使用逆向工程技术生成多选题
Sujin Shin1, Jaehwa Choi2, Eunmin Hong3
1College of Nursing, Ewha Womans University, Seoul, Republic of Korea.
Medical education online
|January 9, 2026
概括
聊天GPT-4可以使用逆向工程创建护理教育多选择题. 人工智能产生的问题在很大程度上遵循项目开发原则,作为教育工作者有价值的草稿.
科学领域:
- 护理教育 护理教育
- 教育中的人工智能
背景情况:
- 传统的多项选择题 (MCQ) 开发是耗时的.
- 探索像ChatGPT-4这样的AI工具,以有效创建教育内容至关重要.
研究的目的:
- 评估ChatGPT-4在使用逆向工程生成护理教育的MCQ的能力.
- 评估人工智能生成的MCQ是否符合已确定的项目开发原则.
主要方法:
- 评估了ChatGPT-4的护理知识.
- 20个逆向工程提示被用来生成60个MCQ.
- 五位护理教育专家审查了人工智能生成的MCQ,以符合原则.
主要成果:
- 聊天GPT-4在医疗外科护理问题上取得了98%的准确性.
- 人工智能生成的MCQ平均达到7.90/9.00 符合项目开发原则.
- "问题干应该只使用关键词或短语"这一原则是最不遵守的.
结论:
- 聊天GPT-4是一个有价值的工具,用于起草护理教育材料,特别是MCQs.
- 反向工程技术和专家审查提高了人工智能生成的问题质量.
- 教师可以通过提供结构化的提示和示例来改善AI输出.
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