在自动项目生成中使用人工智能和基于模板的混合方法在医学教育中创建多选择题:混合AIG
Yavuz Selim Kıyak1,2, Andrzej A Kononowicz2
1Department of Medical Education and Informatics, Faculty of Medicine, Gazi University, Ankara, Turkey.
JMIR formative research
|April 4, 2025
概括
本研究介绍了用于医学教育的自动项目生成 (AIG) 的混合方法,将人工智能 (AI) 与专家监督相结合. 这种方法有效地创建评估项目模板,增强开发过程.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 教育技术的教育技术
背景情况:
- 传统的项目写作是劳动密集型的.
- 基于模板的自动项目生成 (AIG) 依赖于专家模型开发.
- 非基于模板的AIG面临着准确性挑战.
- 医学教育需要人工智能支持,以有效地生成项目.
研究的目的:
- 提出并展示一种混合AIG方法,用于在医学教育中生成项目模板.
- 探索使用人工智能与人类专家合作创建项目模板的可行性.
主要方法:
- 一个混合方法,方法研究与概念验证元素.
- 提出了一种混合AIG方法,涉及结构化的人类-人工智能交互.
- 杆人工智能用于生成项目模型 (模板) 和认知模型.
- 用两个医学多选择题 (呼吸道感染,儿科过敏反应) 进行演示.
主要成果:
- 混合AIG方法涉及7个步骤的过程,最初的5个步骤由专家在定制的人工智能环境中执行.
- 人工智能证明了在10分钟内在专家控制下生成项目模板的能力.
- 在模板开发中利用人工智能显著减少了挑战.
结论:
- 混合AIG方法将AI的生成能力与专家监督相结合.
- 这种方法利用现有的AIG方法的优势和减轻弱点.
- 它提供了一个人-人工智能协作模型,以提高医学教育评估项目生成的效率.
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