Generative AI is revolutionizing education by enhancing personalized learning, fostering innovation, and transforming traditional teaching methodologies, making it a critical tool for the future of education. This study aims to explore the impact of generative AI (Gen-AI) technologies, focusing on academic and learning performance, publication trends, and thematic developments through a comprehensive bibliometric analysis. This study employs a bibliometric analysis using data from WoS and Scopus, focusing on publications from 2015 to 2025. The analysis includes keyword co-occurrence, bibliographic coupling, and citation analysis to map the evolving landscape of Gen-AI adoption by students and teachers in education. The study reveals a significant surge in publications on generative AI in education, highlighting key themes such as ChatGPT, and higher education. The United States, Australia, and United Kingdom lead in research contributions, with diverse topics explored across major journals. This study provides a novel bibliometric analysis of generative AI adoption on academic performance, offering unique insights into publication trends, influential journals, and emerging themes, thereby contributing to the understanding of generative AI’s evolving role in education. The results highlight the need for further longitudinal studies to explore the long-term impact of generative AI on educational practices.
Shahzad et al. (Wed,) studied this question.