Experiences of Multiperspective Text-Based Debriefing Using Generative Artificial Intelligence for Nursing (GAIN) in...

The use of generative artificial intelligence in nursing simulation debriefing is an emerging approach; however, evidence on its educational value remains limited. This study aimed to explore learners' experiences with multiperspective debriefing incorporating text-based generative artificial intelligence in nursing education. A qualitative study was conducted with 12 third-year nursing students recruited through purposive sampling in South Korea. The multiperspective debriefing approach integrated face-to-face, instructor-led, text-based, generative artificial intelligence-assisted, and self-debriefing strategies. A qualitative content analysis following Elo and Kyngäs' approach was conducted to identify categories reflecting learners' experiences. Five categories emerged: "Comparison with face-to-face debriefing," "Learning environment and interaction," "Advantages," "Limitations and improvements," and "Competencies to be enhanced." Learners demonstrated improved competencies in error recognition, information seeking, communication, and empathy, though concerns remained regarding accuracy and depth of reflection. A multiperspective framework leveraging the complementary strengths of instructor-led, text-based generative artificial intelligence, and self-debriefing can support effective reflection. Clear prompt strategies and practical guidelines are needed to ensure high-quality debriefing in resource-limited settings.