Enhancing simulation facilitator debriefing using a generative artificial intelligence feedback interface and retrieval-augmented generation: A pilot study
Year: 2025
Type: article
Abstract: Background High quality simulation requires a skilled educator well-versed in the simulation standards of best practice including facilitation methods and debriefing. While current approaches such as coaching and mentoring have demonstrated effectiveness, they can be time and resource intensive, potentially limiting their scalability and consistent application. Strategies are needed that improve capacity to support ongoing skill advancement. Generative artificial intelligence (GAI) may offer a promising avenue to support the ongoing development of facilitator debriefing skills. Our investigative team developed a homegrown GAI chatbot designed to enhance the quality of feedback facilitators receive on their debriefing practices. Methods This pilot study evaluated the feasibility and usability of the chatbot among simulation facilitators ( n = 6) using a post-test survey design. Results Developing a chatbot to analyze facilitator debriefing skills and provide evidence-informed, personalized feedback was feasible. Facilitators reported that the chatbot was both useful and easy to use. Conclusion Our chatbot may be an impactful evidence-informed GAI educational tool tailored to the specific needs of healthcare simulation facilitation. Leveraging GAI tools may enhance consistent ongoing facilitator debriefing development using a data driven approach.
Source: Clinical Simulation in Nursing
Authors: Jacqueline Vaughn, Shannon H. Ford, Alexander Sheckells, Hunter Fasnacht, Donald Crawford, Gulustan Dogan
Institution: University of North Carolina Wilmington
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
SDG: Quality education
Open Access status: hybrid
Estimated APC paid: $3,210
OpenAlex ID: W4415664057