学生的观点对GenAI来说很重要,在医学教育中的质疑
Olivia Ng1, Siew Ping Han1, Lin Anne Chui1
1Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Medical science educator
|October 20, 2025
概括
医学学生无法区分人工智能和人类创造的多选择题. 由于对准确性和相关性的担忧,他们反对在没有专家审查的情况下在评估中使用人工智能生成的问题.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 评估方法 评估方法
背景情况:
- 将生成人工智能 (GenAI) 整合到医学教育中,带来了新的机遇和挑战.
- 医学学生的感知对于新评估技术的有效和道德实施至关重要.
研究的目的:
- 调查医学学生在GenAI生成和临床医生生成的多选择题 (MCQ) 之间区分的能力.
- 探索学生在正式评估中使用GenAI生成的MCQ的观点.
主要方法:
- 对86名MBBS学生进行了一项调查.
- 参与者被要求区分ChatGPT生成的MCQ和临床教育者创建的MCQ.
- 收集了学生关于在评估中使用GenAI的看法.
主要成果:
- 学生在区分ChatGPT设置和临床医生设置问题方面的表现在统计学上没有显著性,表现在机会水平 (p = 0.46).
- 参与者强烈反对使用未经审查的GenAI产生的问题.
- 学生们提到的关键问题包括人工智能产生的内容的准确性,相关性和教育价值.
结论:
- 医学学生无法可靠地区分GenAI生成的和人类专家生成的评估项目.
- 在医学评估中采用GenAI需要仔细考虑学生的反和工具的教育有效性.
- 专家审查和关注教育价值对于将GenAI负责任地整合到学生评估中至关重要.
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