From medical to pedagogical care: A bibliometric review of AI agent research in education.

BACKGROUND: The integration of artificial intelligence (AI) agents, including chatbots and virtual tutors, into education has expanded rapidly; however, systematic quantitative analysis of research trends in this field remains limited. Notably, the intellectual foundations of AI agent research lie not in education but in medicine, where AI agents were first extensively deployed and studied in clinical, experimental, and pedagogical contexts. METHODS: In this study, a bibliometric analysis of 377 records retrieved from the Web of Science was conducted using VOSviewer to map the evolution, thematic focus, and collaborative networks within this field. RESULTS: The study showed AI agent research originated strongly in healthcare, with educational applications emerging more recently. Key research themes encompassed AI technologies, human-computer interaction, pedagogical applications, and ethical considerations. Collaborative efforts were led by the USA and China, supported by active European and Asian research hubs. The findings revealed a dual narrative of significant benefits for personalized learning and learner well-being alongside persistent challenges such as algorithmic bias and accessibility gaps. CONCLUSION: To realize the transformative potential of AI in education, future research should prioritize the development of adaptive algorithms, robust ethical frameworks, inclusive design, and interdisciplinary collaboration. By focusing on these areas, the field can work toward overcoming technical, ethical, and logistical barriers, thereby ensuring that AI acts as a sustainable force for equity and excellence in education.