卫生科学教育中人工智能产生的多选题:利益相关者的观点和实施考虑
Matthew Reid1, Michelle French2, Stavroula Andreopoulos3
1University of Toronto, School of Continuing Studies, 158 St George St, Toronto, ON M5S 2V8, Canada.
Current research in physiology
|August 13, 2025
概括
人工智能 (AI),特别是大型语言模型 (LLM),可以快速生成高质量的多选择题 (MCQ) 用于健康科学教育. 本讨论探讨了AI-MCQ的好处,缺点和实施指南.
科学领域:
- 医疗专业教育卫生专业教育
- 教育中的人工智能
背景情况:
- 多选题 (MCQ) 对于评估健康科学中的知识和临床推理至关重要.
- 创建高质量的MCQ是资源密集型,需要大量的时间和专业知识.
研究的目的:
- 探索人工智能的潜力,特别是LLMs,在健康科学教育中产生MCQ.
- 讨论与人工智能驱动的MCQ开发相关的好处和挑战.
- 为实施人工智能生成的MCQ提供实用指南.
主要方法:
- 讨论AI和LLM在教育内容生成中的功能.
- 分析潜在的好处,包括效率和一致性.
- 检查缺点,如准确性,公平性,道德性和隐私问题.
主要成果:
- 人工智能和LLM显示出对高效,一致和定制的MCQ生成的承诺.
- 关键的挑战包括确保问题的准确性,公平性以及解决技术/道德方面的考虑.
- 提出了AI-MCQ实施的指导原则.
结论:
- 人工智能为在健康科学教育中创建MCQ提供了变革性的潜力.
- 仔细考虑准确性,公平性和道德含义对于成功的AI集成至关重要.
- 需要进一步的研究来评估AI产生的MCQ对学生学习和教育成果的影响.
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