评估问题特征对ChatGPT的表现和响应解释一致性的影响:来自台湾护士执照考试的见解
Mei-Chin Su1, Li-En Lin2, Li-Hwa Lin3
1Department of Nursing, Taipei Veterans General Hospital, Taipei, Taiwan.
International journal of nursing studies
|February 24, 2024
概括
在准备护士学生参加执照考试时,ChatGPT的准确率达到了80.75%,尽管表现因科目和问题类型而异. 人类专家审查揭示了不一致性,突出了护理教育中人工智能发展的领域.
科学领域:
- 教育中的人工智能
- 护理教育 技术 技术
- 机器学习用于医疗保健
背景情况:
- 研究人工智能 (AI) 工具,特别是ChatGPT,在护理教育中的整合.
- 针对人工智能在护理学生的考试准备和自我评估中的有效性.
研究的目的:
- 评估ChatGPT在回答护士执照考试准备问题的表现.
- 通过专家审查,分析影响ChatGPT答案准确性和可靠性的因素.
主要方法:
- 采用了横截面调查设计.
- 分析了台湾2022年护士执照考试的400个问题.
- 后勤回归评估了问题特征的影响;人类专家审查了答案的一致性.
主要成果:
- 在护士考试问题上,ChatGPT获得了80.75%的准确率,超过了通过门.
- 根据学科,准确性差异很大,一般医学 (88.75%) 最高,基本护理 (63.0%) 最低.
- 聊天GPT答案和解释之间的不一致 (14.25%) 将整体有效准确率降低到74%.
结论:
- 聊天GPT显示潜在的辅助工具在护理教育,但有局限性.
- 在不同类型的问题上,表现有所不同,临床细节和复杂的多选项问题带来了挑战.
- 在医疗保健中,需要进一步开发更可靠的基于人工智能的教育技术.
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