Generative artificial intelligence in education: a comprehensive analysis based on bibliometrics

Currently, generative artificial intelligence (GAI) is advancing rapidly and being increasingly adopted. However, systematic and comprehensive analyses of its integration into educational management are scarce. This study employs bibliometric analysis supplemented by visualization tools to conduct multi-dimensional statistical analyses of 506 valid studies retrieved from the Web of Science database, aiming to depict the current research status and evolutionary trends of GAI in educational management. The quantitative analysis yielded four key findings: first, publication output showed an overall upward trend, with a sharp increase after 2022, suggesting that this topic may attract increasing research attention; second, GAI exhibits a dual nature in educational management applications, with no clear predominance of merits over demerits; third, research on GAI in educational management spans multiple application contexts, while cross-domain collaboration across subfields remains to be strengthened; fourth, the findings suggest that future research may increasingly focus on GAI tool innovation and intelligent educational management. Theoretically, this study delineates the research trajectory of GAI applications in educational management, offering data-backed support and decision-making insights for the formulation of relevant policies and practical implementation of GAI in educational management practices.