Large Language Models in Nursing Education: State-of-the-Art.
ChatGPT
Large Language Models
clinical simulation
natural language processing
nursing education
Journal
Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582
Informations de publication
Date de publication:
22 Aug 2024
22 Aug 2024
Historique:
medline:
23
8
2024
pubmed:
23
8
2024
entrez:
23
8
2024
Statut:
ppublish
Résumé
This study explores the integration of Large Language Models (LLMs) into nursing education, highlighting a paradigm shift towards interactive learning environments. We aimed to analyze the literature to identify how large language models are being implemented in nursing education, as well as key opportunities and limitations that need to be addressed. English records published since 2022 were retrieved from 4 databases including LLMs in nursing education. A total of 19 records were eligible. As LLMs advanced natural language processing capabilities enable interactive learning experiences, nursing educators are presented with unique opportunities to enhance curriculum delivery, foster critical thinking, and simulate complex clinical scenarios. Through a comprehensive analysis of current applications, limitations and future research, this paper navigates the complexities of adopting LLMs (eg ChatGPT) in nursing education. This paper concludes with a call for action to advance the integration of AI in nursing, enhancing educational outcomes while ensuring ethical, effective use.
Identifiants
pubmed: 39176964
pii: SHTI240584
doi: 10.3233/SHTI240584
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM