从调查到模拟:在医疗保健教育中利用ChatGPT和聊天机器人进行基于困境的学习
1Health Systems Management Department, Jerusalem Multidisciplinary College, 37 Hanevi im St, Jerusalem, 9101001 Israel.
Medical science educator
|March 9, 2026
概括
这项研究表明,将基于困境的学习与像ChatGPT和聊天机器人开发这样的AI工具相结合,可以提高医疗管理学生的AI素养和批判性思维. 代过程增强了复杂医疗场景的解决问题和模拟技能.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 健康管理健康管理
背景情况:
- 人工智能 (AI) 在医疗保健中的日益集成,需要在未来的专业人员中提高人工智能素养.
- 传统的教学方法可能无法充分为医疗保健管理学生准备人工智能驱动的环境.
研究的目的:
- 检查一个多阶段的学习框架,将基于困境的学习与人工智能工具 (ChatGPT,聊天机器人开发) 集成为本科医疗管理学生.
- 在这个群体中提升人工智能素养,批判性思维和决策能力.
主要方法:
- 对71个学生的反思期刊进行定性主题分析.
- 实施结构化,多阶段的学习干预,涉及人工智能工具和基于困境的学习.
- 代参与包括快速改进,聊天机器人开发和人工智能驱动的模拟.
主要成果:
- 出现了四个主题:通过询问学习,通过教学和快速改进学习,通过模拟学习,以及斗争和成功.
- 人工智能驱动的学习培养了快速的工程,批判性思维和解决问题的技能.
- 学生们最初面临着迅速制定和聊天机器人对话的挑战,但通过代学习得到了改善.
结论:
- 将人工智能素养和聊天机器人开发集成到医疗保健教育中,对于为学生准备应对复杂困境至关重要.
- 人工智能增强的学习干预有效地提高了学生的分析技能和参与人工智能驱动模拟的能力.
- 这项研究提供了对适应人工智能时代的医学教育的见解.
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