An Agentic AI Framework for Training General Practitioner Student Skills

• URL: http://arxiv.org/abs/2512.18440v1
• Date: Sat, 20 Dec 2025 17:26:39 GMT
• Title: An Agentic AI Framework for Training General Practitioner Student Skills
• Authors: Victor De Marez, Jens Van Nooten, Luna De Bruyne, Walter Daelemans,
• Abstract summary: We introduce an agentic framework for training general practitioner student skills that unifies, evidence-based vignette generation, controlled persona-driven patient dialogue, and standards-based assessment and feedback.<n> participants reported realistic and vignette-faithful dialogue, appropriate difficulty calibration, a stable personality signal, and highly useful example-rich feedback.<n>These results support agentic separation of scenario control, interaction control, and standards-based assessment as a practical pattern for building dependable and pedagogically valuable training tools.
• Score: 1.8865968025608468
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Advancements in large language models offer strong potential for enhancing virtual simulated patients (VSPs) in medical education by providing scalable alternatives to resource-intensive traditional methods. However, current VSPs often struggle with medical accuracy, consistent roleplaying, scenario generation for VSP use, and educationally structured feedback. We introduce an agentic framework for training general practitioner student skills that unifies (i) configurable, evidence-based vignette generation, (ii) controlled persona-driven patient dialogue with optional retrieval grounding, and (iii) standards-based assessment and feedback for both communication and clinical reasoning. We instantiate the framework in an interactive spoken consultation setting and evaluate it with medical students ($\mathbf{N{=}14}$). Participants reported realistic and vignette-faithful dialogue, appropriate difficulty calibration, a stable personality signal, and highly useful example-rich feedback, alongside excellent overall usability. These results support agentic separation of scenario control, interaction control, and standards-based assessment as a practical pattern for building dependable and pedagogically valuable VSP training tools.

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