Artificial intelligence in nursing education: A scoping review of intelligent tutoring systems-evidence and implementation gaps.

BACKGROUND: The concept of ITSs is widely implemented across educational settings, but their adoption in nursing education remains poorly understood. OBJECTIVES: To investigate the current state of evidence on ITS in nursing education, identify research gaps and provide recommendations for future research and practice. DESIGN: A scoping review based on the JBI methodology framework. METHODS: A systematic literature search was initiated (between June and October 2025) across several databases (IEEE Xplore, PubMed, MEDLINE, ERIC, ProQuest, ScienceDirect, and Google Scholar). Grey literature sources and websites of key organisations (e.g., NMC, NICE, IHI, NHS) were also searched. There were no date restrictions, but only articles in English were considered. The screening and selection process was based on the extended PRISMA-ScR framework. RESULTS: Initially, 881 records were retrieved, but 9 studies were included in our scoping review and analysed. Our results indicate that research on ITS in nursing remains limited, with most studies presenting incomplete ITS architectures that focus primarily on domain models or standalone concepts. Among the 9 studies, there is limited evidence suggesting considerations of user-needs evaluation, theoretical frameworks, empirical validation, or curricular integration. CONCLUSIONS: Evidence on ITS in nursing education is limited and inconsistent. Our results led to recommendations for future research and practice, including developing a grounded theory of user perspectives, conducting rigorous empirical evaluations, designing and testing comprehensive ITS architectures aligned with nursing education philosophies, and promoting inclusivity by involving underrepresented populations and low-resource settings.