Mixed-Agent Museum Tour Guide Design Improves Gendered Learning Outcomes and Visitor Preferences
For human-robot interaction and museum design, this work shows that mixed-agent teams can enhance learning for female visitors, addressing gender differences in educational outcomes.
This paper introduces a mixed-agent museum tour guide system combining a physical robot with a projected virtual agent. In a within-subjects study with 30 participants, the system improved learning performance for female participants while maintaining engagement and quality of experience, and was preferred by participants regardless of gender.
Robots are increasingly integrated into everyday contexts, including museums, where they can both entertain and educate visitors. To enhance visitor experience and engagement, we present a novel mixed-agent tour guide system that combines a physical robot with a projected virtual agent that actively participates in the tour through conversation and interaction, achieving the interaction richness of two mobile agents from a single platform. We validate the system through a within-subjects study with 30 participants to assess engagement, quality of experience, and learning performance. Participants experienced different conversational styles and agent configurations, and data were collected via surveys, behavioral sensors, and interviews. Results showed that engagement and quality of experience remained consistent across conditions. Learning performance revealed a significant gender-moderated difference: the mixed-agent conditions improved learning performance for female participants. This suggests that the proposed dyadic conversational style in this paper influenced learning performance differently by gender. Nonetheless, in interviews, participants reported a greater preference for mixed-agent teams regardless of gender, citing interaction as a key factor in their experience.