Generative AI in Chemical Education: A Bibliometric Perspective

The emergence of generative artificial intelligence (GenAI), particularly following the release of ChatGPT, has catalyzed a paradigm shift in the field of chemistry education. This study presents a comprehensive bibliometric analysis of the rapidly evolving research landscape from 2023 to February 2026. Data retrieved exclusively from the Web of Science Core Collection were analyzed to map the publication trends, influential sources, and thematic structures. The results reveal an explosive growth in scholarly activity with Journal of Chemical Education serving as the central hub for academic discourse. Geographically, the United States demonstrates dominant leadership in both publication volume and citation impact, while European and Asian contributions highlight a growing but structurally distinct global interest. Keyword co-occurrence analysis identified four major research themes: (1) technological foundations and chemical pedagogy, (2) assessment and AI literacy in undergraduate chemistry, (3) disciplinary specialization and laboratory-based practice, and (4) curricular innovation and student-centered chemistry learning. These findings suggest that GenAI is evolving from a generic tool to a disciplinary collaborator, prompting a fundamental redesign of how chemical knowledge is constructed and evaluated. The study concludes by proposing future directions for longitudinal research and inclusive international collaboration to address the challenges of technological integration.