汇报
奇纳
心理信息
转化式学习
护士教育
心理学
课程
梅德林
包裹体(矿物)
学习分析
医学教育
护理部
计算机科学
医学
数据科学
教育学
心理干预
社会心理学
政治学
法学
作者
Toni Doston,Justin Fontenot,Dawn Morris,Michael Hebert
标识
DOI:10.3928/01484834-20250313-03
摘要
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. 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. 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. 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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