Determinants of student adoption of artificial intelligence applications in higher education

Abstract

The integration of artificial intelligence (AI) into educational settings has the potential to transform learning experiences; however, its adoption among students remains impacted by various factors. The current study assesses the determinant factors that shape students' willingness to adopt AI applications. A quantitative approach was applied, and data were collected from 211 undergraduate students at the University of Ha'il. The data were analysed via structural equation modelling (SEM) with the AMOS software. The results revealed that readiness, interactivity, and ethical awareness significantly affect students' adoption of AI applications, while trust and performance did not have a significant effect. These findings suggest that fostering AI adoption among students requires a holistic approach that addresses students' technical preparedness and considers trust-building and ethical educational usage. The implications of this study are significant for educational institutions such as universities, as well as for policy makers, educators and developers aiming at integrating the AI applications effectively into students' learning and curriculum. University administrators could benefit by developing the necessary infrastructure and training, while educators could leverage these insights in designing AI-supported learning environments. Students would benefit from these improved academic experiences that are tailored to their needs. This research contributes to the growing discourse on AI in education and offers a holistic conceptual framework to maximize its potential.

The authors' abstract, as published at the source. Scientific Reports, 2025 · DOI ↗