LLM vs. Human Driven Conversation: A User Study in Virtual Reality Medical Simulation - Ferreira, Wesley Ferreira De; Negrão, Matheus D.; Maciel, Anderson; Torchelsen, Rafael Piccin; Nedel, Luciana (Anais do Simpósio de Realidade Virtual e Aumentada (SVR); 2025: Anais do XXVII Simpósio de Realidade Virtual e Aumentada, 2025)
Virtual humans are an important area of study in human-computer interaction, where artificial intelligence-driven agents have gained prominence with the emergence of large language models (LLMs). This work explores users’ preferences in conversations produced either by a large language model or by a human in a synthesized voice conversation. To address this question, we developed a scenario within a medical learning simulator. There, the LLM and a human participant alternately simulate the role of a patient in the medical scenario while the subject user takes the role of the doctor. We conducted a user experiment with a relevant population to assess the use of AI agents in realistic training environments, focusing on user perceptions of realism, empathy, and utility. The findings suggest that LLM-based virtual patients hold strong potential for scalable clinical training, but improvements in expressiveness and interaction flow are essential for broader adoption.