HAT Swapping: Virtual Agents as Stand-ins for Absent Human Instructors in Virtual Training

Virtual reality (VR) is increasingly adopted for collaborative teaching and learning, enabling immersive and interactive experiences. As Artificial Intelligence (AI) tutors begin to take on roles alongside human instructors, it becomes crucial to understand how their integration influences interaction dynamics and role perception in these settings. This study investigates the role of Embodied Virtual Agents (EVAs) substituting human instructors in virtual training, specifically addressing the previously underexplored issue of EVA appearance consistency with instructors in Human-Agent Teaming (HAT). We recruited 21 participants to compare three conditions: No Agent, Shared-Appearance (SA) EVA, and Unique-Appearance (UA) EVA, where an EVA substitutes for the instructor during temporary absences. We evaluated collaboration efficiency, user perception/preference, and HAT dynamics. Our findings confirm that EVAs significantly enhance task efficiency compared to no support and reveal a key trade-off regarding appearance: SA fosters perceived continuity and trust but risks ambiguity and uncanny effects, while UA provides transparency and role clarity but may disrupt experiential coherence. These results have implications for designing dynamic HAT systems where control may shift. We discuss the benefits and limitations of each approach and offer design recommendations for future mixed-agency interfaces.