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Artificial intelligence to support debriefing in simulation-based healthcare education: a scoping review
Aseelah Alnazawi1,2, Mohammed Almarhabi3,4
1Jeddah Clinical Skills and Simulation Center, College of Medicine, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), King Abdulaziz Medical City, Jeddah, Saudi Arabia. aseelah.alnazawi@kcl.ac.uk.
Background:
Artificial intelligence is increasingly being integrated into healthcare education and simulation-based education. However, its role in supporting the debriefing phase of simulation remains underexplored and inconsistently described. This scoping review aimed to map the existing literature on the use of artificial intelligence to support debriefing in simulation-based healthcare education.
Methods:
A scoping review was conducted in accordance with Arksey and O'Malley's framework and Joanna Briggs Institute guidance and reported in line with PRISMA-ScR. MEDLINE, Scopus, Web of Science, and CINAHL were searched without date restrictions. Eligible studies examined the use of artificial intelligence to support debriefing-related processes within healthcare simulation. Data were charted using a structured extraction form and synthesised descriptively and thematically.
Results:
Seven studies published between 2023 and 2026 met the inclusion criteria. Studies were conducted in the United States, Switzerland, Chile, and South Korea. Artificial intelligence applications clustered into three domains: communication and performance analytics using speech recognition and natural language processing; generative artificial intelligence systems supporting facilitator feedback and structured report generation; and learner-facing reflective dialogue systems. Across the included studies, artificial intelligence was mainly positioned as an adjunct to human facilitation rather than as a replacement for facilitators. Reported outcomes focused primarily on feasibility, usability, technical accuracy, and perceived educational value, with limited evidence of objective improvements in learner performance or clinical outcomes.
Conclusions:
Artificial intelligence is emerging as a supportive tool for debriefing in simulation-based healthcare education. Current evidence remains limited, exploratory, and largely single-institutional, indicating the need for more rigorous research on educational effectiveness, ethical implementation, and the continuing role of human facilitation.