Smart education, supported by artificial intelligence (AI), big data, and virtual simulation, is reshaping medical education toward more flexible and collaborative models. However, persistent barriers—fragmented governance, limited data interoperability, and uneven resource distribution—continue to constrain effective collaboration between medical schools and teaching hospitals. This narrative review synthesizes recent developments in digital governance for medical education and proposes a four-layer framework comprising institutional foundations, cross-organizational mechanisms, platform-based technological support, and data-driven quality assurance. The review also highlights key implementation considerations, including interoperability standards for integrating educational and clinical data, staged technology adoption across different resource settings, and governance-oriented evaluation criteria for AI-enabled assessment (e.g., effectiveness, reliability, fairness, explainability, and human oversight). Finally, it discusses privacy, security, and algorithmic accountability challenges under different regulatory contexts. Overall, smart education may facilitate a transition toward more data-informed governance, while requiring context-sensitive implementation and robust ethical safeguards.
Zhang et al. (Fri,) studied this question.