人性化人工智能培训卫生专业教育工作者教育工作者
Jerusalem Merkebu1, Anita Samuel1
1Department of Health Professions Education, Uniformed Services University of Health Sciences, Bethesda, MD, USA.
Medical teacher
|July 9, 2025
概括
卫生专业的教育工作者面临的情感负担,整合生成AI (GenAI). 一个新的课程通过同情的设计来解决这些焦虑,培养对人工智能采用的准备.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 教育心理学教育心理学
背景情况:
- 卫生专业的教育工作者在将生成人工智能 (GenAI) 整合到他们的教学实践中时,经历了相当大的情绪困扰,包括技术压力,自我怀疑和对过时的恐惧.
- 当前的教师发展计划往往忽视了关键的情感层面,优先考虑技术技能,而不是解决教育工作者的焦虑和情感准备,以采用人工智能.
研究的目的:
- 为了解决医疗专业教育工作者采用生成AI (GenAI) 面临的情感负担和情感准备挑战.
- 开发和评估一个富有同情心和创伤感的课程,旨在为人工智能集成创造一个安全和支持的学习环境.
主要方法:
- 一个为期六周的课程题为"AI in Health Professions Education"被设计和实施.
- 该课程结合了同情设计和创伤知情教学原则,重点关注心理安全,透明度,协作和学习者赋权.
- 策略包括验证情绪反应,促进实验,教练对人工智能使用和个人焦虑的透明度,并为学习者提供选择来增强代理.
主要成果:
- 承认和解决教育工作者的情感准备对于成功采用人工智能至关重要;仅仅是技术技能是不够的.
- 富有同情心,心理安全和赋权的策略有效地减轻了与人工智能相关的常见焦虑,例如对不足的恐惧.
- 这种方法为教育工作者在各种全球环境中实现可行和赋权的AI采用提供了便利.
结论:
- 优先考虑学习的情感层面对于有效地将技术整合到卫生专业教育中至关重要.
- 富有同情心和创伤知识的教学方法可以成功地解决围绕人工智能的广泛焦虑,促进更大的采用和信心.
- 未来的研究应该调查情感学习结果,并开发全球可访问的人工智能培训工具包,特别是在资源较少的环境中.
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