Revolutionising Learning: An Attempt to Understand the Impact of AI-Driven Personalised Education on Under- graduate Student Engagement and Performance

Abstract

Artificial Intelligence, rapidly becoming part of educational systems worldwide, and is transforming learning and teaching in schools and other higher education institutions by giving students real-time experiences. Meanwhile, per-sonalised education led by AI is reshuffling the process of learning. Recent research has often been directed toward particular applications of AI tools and the assessment of AI education's overall impact. There have not been ample studies investigating the mediating effect of student engagement and the moderating effects of learner characteristics on AI learning outcomes (Saleem et al., 2025). This study attempts to fill that gap by proposing a research framework for the analysis of the impact of AI-driven personalised learning on students' engagement and performance among undergraduate students within Qatar University, particularly looking at the mediating effect of engagement and the moderating impact of learner characteristics at different levels of education. The anticipated research findings of the testing of the proposed framework are expected to provide clear insights into the effects of AI-driven personalised learning on Qatar University undergraduate students' engagement and performance. Such research findings will not only add to the current knowledge in the field. Still, they will also provide helpful guidance for university educators and policymakers on how to maximise the valuable influence of AI-driven personalised learning usage on UG students.