护士教育中的大型语言模型:最先进的技术状态
Daniel Rodrigues1,2, Ricardo Cruz-Correia1,2
1Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal.
Studies in health technology and informatics
|August 23, 2024
概括
大型语言模型 (LLM) 通过实现交互式学习来改变护理教育. 本研究分析了在护理中的LLM应用,机遇和挑战,以指导道德和有效的整合.
科学领域:
- 护理教育 护理教育
- 人工智能的人工智能
- 教育技术的教育技术
背景情况:
- 像大型语言模型 (LLM) 这样的先进人工智能工具的整合正在重塑教育范式.
- 护理教育面临着对创新的教学方法的不断变化的需求,以准备未来的医疗保健专业人员.
研究的目的:
- 系统地审查和分析当前关于在护理教育中实施大型语言模型的文献.
- 确定与在护理课程中采用LLM相关的关键机会和局限性.
- 为教育工作者和研究人员提供有关利用人工智能提高护理教育的见解.
主要方法:
- 在四个数据库中对2022年以来出版的英语记录进行了系统的文献搜索.
- 关键词包括"大型语言模型"和"护理教育".
- 总共有19个相关记录被确定和分析.
主要成果:
- LLM提供了通过互动学习,批判性思维发展和临床场景模拟来增强护理教育的重要机会.
- 确定的应用包括课程增强和个性化学习体验.
- 还指出了采用关键的局限性和挑战,需要仔细考虑.
结论:
- 法律学士课程代表了护理教育的范式转变,为交互式和有效的学习提供了强大的工具.
- 需要进一步的研究和战略实施,以最大限度地提高收益,同时应对道德和实际挑战.
- 建议采取行动,以促进人工智能在护理教育中的整合,以获得更好的结果.
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