聊天GPT为教学和评估生成临床图片和多选择题:一个随机控制实验
Özlem Coşkun1, Yavuz Selim Kıyak1, Işıl İrem Budakoğlu1
1Department of Medical Education and Informatics, Gazi University, Ankara, Turkey.
Medical teacher
|March 13, 2024
概括
聊天GPT生成的临床图片和多选题 (MCQ) 的质量与医学教育中人类撰写的材料相美. 一些MCQ表现出可接受的心理测量属性进行评估.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 教育技术的教育技术
背景情况:
- 像ChatGPT这样的人工智能 (AI) 工具的整合为教育内容生成提供了新的可能性.
- 在现实世界的教育环境中评估人工智能产生的材料的有效性对于采用至关重要.
- 基于证据的医学培训需要高质量的临床病例和评估.
研究的目的:
- 评估由ChatGPT创建的临床小题和多项选择题 (MCQ) 的现实表现.
- 将ChatGPT生成的教育材料的质量与人类撰写的内容进行比较.
- 评估人工智能生成的MCQ的心理测量特性,用于医学教育评估.
主要方法:
- 一项随机对照研究,涉及74名医学学生参加基于证据的医学培训计划.
- 两组被分配:一个接收了ChatGPT生成的案例,另一个接收了人类编写的案例.
- 参与者使用利克特尺度评估病例质量,并完成ChatGPT生成的MCQ;分析了心理测量特征.
主要成果:
- 在ChatGPT和对照组之间的病例评估中没有发现显著差异 (p > .05).
- 在ChatGPT生成的15个MCQ中,只有6个具有可接受的点-双序列相关性 (>0.30).
- 五个MCQ满足了课堂评估的可接受标准,表明部分心理测量有效性.
结论:
- 通过ChatGPT生成的临床图片在质量上与人类撰写的相似.
- 一些人工智能生成的MCQ具有可接受的心理测量特征用于教育评估.
- 聊天GPT证明了在医疗教育中创建用于教学的临床图片和用于评估的MCQ的潜力.
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