
浏览全部资源
扫码关注微信
中国医科大学,沈阳 110122
Email:qubo6666@163.com
收稿:2025-03-26,
纸质出版:2025-10-20
移动端阅览
曲波. 推动AI与教育深度融合 构建精准学习新路径[J]. 中华医学教育探索杂志, 2025, 24(10): 1297-1299.
Qu Bo. Promoting deep integration of artificial intelligence and education for new pathways of precision learning[J]. Chinese journal of medical education research, 2025, 24(10): 1297-1299.
曲波. 推动AI与教育深度融合 构建精准学习新路径[J]. 中华医学教育探索杂志, 2025, 24(10): 1297-1299. DOI: 10.3760/cma.j.cn116021-20250326-02133.
Qu Bo. Promoting deep integration of artificial intelligence and education for new pathways of precision learning[J]. Chinese journal of medical education research, 2025, 24(10): 1297-1299. DOI: 10.3760/cma.j.cn116021-20250326-02133.
本文围绕人工智能(artificial intelligence,AI)与教育深度融合的背景,探讨了构建精准学习新路径的理论基础与实践策略。精准学习是一种体系化、概念化、数智化的科学学习范式,能够有效解决教育规模化与个性化之间的矛盾。通过“一体、两翼、三心、四准”的实施框架,即强化学科知识图谱建设、优化数字化资源与题库、推动循证教学与AI赋能、实现精准分类与推送,可系统推进精准学习的落地。最后,展望了医学教育在数智化转型中的发展方向,强调AI技术在提升医学教育质量、推动个性化培养和跨区域合作中的重要作用,旨在为推进中国式教育现代化提供理论支持与实践路径。
This article focuses on discussing the theoretical basis and practical strategies for constructing new pathways of precision learning in the context of the deep integration of artificial intelligence (AI) and education. Precision learning is a scientific
systematic
conceptualized
and digitized learning paradigm that can effectively solve the contradiction between education scaling and personalization. Through implementing a framework that comprises strengthening the construction of disciplinary knowledge graphs
optimizing digital resources and question banks
promoting evidence-informed and AI-empowered instruction
and achieving precise classification and delivery
precision learning can be systematically advanced. Finally
we present an outlook on the future directions of medical education in the era of digital and intelligent transformation
emphasizing the important role of AI technology in improving the quality of medical education
promoting personalized training
and facilitating cross-regional cooperation
with the aim of providing theoretical support and practical paths for building a modern Chinese-style education system.
高举中国特色社会主义伟大旗帜为全面建设社会主义现代化国家而团结奋斗——在中国共产党第二十次全国代表大会上的报告 [J ] . 党史博采 , 2023 ( 22 ): 46 .
吴佳莉 , 郑程月 , 吴霓 . “办人民满意的教育”的内涵、演进与实践路径 [J ] . 清华大学教育研究 , 2018 , 39 ( 6 ): 74 - 79 . DOI: 10.14138/j.1001-4519.2018.06.007406 http://dx.doi.org/10.14138/j.1001-4519.2018.06.007406 .
曾海军 , 王静漪 , 张卓 , 等 . 区域智慧教育建设特色与发展思考 [J ] . 电化教育研究 , 2023 , 44 ( 9 ): 50 - 56 . DOI: 10.13811/j.cnki.eer.2023.09.007 http://dx.doi.org/10.13811/j.cnki.eer.2023.09.007 .
Liu Q , Tian Y , Zhou T , et al . An explainable and personalized cognitive reasoning model based on knowledge graph: toward decision making for general practice [J ] . IEEE J Biomed Health Inform , 2024 , 28 ( 2 ): 707 - 718 . DOI: 10.1109/JBHI.2023.3312154 http://dx.doi.org/10.1109/JBHI.2023.3312154 .
Rampton V , Mittelman M , Goldhahn J . Implications of artificial intelligence for medical education [J ] . Lancet Digit Health , 2020 , 2 ( 3 ): e111 - e112 . DOI: 10.1016/S2589-7500(20)30023-6 http://dx.doi.org/10.1016/S2589-7500(20)30023-6 .
Zhang W , Cai M , Lee HJ , et al . AI in Medical Education: Global situation, effects and challenges [J ] . Educ Inf Technol , 2024 , 29 ( 4 ): 4611 - 4633 . DOI: 10.1007/s10639-023-12009-8 http://dx.doi.org/10.1007/s10639-023-12009-8 .
Sawa K . How we learn: Why brains learn better than any machine. for now (S. Matsuura, Trans.) (Original work published 2020) [J ] . The Japanese Journal of Psychonomic Science , 2022 , 40 ( 2 ): 213- 214. DOI: 10.14947/psychono.40.29 http://dx.doi.org/10.14947/psychono.40.29 .
李令青 , 韩笑 , 辛涛 , 等 . 认知诊断评价在个性化学习中的功能与价值 [J ] . 中国考试 , 2019 ( 1 ): 40 - 44 . DOI: 10.19360/j.cnki.11-3303/g4.2019.01.007 http://dx.doi.org/10.19360/j.cnki.11-3303/g4.2019.01.007 .
Azer SA , Guerrero APS . The challenges imposed by artificial intelligence: are we ready in medical education? [J ] . BMC Med Educ , 2023 , 23 ( 1 ): 680 . DOI: 10.1186/s12909-023-04660-z http://dx.doi.org/10.1186/s12909-023-04660-z .
唐琳 , 归航 , 王辰 . 健康中国背景下新医科建设工作的再思考 [J ] . 国家教育行政学院学报 , 2024 ( 1 ): 51 - 57 .
0
浏览量
1
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621