Exploring LLM-Powered Role and Action-Switching Pedagogical Agents for History Education in Virtual Reality
Zihao Zhu, Ao Yu, Xin Tong, and Pan Hui

TL;DR
This study develops and evaluates a VR-based history education system with LLM-powered adaptive role and action switching, enhancing social presence and perceived expertise, and providing design insights for future educational tools.
Contribution
Introduces a novel VR pedagogical agent system with adaptive role and action switching powered by LLMs, and empirically evaluates its effects on learning experience.
Findings
Adaptive role-switching improves perceived trustworthiness and expertise.
Adaptive action-switching increases social presence, humanness, and perceived expertise.
No significant effects on usability, motivation, or cognitive load.
Abstract
Multi-role pedagogical agents can create engaging and immersive learning experiences, helping learners better understand knowledge in history learning. However, existing pedagogical agents often struggle with multi-role interactions due to complex controls, limited feedback forms, and difficulty dynamically adapting to user inputs. In this study, we developed a VR prototype with LLM-powered adaptive role-switching and action-switching pedagogical agents to help users learn about the history of the Pavilion of Prince Teng. A 2 x 2 between-subjects study was conducted with 84 participants to assess how adaptive role-switching and action-switching affect participants' learning outcomes and experiences. The results suggest that adaptive role-switching enhances participants' perception of the pedagogical agent's trustworthiness and expertise but may lead to inconsistent learning experiences.…
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Taxonomy
TopicsInnovative Educational Techniques · Simulation and Modeling Applications · Virtual Reality Applications and Impacts
