学生对人工智能支持的药理学培训评估的看法
Jon Andsnes Berg1,2, Øyvind Repstad3, Trond Trætteberg Serkland1,2
1Department of Clinical Science, Faculty of Medicine, University of Bergen, Bergen, Norway.
医学学生发现人工智能 (AI) 反对药理学学习很有用,但对其积极性和评估设计表示担忧. 有效的AI反需要培训学生反素养和程序支持.
科学领域:
- 医学教育
- 教育中的人工智能
- 药理学教育
背景情况:
- 高质量的反对于医学学生的药理学学习至关重要.
- 个性化反是资源密集型的,
- 学生对人工智能所产生的反的看法在很大程度上是未知的.
研究的目的:
- 在形成性药理学评估中调查医学生对人工智能产生的反的看法和利用.
- 了解影响学生人工智能反的因素.
主要方法:
- 涉及三年级医学学生的定性研究.
- 用八个简短答案的药理问题进行形成性评估.
- 使用代主题分析分析的焦点组 (n=11).
主要成果:
- 三个主要主题出现了:反的可信性/可访问性,与学习计划的协调性以及学生反素养.
- 学生认为人工智能反是有用的,
- 其中包括人工智能的积极性,评估时间/任务以及长时间反的工作量.
结论:
- 人工智能支持的形成性评估的有效性取决于技术,上下文和个人因素.
- 人工智能反的成功实施需要为学生提供反素养.
- 教育计划必须激励与人工智能产生的反有意义的参与.
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