Generative artificial intelligence driving the digital transformation of medical education: challenges and implementation pathways

doi:10.3760/cma.j.cn115259-20241212-01292

Chinese Journal of Medical Education ›› 2025, Vol. 45 ›› Issue (10): 754-759.DOI: 10.3760/cma.j.cn115259-20241212-01292

• Educational Technologies • Previous Articles Next Articles

Generative artificial intelligence driving the digital transformation of medical education: challenges and implementation pathways

Zhang Yuan¹, Wu Bohan², Tang Bin², Li Zhenglin³, Yi Minhan²

¹Department of Respiratory Medicine, Xiangya Hospital, Central South University & National Clinical Research Center for Geriatric Disorders, Changsha 410008, China;
²Department of Biomedical Informatics, School of Life Sciences, Central South University, Changsha 410013, China;
³Department of Education, College of Education, Fujian Normal University, Fuzhou 350007, China

Received:2024-12-12 Published:2025-09-28
Contact: Yi Minhan, Email: minhan@csu.edu.cn
Supported by:
The Hunan Provincial Education Reform Project (HNJG-20230104); the Hunan Provincial Degree & Postgraduate Education Reform Project (2023JGYB026, 2023JGYB016, 2024JGYB042); the Undergraduate Education Reform Project of Central South University (2024jy103)

Abstract

Abstract: Generative AI brings opportunities for advancing the digital transformation of medical education in areas such as handling highly abstract medical concepts, simulating clinical scenarios, and providing personalized medical teaching interactions. This article, based on the practical needs of digital transformation in medical education, analyzes the opportunities, risks, and implementation pathways of applying generative AI in medical education. It proposes a four-dimensional practical framework of ″literacy-resources-teaching-governance″ and emphasizes that the digital transformation of medical education empowered by generative AI must always adhere to the principle of ″physician-centeredness.″

Key words: Education, medicine, Generative AI, Digital transformation of education

CLC Number:

R-05

Zhang Yuan, Wu Bohan, Tang Bin, Li Zhenglin, Yi Minhan. Generative artificial intelligence driving the digital transformation of medical education: challenges and implementation pathways[J]. Chinese Journal of Medical Education, 2025, 45(10): 754-759.

