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Integration of Artificial Intelligence in Nursing Simulation Education: A Scoping Review
Abstract
BACKGROUND: Artificial intelligence (AI) integration in nursing simulation education is growing, yet understanding its implementation across simulation phases remains limited. PURPOSE: To map AI applications across prebriefing, simulation, and debriefing phases in nursing simulation education. METHODS: Following Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines, we searched PubMed, CINAHL Complete, EMBASE, Scopus, and Web of Science (2015-2024) using terms related to nursing students, simulation, and artificial intelligence Studies were included if they involved prelicensure nursing students, AI-integrated nursing simulation education, and were peer-reviewed English publications. Data were charted using the population, concept, context framework. RESULTS: Analysis of 14 articles revealed AI applications in prebriefing (chatbots; n = 2), simulation (virtual environments; n = 11), and debriefing (feedback; n = 1). Benefits included standardization and personalized learning, while challenges involved technical limitations and faculty readiness. CONCLUSIONS: AI shows potential in enhancing nursing simulation education through standardized learning experiences but requires structured faculty support and evaluation methods.
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“That review identified barriers to the implementation of AI simulations, including system instability, inaccurate speech recognition, and a lack of structured training for instructors.”
From AI-Powered Simulation for Nursing Education: Mixed Methods Systematic Review (2026) · cites this paper as [65]
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PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
Tricco, A. C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., et al. (2018) · Annals of Internal Medicine · doi:10.7326/m18-0850 · Cited by 43,565
Virtual simulation in nursing education: a systematic review spanning 1996 to 2018
Foronda, C. L., Fernandez-Burgos, M., Nadeau, C., Kelley, C. N., & Henry, M. N. (2020) · Simulation in Healthcare The Journal of the Society for Simulation in Healthcare · doi:10.1097/sih.0000000000000411 · Cited by 505
Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review
Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2021) · JMIR Nursing · doi:10.2196/23933 · Cited by 326
Liaw, S. Y., Tan, J. Z., Lim, S., Zhou, W., Yap, J., Ratan, R., Ooi, S. L., Wong, S. J., Seah, B., & Chua, W. L. (2023) · Nurse Education Today · doi:10.1016/j.nedt.2023.105718 · Cited by 223
Communication skills training using virtual reality: a descriptive qualitative study
Shorey, S., Ang, E., Ng, E. D., Yap, J., Lau, L. S. T., & Chui, C. K. (2020) · Nurse Education Today · doi:10.1016/j.nedt.2020.104592 · Cited by 152
Liaw, S. Y., Tan, J. Z., Bin Rusli, K. D., Ratan, R., Zhou, W., Lim, S., Lau, T. C., Seah, B., & Chua, W. L. (2023) · Journal of Medical Internet Research · doi:10.2196/47748 · Cited by 87
Chen, Y., Lin, Q., Chen, X., Liu, T., Ke, Q., Yang, Q., Guan, B., & Ming, W.-K. (2023) · Digital Health · doi:10.1177/20552076231185435 · Cited by 24
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Cited by
Sorted by citations
El-Banna, M. M., Sajid, M. R., Rizvi, M. R., Sami, W., & McNelis, A. M. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1681784 · Cited by 62
AI-Powered Simulation for Nursing Education: Mixed Methods Systematic Review
Jiang, H., Wang, Z., Shen, W., Meng, M., Yang, D., Li, X., & Hao, Y. (2026) · Journal of Medical Internet Research · doi:10.2196/95167 · Cited by 4
Kor, P. P. K., Chan, K., Tsang, A. P. L., Liu, J. Y. W., Cheung, K., Lai, K. H., Cheung, E. S. P., Tan, L. H. Z., & He, H. C. (2026) · Nurse Education Today · doi:10.1016/j.nedt.2026.107275
Metadata
- Authors
- Chan, M. M. K., Wan, A. W. H., Cheung, D. S. K., Choi, E. P. H., Chan, E. A., Yorke, J., & Wang, L.
- Affiliations
- Hong Kong Polytechnic University (HK)
- Deakin University (AU)
- ORCID
- Venue
- Nurse Educator
- Published
- 2025-04-01
- Volume
- 50
- Issue
- 4
- Pages
- 195-200
- ISSN
- 0363-3624 (ISSN-L)
- 1538-9855
- OpenAlex
- W4409118705
- Cited by
- 56
- References
- 7
- Citations by year
- 2026: 45 · 2025: 11
- FWCI
- 36.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nurse Educator (publishedVersion)
- PubMed (publishedVersion)
- Figshare (acceptedVersion)
- Topics
- Social Sciences › Education › Simulation-Based Education in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Surgery › Surgical Simulation and Training
- Keywords
- artificial intelligence, prebriefing, debriefing, chatbots, virtual worlds, simulation-based training, prelicensure nursing students, personalized learning, faculty readiness, simulation feedback
- MeSH terms
- Simulation Training, Artificial Intelligence, Education, Nursing, Education, Nursing, Baccalaureate, Humans, Students, Nursing, Nursing Education Research
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- The paper
- Chan, M. M. K., Wan, A. W. H., Cheung, D. S. K., Choi, E. P. H., Chan, E. A., Yorke, J., & Wang, L. (2025). Integration of Artificial Intelligence in Nursing Simulation Education: A Scoping Review. Nurse Educator. https://doi.org/10.1097/nne.0000000000001851
