Artificial Intelligence Integration in Medical Education: A Landscape with HOT Dimensions in Viet Nam
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Washington, DC: World Bank
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The study adopted a mixed-methods approach to: (i) describe the landscape of Artificial Intelligence (AI) adoption in medical schools in Viet Nam; (ii) analyze critical factors affecting the integration of AI in medical education; (iii) present key strategic actions areas to promote the integration of AI in medical education in Viet Nam. Overall, AI adoption among students and teachers is relatively high, with a large proportion reporting the use of AI-powered tools, particularly generative AI applications such as learning assistants. However, the integration of AI remains largely informal, fragmented, and concentrated in individual-level use cases rather than being systematically embedded into institutional teaching, clinical training, and educational management systems. The analysis of human factors reveals generally supportive attitudes for AI adoption. Students and teachers demonstrate positive attitudes and recognize the benefits of AI in improving learning efficiency, digital literacy, and research capacity. At the same time, important concerns persist regarding over-reliance on AI, reduced critical thinking, academic integrity, and the potential erosion of humanistic aspects of medical practice. From an organizational perspective, key barriers include the lack of structured AI training programs, limited integration of AI competencies into curricula, insufficient financial resources, and the absence of clear regulatory and ethical frameworks. Technological factors present a mixed picture with digital infrastructure providing a strong foundation but digital data underdevelopment and concerns about AI accuracy remain challenges. Advancing AI integration in medical education in Viet Nam requires a comprehensive and coordinated approach across human, organizational, and technological dimensions.
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ARTIFICIAL INTELLIGENCE, DIGITAL LITERACY, MEDICAL EDUCATION, CURRICULUM INTEGRATION, REGULATORY FRAMEWORKS