The Use of Artificial Intelligence in Nursing Education: A Scoping Review.

IF 1.9

The Journal of nursing education Pub Date : 2025-08-01 DOI:10.3928/01484834-20250313-03

Toni Doston, Justin Fontenot, Dawn Morris, Michael Hebert

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Abstract

Background: The application of artificial intelligence (AI) in nursing education is increasingly prevalent, yet there remains a limited understanding of its current state. This scoping review examines how AI tools, large language models, and chatbots are used in nursing education, their effects on educational outcomes, and their challenges.

Method: This review, which adhered to Joanna Briggs Institute guidelines and registered on the Open Science Framework, systematically assessed studies across the following databases: PubMed, PsycINFO, Academic Search Complete, and CINAHL Complete.

Results: Thirty-eight studies met inclusion criteria, highlighting AI's roles in simulation training, predictive analytics, debriefing, tutoring, and curriculum development. Although ethical concerns and limited longitudinal impact data persist, simulation and predictive analytics applications demonstrate promise.

Conclusion: AI has transformative potential in nursing education, particularly for personalized learning and performance prediction. Educators must navigate ethical considerations, and further research is needed to evaluate AI's long-term efficacy and explore how nursing students use AI.

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人工智能在护理教育中的应用：范围综述。

背景：人工智能（AI）在护理教育中的应用越来越普遍，但对其现状的了解仍然有限。本综述探讨了人工智能工具、大型语言模型和聊天机器人如何在护理教育中使用，它们对教育成果的影响以及它们面临的挑战。方法：本综述遵循乔安娜布里格斯研究所的指南，并在开放科学框架上注册，系统地评估了以下数据库中的研究：PubMed、PsycINFO、Academic Search Complete和CINAHL Complete。结果：38项研究符合纳入标准，突出了人工智能在模拟训练、预测分析、汇报、辅导和课程开发方面的作用。尽管伦理问题和有限的纵向影响数据仍然存在，但模拟和预测分析应用显示出前景。结论：人工智能在护理教育中具有变革潜力，特别是在个性化学习和绩效预测方面。教育工作者必须考虑到伦理问题，需要进一步的研究来评估人工智能的长期功效，并探索护理学生如何使用人工智能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Journal of nursing education

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