摘要
从政策工具视角出发,梳理中国人工智能赋能医学教育有关政策文本,分析政策发展方向,为今后政策的制定和完善提供参考和建议。本研究以154份人工智能赋能医学教育的政策文本为样本进行分析,采取政策语义特征研究、政策工具研究等方法,得出政策的趋势以及政策工具的具体使用情况。分析发现,“人工智能”“医学”“教育”等词占比突出。对所纳入的154份政策文本内容进行编码,统计结果显示政策工具主要以供给型为主,占比为51.15%;需求型政策工具次于之,占比为27.18%;环境型政策工具占比最少,占比为21.65%。研究结果显示,不同类型政策工具的使用存在失衡,应该增加供给型政策工具的实施,同时提高环境型政策工具中激励性工具的使用以及增加需求型政策工具的需求。
From the perspective of policy tools,this paper reviews the relevant policy texts of AI-enabled medical education in China,analyzes the development direction of policies,and provides reference and suggestions for the formulation and improvement of policies in the future.Focusing on 154 policy texts of AI-enabled medical education,we adopted research methods such as policy seman-tic characteristics and policy tools to obtain the policy trends and specific use of policy tools.The analy-sis revealed that words“artificial intelligence”,“medicine”,“education”and so on accounted for a prominent proportion.The contents of 154 included policy texts were coded,and statistical analysis was mainly based on supply tools,accounting for 51.15%;demand policy tools were second only to supply policy,accounting for 27.18%;and environmental policy tools accounted for the smallest pro-portion,only 21.65%.On the whole,there is an imbalance in the use of different types of policy tools.Therefore,the implementation of supply-based policy tools should be increased;so should the use of incentive tools and the demand for demand-based policy tools.
作者
邹陆曦
林华
孙玲
ZOU Luxi;LIN Hua;SUN Ling(School of Management,Xuzhou Medical University,Xuzhou 221000,China;Department of Nephrology,Xuzhou Central Hospital,Xuzhou 221006,China)
出处
《中国医学教育技术》
2025年第1期23-28,共6页
China Medical Education Technology
基金
江苏高校哲学社会科学研究重大项目(2024SJZD062)
江苏省卫生健康委医学科研重点项目(ZD2022044)。
关键词
人工智能
医学教育
政策文本
政策制定
artificial intelligence
medical education
policy text
policy making
作者简介
邹陆曦,副教授,高级工程师,博士,硕士研究生导师,研究方向为智慧医疗与数字健康研究、医学人文教育。E-mail:zouluxi@xzhmu.edu.cn。
