Integration of Artificial Intelligence in Nursing Simulation Education
Maggie Mee Kie Chan, Abraham Wai Him Wan, Daphne Sze Ki Cheung, Edmond Pui Hang Choi, Engle Angela Chan, Janelle Yorke, Lizhen Wang
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.