使用大型语言模型实现以故事为中心的课程的实施和教育影响:物理治疗学生的内部障碍课程
Shota Okuno1, Kenta Kawamitsu1, Tamotsu Yamaguchi2
1Department of Rehabilitation, Aso Iizuka Hospital, IIzuka, JPN.
Cureus
|November 13, 2025
概括
这项研究表明,与传统方法相比,使用大型语言模型 (LLM) 为物理治疗学生创建以故事为中心的课程 (SCC) 显著提高了临床推理技能和学习者参与度. 通过LLM驱动的SCC方法提供了一种高效有效的方法来增强物理治疗教育.
科学领域:
- 医学教育 医学教育
- 健康 职业 教育 教育 专业
- 数字健康数字健康
背景情况:
- 故事为中心的课程 (SCC) 提高了临床推理和参与度,但开发需要大量资源.
- 大型语言模型 (LLM) 提供了一个潜在的解决方案,可以有效地创建高保真性的教育场景.
研究的目的:
- 为物理治疗学生开发和评估LLM生成的SCC.
- 评估LLM创建的纵向呼吸病例的教育影响.
主要方法:
- 与历史对照组进行的准实验性研究.
- 干预:15个会议课程,包括8个LLM生成的SCC会议与传统的基于案例的会议.
- 主要结果:能力测试成绩的变化;次要结果:通过利克特尺度学习者体验.
主要成果:
- 与对照组相比,LLM-SCC组在测试分数 (p < 0.001) 和更高的测试后分数 (p = 0.013) 中表现出明显更大的改善.
- 在LLM-SCC组中,超过90%的积极反对沉浸和学习保留.
- 参与LLM-SCC独立预测了更好的测试后表现 (p < 0.001).
结论:
- 通过LLM生成的SCC是物理治疗的创新和有效的教育方法.
- 这种方法平衡了提高学习成果与高效的场景开发.
- 通过LLM驱动的SCC具有在物理治疗中推进基于模拟的教育的巨大潜力.
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