Transforming Online Learning Through Generative AI: Enhancing Personalized Learning and Student Engagement in Higher Education

Abstract

This study aims to examine how Generative Artificial Intelligence (GenAI) transforms online learning by enhancing personalized learning and student engagement in education. A qualitative case study design was employed at school. Data were collected through in-depth interviews, observations, and documentation involving school leaders, teachers, and students. Data were analyzed through data condensation, data display, and conclusion drawing and verification, while data credibility was established through source, technique, and time triangulation, supported by member checking. The findings indicate that GenAI enhanced personalized learning by providing individualized explanations, additional examples, repeated clarification, and flexible learning assistance according to students’ needs and learning pace. GenAI also strengthened student engagement by encouraging active questioning, cognitive exploration, independent learning, learning persistence, and sustained participation. The study concludes that GenAI functions effectively as a pedagogical mediator when integrated with teacher guidance and purposeful learning activities rather than replacing educators. The findings imply that educational institutions should develop responsible AI integration strategies, strengthen teacher competencies and student AI literacy, and maintain human-centered pedagogical supervision to maximize meaningful learning outcomes.