基于认知与使用视角的临床教师人工智能素养现状与教学应用需求调查

郑兰斌; 徐锐; 周舒艾君; 蔡景一

doi:10.3760/cma.j.cn116021-20251026-02241

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基于认知与使用视角的临床教师人工智能素养现状与教学应用需求调查

数智医学教育 | 更新时间：2026-07-27

- 基于认知与使用视角的临床教师人工智能素养现状与教学应用需求调查
- Artificial intelligence literacy and teaching application needs of clinical teachers: a survey from the perspectives of awareness and practical use
- 中华医学教育探索杂志 2026年25卷第7期页码：786-792
- 作者机构：
  
  1.北京大学医学部教育处，北京 100191
  2.北京大学医学图书馆，北京 100191
- 作者简介：
  
  郑兰斌，Email：zhenglanbin@bjmu.edu.cn
- 基金信息：
  
  北京大学本科教学改革项目(JG2025143)
- DOI：10.3760/cma.j.cn116021-20251026-02241
  中图分类号： R-0;R-4
- 收稿：2025-10-26，
  
  网络首发：2026-03-05，
  
  纸质出版：2026-07-20
- 稿件说明：
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郑兰斌, 徐锐, 周舒艾君, 等. 基于认知与使用视角的临床教师人工智能素养现状与教学应用需求调查[J]. 中华医学教育探索杂志, 2026, 25(7): 786-792.

Zheng Lanbin, Xu Rui, Zhou Shu'aijun, et al. Artificial intelligence literacy and teaching application needs of clinical teachers: a survey from the perspectives of awareness and practical use[J]. Chinese Journal of Medical Education Research, 2026, 25(7): 786-792.
郑兰斌, 徐锐, 周舒艾君, 等. 基于认知与使用视角的临床教师人工智能素养现状与教学应用需求调查[J]. 中华医学教育探索杂志, 2026, 25(7): 786-792. DOI： 10.3760/cma.j.cn116021-20251026-02241.

Zheng Lanbin, Xu Rui, Zhou Shu'aijun, et al. Artificial intelligence literacy and teaching application needs of clinical teachers: a survey from the perspectives of awareness and practical use[J]. Chinese Journal of Medical Education Research, 2026, 25(7): 786-792. DOI： 10.3760/cma.j.cn116021-20251026-02241.

摘要

目的

调查临床教师人工智能（artificial intelligence，AI）素养现状、AI教学应用态度及实际需求，为提升其AI教学能力提供实证依据。

方法

运用问卷调查法，对195名临床教师展开调查。问卷内容涵盖人口学特征、人工智能素养量表、AI教学有用性与易用性态度题项以及开放性问题。采用SPSS 26.0软件进行描述性统计、

检验、方差分析和Wilcoxon符号秩检验，并对开放性问题文本资料开展主题分析。

结果

临床教师AI素养存在意识领先于使用的结构性失衡（意识：5.89±0.86；使用：5.63±0.89），其对AI教学有用性的积极评价率显著高于易用性（75.90% vs. 43.08%，

=-8.02，

0.001）。除性别在意识和评估维度得分上存在差异外，AI素养在不同年龄、学位、职称组间差异均无统计学意义，呈现出“去人口学特征”现象。质性分析表明，教师面临工具选择困难与教学融合不足的双重障碍，普遍停留在基础应用层面，难以实现高阶应用，因而呼吁开展系统培训、提供更便利的AI接入方式。

结论

临床教师普遍认可AI教学价值，但面临知易行难的实践困境。院校需构建系统化支持体系，通过降低技术门槛、加强实操培训、完善激励机制，推动教师从AI技术适应者转变为人机协同主导者，为AI时代医学教育转型奠定坚实基础。

Abstract

Objective

To investigate the current status of artificial intelligence (AI) literacy

the attitudes towards AI teaching applications

and the practical needs among clinical teachers

and to provide an empirical basis for enhancing their AI teaching capabilities.

Methods

A questionnaire survey was conducted among 195 clinical teachers. The questionnaire covered demographic characteristics

an AI Literacy Scale

items on the perceived usefulness and ease of use of AI in teaching

and open-ended questions. Data were analyzed using SPSS 26.0 software

including descriptive statistics

-tests

analysis of variance

and the Wilcoxon signed-rank test. A thematic analysis was performed on the open-ended text responses.

Results

A structural imbalance was identified in the AI literacy of clinical teachers

with the score of awareness (5.89±0.86) exceeding that of practical use (5.63±0.89). Their positive evaluation of AI's usefulness in teachi

ng was significantly higher than its perceived ease of use (75.90% vs. 43.08%

=-8.02

0.001). Except for differences in the awareness and evaluation dimensions related to gender

AI literacy showed no significant differences across age

education

or professional title groups

presenting a "demographic-irrelevant" phenomenon. Qualitative analysis revealed that teachers face the dual challenges of difficulties in tool selection and insufficient integration into teaching practice. Their use predominantly remained at a basic level

with limited progression to advanced applications

thus highlighting the need for systematic training and more accessible AI tools.

Conclusions

Clinical teachers generally recognized the value of AI in teaching but faced practical challenges characterized by "easier said than done". Institutions need to build a systematic support framework by reducing technical barriers

enhancing hands-on training

and improving incentive mechanisms to facilitate the transition of teachers from AI technology adaptors to leaders in human-AI collaboration

thereby laying a solid foundation for the transformation of medical education in the AI era.

关键词

Keywords

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