环境听力设备作为模拟学习环境中的反工具
Robert Snedegar1, Kendra Unger1, Jason F Craig2
1Department of Family Medicine, West Virginia University School of Medicine, Morgantown, USA.
Cureus
|February 12, 2026
概括
人工智能 (AI) 环境倾听 (AL) 显示出在医疗教育中提供形成性反的希望. 这项试点研究发现,人工智能产生的反是可行的,得到了很好的接受,并且与模拟患者接触中的学习者自我评估保持一致.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 临床模拟 临床模拟
背景情况:
- 人工智能在模拟的临床接触中提供形成性反的证据有限.
- 环境听 (AL) 技术虽然对文档有好处,但对于教育反来说尚未得到充分探索.
- 这项研究解决了在本科医学教育中评估人工智能产生的反的需要.
研究的目的:
- 通过使用AL技术评估人工智能生成反的可行性.
- 评估这种反的感知质量和学习者接受程度.
- 探索AI在模拟患者接触中补充形成性反中的作用.
主要方法:
- 一年级和二年级的医学学生参加了模拟的患者接触.
- 通过使用人工智能驱动的AL应用程序记录了遭遇.
- 创建了自动反和SMART目标;学习者完成了关于反质量的验证调查.
主要成果:
- 所有参与者都认为人工智能反足够,可操作和与行为相关.
- 定性反描述了人工智能生成的评论是准确的,并与其他评估保持一致.
- 学习者为更大的背景和具体的例子提出了改进建议.
结论:
- 人工智能驱动的AL是一种可行且被广泛接受的方法,用于在模拟的临床环境中补充形成性反.
- 它可能为直接观察提供了一个可扩展的替代方案,特别是在教师数量有限的情况下.
- 需要进一步的多机构研究来证实可通用性和教育影响.
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