聊天GPT与对比. 人类在产生护理研究生考试多选题 - 国际视角研究研究
Nader Alnomasy1, Jiyoun Song2, Romeo Jr Mostoles1
1University of Hail, School of Nursing, Saudi Arabia.
Studies in health technology and informatics
|August 8, 2025
概括
与人类创建的问题相比,聊天GPT生成的护理考试多选择题 (MCQ) 在相关性和认知水平方面得分更高,但在偏见和包容性方面得分更低.
科学领域:
- 护理教育 护理教育
- 教育中的人工智能
- 评估和评价的评估和评估.
背景情况:
- 人工智能 (AI) 在教育中日益集成,需要评估其在生成评估工具方面的有效性.
- 多选题 (MCQ) 是评估护理知识的常用格式.
- 将人工智能生成的内容与人类专家创建的内容进行比较,对于理解人工智能在教育评估中的作用至关重要.
研究的目的:
- 将ChatGPT生成的MCQ质量与经验丰富的人类护理教育者为研究生级护理考试创建的质量进行比较.
- 在包括认知水平,相关性,偏见和包容性在内的关键质量领域评估AI产生的MCQ.
主要方法:
- 一个由25名国际护理教育工作者组成的小组使用5分利克特级别评估了100个MCQ (50个由人工智能生成,50个由人类生成).
- 评估标准包括认知水平,场景相关性,分心因子的可信性,偏见,包容性和与布鲁姆的分类学保持一致.
主要成果:
- 聊天GPT生成的MCQ在场景相关性和认知水平方面被评为显著更高.
- 人类生成的MCQ被认为具有较低的偏见和更高的包容性.
- 人工智能生成的问题显示了高级认知评估和相关性的潜力.
结论:
- 像ChatGPT这样的AI工具在为护理教育生成高质量的MCQ方面表现有希望,特别是在相关性和认知复杂性方面.
- 需要进一步精细化,以解决潜在的偏见,并提高AI产生的评估项目的包容性.
- 人工智能可以作为教育工作者开发评估材料的宝贵补充工具.
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