用人工智能重新定义医学教育中的指导:关于可行性和影响的德尔菲研究
1Faculty of Education, Terzioğlu Campus, Çanakkale Onsekiz Mart University, Çanakkale, Türkiye.
Teaching and learning in medicine
|June 19, 2025
概括
人工智能 (AI) 可以通过提供个性化的指导和反来增强医学学生的指导. 然而,道德考虑和人类监督的需要对于其有效地融入医学教育至关重要.
科学领域:
- 医疗教育 技术 技术 医学教育
- 医疗保健中的人工智能
- 辅导和专业发展的指导和专业发展
背景情况:
- 导师对于医学学生的发展至关重要.
- 人工智能 (AI) 提供了彻底改变医疗指导的机会.
- 现有的指导模式需要适应技术进步.
研究的目的:
- 探索人工智能在指导医学生的潜在好处和局限性.
- 收集有关将基于人工智能的指导整合到医学教育中的专家共识.
- 在医疗指导中解决与AI相关的伦理问题.
主要方法:
- 一个结构化的在线Delphi技术,涉及27个医学教育和AI的跨学科专家.
- 采用了四轮的定性 (专家采访) 和定量 (调查数据) 研究方法.
- 使用描述性统计,弗莱斯卡帕 (κ=0.79) 和类内相关系数 (ICC=0.873) 来衡量共识.
主要成果:
- 在AI导师能力和关键考虑方面取得了实质性的专家共识.
- 人工智能导师通过反显示了个性化学习,职业指导和技能提升的潜力.
- 确定了人工智能对人类深度判断能力的局限性以及过度依赖的风险.
结论:
- 建议采用混合导师模式,将人工智能见解与人类同情心和道德监督相结合.
- 建议在医学教育中对人工智能进行战略性,分阶段整合和跨学科监督.
- 该研究为未来研究优化AI整合到医疗指导中的研究提供了框架.
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