Artificial intelligence in nursing education: A scoping review
Abstract
Aim To explore recent empirical studies on implementation of artificial intelligence in nursing education in hospital settings through the prism of the Strengths, Weaknesses, Opportunities and Threats (SWOT) model.Background In the last decade, artificial intelligence has markedly influenced healthcare and nursing domains, particularly in improving care and educational processes for nursing staff. Despite its ongoing integration in nursing education, an understanding of its impact remained limited.Design Scoping review.Methods A systematic search using PubMed and ScienceDirect databases, following PRISMA guidelines, identified relevant studies. The main inclusion criteria were empirical studies from 2018 onwards and a focus on nursing students/registered nurses in hospital settings. The exclusion criteria were non-empirical documentation such as abstracts, editorials and opinion-related articles, as well as studies in surgical, pediatric, gynecological and mental health nursing.Results In total, 15 articles were selected from a pool of 6517 documents. The aspects mentioned in the employed literature highlighted the positive impact of artificial intelligence on educational experiences, knowledge acquisition and mental safety. Challenges of the artificial intelligence implementation in the nursing education field, such as technical issues, language barriers and limited realistic experience were also identified.Conclusions The findings of the review suggest that artificial intelligence provides significant benefits for nursing education. However, continuous evaluation managing weaknesses and maximizing the educational potential of artificial intelligence in the nursing field is crucial.
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The 18 included studies collectively explored diverse applications of AI in nursing across research, practice, and education.
“The 18 included studies in this umbrella review collectively explored the diverse applications of AI in nursing across research, practice, and education [32-49].”
From The Role of AI in Nursing Education and Practice: Umbrella Review (2025) · cites this paper as [35]
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- Authors
- Lifshits, I., & Rosenberg, D.
- Affiliations
- Hebrew University of Jerusalem (IL)
- ORCID
- Rosenberg, Dennis
- Venue
- Nurse Education in Practice
- Publisher
- Elsevier BV
- Published
- 2024-10
- Volume
- 80
- Pages
- 104148
- ISSN
- 1471-5953 (ISSN-L)
- OpenAlex
- W4403244162
- Cited by
- 121
- References
- 32
- Citations by year
- 2026: 68 · 2025: 51 · 2024: 1 · 2022: 1
- FWCI
- 2.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nurse Education in Practice (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Physiology › Simulation-Based Education in Healthcare
- Keywords
- artificial intelligence, nursing education, hospital-based nursing education, SWOT analysis, implementation barriers, nursing students, registered nurses, knowledge acquisition, technical challenges, language barriers, simulation-based training
- MeSH terms
- Artificial Intelligence, Clinical Competence, Education, Nursing, Education, Nursing, Baccalaureate, Humans, Students, Nursing
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