Large Language Models in Nursing Education: State-of-the-Art.


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
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

Pagination

1024-1028

Auteurs

Daniel Rodrigues (D)

Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal.
VirtualCare, Portugal.

Ricardo Cruz-Correia (R)

Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal.
VirtualCare, Portugal.

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Classifications MeSH