References

[1] 中共中央国务院印发《教育强国建设规划纲要(2024—2035年)》[EB/OL]. (2025-01-19)[2025-03-27].http://www.moe.gov.cn/jyb_xxgk/moe_1777/moe_1778/202501/t20250119_1176193.html.
[2] 王金, 王秋杰, 赵文龙, 等. 教育数字化转型背景下智慧医学人才培养探索[J].医学信息学杂志,2024,45(10):1-6.
[3] 兰雪, 张晗, 何佳陆, 等. 教育数字化转型背景下医学生数字素养现状及对策研究[J].医学信息学杂志,2024,45(11):99-103. DOI: 10.3969/j.issn.1673-6036.2024.11.016.
[4] 姚海燕, 邵丽, 周燕婷, 等. 数字化赋能,新范式管理:临床实习智慧化管理平台的构建路径[J].中国医学教育技术,2025,39(1):87-92. DOI: 10.13566/j.cnki.cmet.cn61-1317/g4.202501015.
[5] 饶玉良, 徐辉, 张亚东, 等. 数字化背景下基础医学教学全景实验室建设的思考[J].中国医学教育技术,2024,38(6):699-703. DOI: 10.13566/j.cnki.cmet.cn61-1317/g4.202406001.
[6] 黎济荣, 李国俊, 程洪全. 基层中医院临床病理创新学习方式的实践[J].中华医学教育探索杂志,2019,18(12):1287-1291. DOI: 10.3760/cma.j.issn.2095-1485.2019.12.024.
[7] Morimoto T, Hirata H, Ueno M, et al. Digital transformation will change medical education and rehabilitation in spine surgery[J]. Medicina (Kaunas), 2022,58(4):508. DOI: 10.3390/medicina58040508.
[8] Lauinger AR, McNicholas M, Bramlet M, et al. Applications of mixed reality with medical imaging for training and clinical practice[J]. J Med Imaging (Bellingham), 2024,11(6):062608. DOI: 10.1117/1.JMI.11.6.062608.
[9] Jeyaraman M, Ramasubramanian S, Balaji S, et al. ChatGPT in action: harnessing artificial intelligence potential and addressing ethical challenges in medicine, education, and scientific research[J]. World J Methodol, 2023,13(4):170-178. DOI: 10.5662/wjm.v13.i4.170.
[10] Friederichs H, Friederichs WJ, März M. ChatGPT in medical school: how successful is AI in progress testing?[J]. Med Educ Online, 2023,28(1):2220920. DOI: 10.1080/10872981.2023.2220920.
[11] Spennemann DHR. ChatGPT and the generation of digitally born ″knowledge″: how does a generative AI language model interpret cultural heritage values?[J]. Knowledge, 2023, 3(3): 480-512. DOI:10.3390/knowledge3030032.
[12] 国家互联网信息办公室, 国家发展和改革委员会, 教育部, 等. 生成式人工智能服务管理暂行办法[EB/OL]. (2023-08-15)[2025-03-27]. https://www.gov.cn/gongbao/2023/issue_10666/202308/content_6900864.html.
[13] 祝智庭, 韩中美, 黄昌勤. 教育人工智能(eAI): 人本人工智能的新范式[J].电化教育研究,2021,42(1):5-15. DOI: 10.13811/j.cnki.eer.2021.01.001.
[14] Assefa Y, Gebremeskel MM, Moges BT, et al. Rethinking the digital divide and associated educational in(equity) in higher education in the context of developing countries: the social justice perspective[J]. International Journal of Information and Learning Technology, 2025,42(1):15-32. DOI:10.1108/IJILT-03-2024-0058.
[15] 黄红涛, 余琳, 王继新. 生成式人工智能赋能的非线性学习智能体模型建构[J].中国电化教育,2024(11):61-68. DOI: 10.3969/j.issn.1006-9860.2024.11.009.
[16] 牟智佳, 岳婷, 朱陶. 人机协同视域下基于认知智能大模型的个性化学习设计研究[J].电化教育研究,2025,46(2):80-87. DOI: 10.13811/j.cnki.eer.2025.02.011.
[17] Qiu J, Li L, Sun J, et al. Large AI models in health informatics: applications, challenges, and the future[J]. IEEE J Biomed Health Inform, 2023,27(12):6074-6087. DOI: 10.1109/JBHI.2023.3316750.
[18] 李志涛. 过程性评价纳入高校招生评价体系的国际经验与启示[J].中国考试,2021(2):69-76. DOI: 10.19360/j.cnki.11-3303/g4.2021.02.008.
[19] Karabacak M, Ozkara BB, Margetis K, et al. The advent of generative language models in medical education[J]. JMIR Med Educ, 2023,9:e48163. DOI: 10.2196/48163.
[20] 徐光木, 熊旭辉, 张屹, 等. ChatGPT助推教育考试数字化转型:机遇、应用及挑战[J].中国考试,2023(5):19-28. DOI: 10.19360/j.cnki.11-3303/g4.2023.05.003.
[21] Sallam M. ChatGPT Utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns[J]. Healthcare (Basel), 2023,11(6):887. DOI: 10.3390/healthcare11060887.
[22] Masters K, Herrmann-Werner A, Festl-Wietek T, et al. Preparing for artificial general intelligence (AGI) in health professions education: AMEE Guide No. 172[J]. Med Teach, 2024,46(10):1258-1271. DOI: 10.1080/0142159X.2024.2387802.
[23] 宋超, 章文, 洪云霞, 等. 医学虚拟仿真教学的人工智能化前景探讨[J].医学教育研究与实践,2023,31(5):515-519. DOI: 10.13555/j.cnki.c.m.e.2023.05.001.
[24] Lim WM, Gunasekara A, Pallant JL, et al. Generative AI and the future of education: ragnarök or reformation? a paradoxical perspective from management educators [J]. The International Journal of Management Education, 2023, 21(2): 100790. DOI:10.1016/j.ijme.2023.100790.
[25] D'Mello S, Lehman B, Pekrun R, et al. Confusion can be beneficial for learning[J].Learning and Instruction, 2014, 29: 153-170. DOI:10.1016/j.learninstruc.2012.05.003.
[26] 周洪宇, 常顺利. 生成式人工智能嵌入高等教育的未来图景、潜在风险及其治理[J].现代教育管理,2023(11):1-12. DOI: 10.16697/j.1674-5485.2023.11.001.
[27] Reddy S. Generative AI in healthcare: an implementation science informed translational path on application, integration and governance[J]. Implement Sci, 2024,19(1):27. DOI: 10.1186/s13012-024-01357-9.
[28] Boscardin CK, Gin B, Golde PB, et al. ChatGPT and generative artificial intelligence for medical education: potential impact and opportunity[J]. Acad Med, 2024,99(1):22-27. DOI: 10.1097/ACM.0000000000005439.
[29] 李廷翰, 张素芳. 高校用户AI素养框架探索[J].图书馆论坛,2025,45(1):78-86.
[30] Masters K, MacNeil H, Benjamin J, et al. Artificial intelligence in health professions education assessment: AMEE Guide No. 178[J]. Med Teach, 2025:1-15. DOI: 10.1080/0142159X.2024.2445037.
[31] Masters K. Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158[J]. Med Teach, 2023,45(6):574-584. DOI: 10.1080/0142159X.2023.2186203.

Generative artificial intelligence driving the digital transformation of medical education: challenges and implementation pathways

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