MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education

MedGame transforms static clinical cases into structured, executable storytelling games for medical education, moving beyond the localized question-answering and single-turn feedback that characterize most LLM medical-training systems. It uses a dual-engine design: a Medical Narrative Designer synthesizes case-grounded clinical storylines with states and decision nodes, while a Story Director converts them into dependency-aware multimodal orchestration plans rendered by an interactive platform. The authors release MedGame Bench, a 5,000-case benchmark and evaluation protocol for Medical Narrative Generation and Story Direction; task-specific fine-tuning substantially improves open-source LLMs and narrows the gap with commercial models. A pilot student study finds learners perceive MedGame as more engaging and useful than text-only alternatives, extending decision-centered, immersive approaches seen in Multimodal AI Tutoring and Intelligent Tutoring. Its use of Generative AI for scenario authoring connects to LLM Tts Dialogue Lesson Generation, and the engagement gains speak to engagement-metrics as a design target in professional training.

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Wu, Zhou, Ma, Chen, Gao, Lin, Wu, Gou, Liu, Lau & Dou (2026). MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education. arXiv:2607.21570. arXiv preprint (cs.CL).