey administered to 360 students at a selected South African university. The study examined the influence of perceived value, perceived usefulness, perceived enjoyment, perceived risks, and perceived costs on AI adoption. The findings reveal that all five VAM constructs significantly influence AI adoption, with perceived usefulness emerging as the strongest positive predictor (β = 0.209, p < 0.001) and perceived cost as the strongest negative predictor (β = −0.152, p = 0.006). The model explained 17.3% of the variance in AI adoption, while no statistically significant differences were identified across gender or study levels. The study confirms that students engage in value-maximizing decision-making processes when considering AI adoption by balancing perceived benefits against associated sacrifices. These findings provide practical implications for higher education institutions by emphasizing the importance of enhancing the perceived benefits of AI through demonstrated utility and engaging learning experiences, while simultaneously reducing perceived barriers through structured support mechanisms and clear ethical guidelines.