聊天GPT可以生成可接受的基于案例的多选题医学院解剖学考试吗? 一个关于项目难度和歧视的试点研究
Yavuz Selim Kıyak1, Ayşe Soylu2, Özlem Coşkun1
1Department of Medical Education and Informatics, Faculty of Medicine, Gazi University, Ankara, Turkey.
Clinical anatomy (New York, N.Y.)
|March 25, 2025
概括
人工智能 (AI) 可以生成基于病例的解剖学多选择题 (MCQ) 进行医学检查. 这些人工智能生成的MCQ显示了可接受的难度和歧视,帮助医学教育.
科学领域:
- 医学教育 医学教育
- 人工智能在评估中的作用
背景情况:
- 开发高质量的医学院MCQ是资源密集的.
- 像ChatGPT这样的AI工具为评估项目生成提供了潜在的解决方案.
研究的目的:
- 评估ChatGPT在生成基于病例的解剖学MCQ的能力.
- 评估AI生成的医疗考试MCQ的心理测量特性 (难度和歧视).
主要方法:
- 使用ChatGPT创建基于案例的解剖学MCQ,使用人工智能辅助的项目生成框架.
- 产生的MCQs经过专家审查,部门批准,并给502名医学学生.
- 分析了项目难度和歧视指数.
主要成果:
- 项目歧视指数从0.29到0.54不等,表明了良好的差异化.
- 土耳其MCQ (100%) 和英语MCQ (83%) 达到较高的歧视值 (≥0.30).
- 项目难度指数从0.41到0.89不等,大多数项目处于中等范围 (0.20-0.80).
结论:
- 聊天GPT可以产生基于病例的解剖学MCQ,具有可接受的心理测量特性,用于医学教育.
- 人工智能为生成评估项目提供了一个有希望的工具,但人类监督仍然至关重要.
- 进一步的研究应该探索不同的解剖学主题和不同的AI模型用于MCQ生成.
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