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Updated: Jun 10, 2025

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Using Learning Outcome Measures to assess Doctoral Nursing Education
Published on: June 21, 2010
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人工智能生成与学生制作的作业以及对评估学生在护理工作的含义:一个探索性的反思
Kateryna Metersky1, Kaveenaa Chandrasekaran1, Rezwana Rahman1
1Daphne Cockwell School of Nursing, Toronto Metropolitan University, Toronto, ON, Canada.
International journal of nursing education scholarship
|October 14, 2024
概括
护理教育工作者可以通过识别过时的引用和ChatGPT-3.5任务中缺乏深度来识别人工智能生成的内容. 了解人工智能能力对于保持护理教育学术诚信至关重要.
科学领域:
- 教育中的人工智能
- 在护理学中的学术诚信.
背景情况:
- 像ChatGPT (聊天生成预训练变压器) 这样的先进AI语言模型的出现对护理教育的学术完整性提出了挑战.
- 学生可以利用AI工具来生成作业内容,需要检测方法.
研究的目的:
- 探索和确定有效的策略,以帮助护理教育工作者区分人工智能生成和学生撰写的学术提交.
- 解决有关人工智能在护理教育中的使用及其对学习的影响的担忧.
主要方法:
- 四名护士学生被指示制作两种版本的"写给编辑的信"作业.
- 一个版本是学生写的,而另一个版本则是 ChatGPT-3.5.5 独家生成的.
主要成果:
- 人工智能生成的作业表现出强大的语法,但往往包含过时,不准确或伪造的学术参考.
- 与学生工作相比,ChatGPT-3.5生成的提交通常缺乏预期的细节和深度.
结论:
- 护理教育工作者需要对像ChatGPT这样的AI技术有基本的了解,以促进学生的知识发展.
- 实施识别人工智能生成内容的策略对于维护护护理课程的学术完整性至关重要.
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