设计用于临床沟通训练的VR仿真系统：基于LLMs的具身对话代理
Designing VR Simulation System for Clinical Communication Training with LLMs-Based Embodied Conversational Agents
AI总结：
本研究通过半结构化访谈获取设计洞察，开发了由LLMs和ECAs驱动的新型VR系统VAPS，支持动态可定制的患者交互，解决临床沟通训练中学习内容固定且缺乏定制化的问题。
摘要：
健康专业（HP）教育中的VR仿真展现出巨大潜力，但固定的学习内容且缺乏定制化限制了其在实验室环境之外的应用。为解决患者沟通训练VR语境中的这些局限，我们开展了一项以用户为中心的研究，对高年级HP学生进行半结构化访谈，以了解他们在临床沟通训练中面临的挑战以及对基于VR解决方案的看法。由此，我们得出了设计洞察，强调真实场景、简单交互和不可预测对话的重要性。基于这些洞察，我们开发了虚拟AI患者模拟器（VAPS），这是一种由大型语言模型（LLMs）和具身对话代理（ECAs）驱动的新型VR系统，支持动态且可定制的患者交互以实现沉浸式学习。我们还提供了一个示例，说明临床教授如何使用用户友好的设计表单在VAPS中创建与课程目标一致的个性化场景，并讨论了将AI驱动技术整合到VR教育中的未来影响。
英文摘要：
VR simulation in Health Professions (HP) education demonstrates huge potential, but fixed learning content with little customization limits its application beyond lab environments. To address these limitations in the context of VR for patient communication training, we conducted a user-centered study involving semi-structured interviews with advanced HP students to understand their challenges in clinical communication training and perceptions of VR-based solutions. From this, we derived design insights emphasizing the importance of realistic scenarios, simple interactions, and unpredictable dialogues. Building on these insights, we developed the Virtual AI Patient Simulator (VAPS), a novel VR system powered by Large Language Models (LLMs) and Embodied Conversational Agents (ECAs), supporting dynamic and customizable patient interactions for immersive learning. We also provided an example of how clinical professors could use user-friendly design forms to create personalized scenarios that align with course objectives in VAPS and discuss future implications of integrating AI-driven technologies into VR education.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
