评估主要课程变化:确保研究生获得心理安全的学习环境
Gail Elliott1, Grace Pinhal-Enfield1,2
1Department of Neuroscience and Cell Biology, Office of Education, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA.
Anatomical sciences education
|October 22, 2025
概括
一个重写的粗体解剖学课程评估显示了积极的学生反. 人工智能对书面评论的分析证实,实现了安全的学习环境,强调了教师的支持和归属.
科学领域:
- 医学教育 医学教育
- 解剖学教学学术的教育学
背景情况:
- 研究生级士的粗体解剖学课程需要有效的课程交付,以获得学生的成功.
- 传统的学生评价 (例如,利克特等级) 往往缺乏对学习环境的细微见解.
- 书面反分析是评估教育环境的一个未充分利用的方法.
研究的目的:
- 为了评估新修订的粗体解剖学课程的成功.
- 为了确定是否建立了一个安全的学习环境,使用人工智能驱动的学生评论情绪分析.
- 确定有助于积极学习体验的关键因素.
主要方法:
- 实施了一个修订后的课程,为研究生级的粗体解剖学课程.
- 收集了88名学生的课程结束评估.
- 利用基于人工智能的文本分析工具来评分情绪,并在学生的书面反中对主题进行分类.
主要成果:
- 在课程变化之后,学生的整体评价非常有利.
- 人工智能分析确定了学生反中的关键主题,包括教师的可用性,知识,幽默,群体动态和归属感.
- 情绪数据分析提供了超越传统量化措施的细微洞察力.
结论:
- 修订后的粗体解剖学课程成功培养了安全和支持性的学习环境.
- 用人工智能驱动的定性反分析是深入教育评估的宝贵工具.
- 诸如教师互动和同行归属等关键要素对于建立积极的学习氛围至关重要.
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