Understanding Student Engagement in AI ‐Assisted Learning in Higher Education: The Roles of AI Support, Teacher Support and Flow
TL;DR
The findings suggest that student engagement in AI‐assisted learning is linked not only to the availability of technological and interpersonal support, but also to the extent to which students experience learning as focused, absorbing and meaningful.
Abstract
With the increasing integration of artificial intelligence (AI) in higher education, this study examined how AI support, teacher support and flow are associated with student engagement in AI‐assisted learning in higher education. Drawing on Self‐Determination Theory, a cross‐sectional survey was conducted with 677 university students from multiple institutions who had prior experience using AI‐enabled tools for learning. Data were analysed using structural equation modelling with AMOS 26.0 to examine the hypothesised relationships among the study variables. The results showed that AI support and teacher support were both positively associated with student engagement. In addition, both forms of support were positively associated with flow and flow was positively associated with engagement. Mediation analyses further indicated that flow mediated the associations between AI support and engagement and between teacher support and engagement. These findings suggest that student engagement in AI‐assisted learning is linked not only to the availability of technological and interpersonal support, but also to the extent to which students experience learning as focused, absorbing and meaningful. The study contributes to current research by integrating technological support, teacher support and experiential processes into a single framework for understanding engagement in AI‐assisted learning in higher education.