Volume 20, Issue 4 (Winter 2026)
jmed 2026, 20(4): 1411-1425 |
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Mokhtarezadeh M M. The Role of Artificial Intelligence in Reshaping Teaching and Learning Structures in Medical Education: A Narrative Review. jmed 2026; 20 (4) :1411-1425
URL: http://jmed.ssu.ac.ir/article-1-1603-en.html
URL: http://jmed.ssu.ac.ir/article-1-1603-en.html
Medical Student, Student Research Committee, School of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran , 0930moein@gmail.com
Abstract: (20 Views)
Introduction: Artificial intelligence is increasingly influencing teaching, learning, and assessment processes in medical education. Recent advances, particularly in generative AI, have highlighted the limitations of traditional educational models and underscored the need to reconsider educational paradigms and curricula. The aim of this narrative review is to reconfigure the structures of teaching and learning in medical sciences education.
Methods: This study was conducted as a narrative review of Persian- and English-language articles published between 2015 and 2025. Relevant studies were retrieved from PubMed, Scopus, Web of Science, SID, Irandoc, and Magiran using keywords related to artificial intelligence, medical education, curriculum, and generative AI. After removing duplicates and independently screening titles, abstracts, and full texts by two reviewers, a total of 15 articles met the inclusion criteria. Data were extracted and analyzed using qualitative thematic content analysis.
Results: : Analysis of the selected studies resulted in the identification of five main themes: AI driven innovative learning paradigms, the need for curriculum revision, the educational role of generative AI, stakeholders’ attitudes and readiness, and ethical challenges and considerations. The evidence indicated that AI can enhance personalized learning, clinical simulation, and educational feedback; however, challenges such as algorithmic bias, the generation of inaccurate information, and threats to academic integrity were also frequently reported.
Conclusion: Effective integration of AI into medical education requires a systematic, evidence based, and ethics oriented approach, along with targeted curriculum reform to address existing gaps.
Methods: This study was conducted as a narrative review of Persian- and English-language articles published between 2015 and 2025. Relevant studies were retrieved from PubMed, Scopus, Web of Science, SID, Irandoc, and Magiran using keywords related to artificial intelligence, medical education, curriculum, and generative AI. After removing duplicates and independently screening titles, abstracts, and full texts by two reviewers, a total of 15 articles met the inclusion criteria. Data were extracted and analyzed using qualitative thematic content analysis.
Results: : Analysis of the selected studies resulted in the identification of five main themes: AI driven innovative learning paradigms, the need for curriculum revision, the educational role of generative AI, stakeholders’ attitudes and readiness, and ethical challenges and considerations. The evidence indicated that AI can enhance personalized learning, clinical simulation, and educational feedback; however, challenges such as algorithmic bias, the generation of inaccurate information, and threats to academic integrity were also frequently reported.
Conclusion: Effective integration of AI into medical education requires a systematic, evidence based, and ethics oriented approach, along with targeted curriculum reform to address existing gaps.
Keywords: Artificial intelligence, Medical education, Curriculum, Generative artificial intelligence
Type of Study: Review |
Subject:
Medical Education
Received: 2025/11/12 | Accepted: 2026/02/23 | Published: 2026/04/4
Received: 2025/11/12 | Accepted: 2026/02/23 | Published: 2026/04/4
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