Mapping the Rise of Generative AI in Personalized Learning: A Global Bibliometric Analysis in Higher Education

The rapid development of Generative Artificial Intelligence (GenAI), especially large language models, has heightened academic attention on its role in incentivizing personalized learning in higher education. The current paper will include a thematic bibliometric survey of the Scopus-indexed articles published by 2023 and 2025 to trace the changing research environment at the intersection of generative AI and personalized learning. Through the Bibliometrix R package through Biblioshiny and VOSviewer, the analysis is performed to analyze the development of publications, journals and documents with the greatest impact, patterns of international collaboration, and the development of research topics. The results demonstrate a dramatic rise in the number of research and a great involvement of the world, and also the change in the scholarly perspective of research towards pedagogic, ethical and institutional issues. Such themes of research are AI-facilitated personalized learning, student engagement, academic honesty, and responsible usage of AI. This study can inform researchers, educators, and policymakers in the timely manner by synthesizing the global research trends, so that they can design, govern, and assess generative AI-enhanced personalized learning in higher education.