Silent teachers: Narratives from the simulation lab

沉默的教师:来自模拟实验室的叙述

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Abstract

INTRODUCTION: Patient mannequins are ubiquitous in simulation-based medical education, yet their own 'stories' remain untold. This paper adopts a playful, phenomenological lens, amplified by artificial intelligence (AI), to explore the fictional 'lived experiences' of these silent teachers and reflect on their pedagogical significance. METHODS: Fictional narratives were generated for three representative mannequins - Mr. Heart Attack, Mrs. Difficult Birth and a composite 'Geriatric Triplet' representing common geriatric syndromes - using a large language model (ChatGPT 4.0). These narratives were analysed using qualitative methods (narrative inquiry, phenomenology, content analysis) to explore their 'experiences' and pedagogical roles. RESULTS: The AI-generated narratives depicted mannequins possessing distinct 'personalities' and reflections on their roles (e.g., Mr. Heart Attack's resignation, the Triplets' patience). They highlighted key learning opportunities, such as managing clinical uncertainty (Mr. Heart Attack), holistic care (Triplets) and navigating high-stakes emotional scenarios (Mrs. Difficult Birth). Themes emerged around clinical decision-making, teamwork, communication and empathy. CONCLUSION: This playful yet reflective study highlights mannequins as more than inert tools, using their AI-generated 'voices' to underscore key simulation principles. It also demonstrates a novel methodological approach, prompting reflection on narrative, perspective and the potential roles of AI in shaping educational discourse.

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