@inproceedings{6bbb8862d2984105bce977985e2de018,
title = "Does AI's Personality Matter? Comparing Verbally Extraverted and Introverted AI-Driven Guides in a VR Museum Experience",
abstract = "Large language models (LLMs) can compliment cultural heritage learning within personalized guided virtual tours. This research explores agent traits that embed personality types, specifically verbal extraversion, to examine their impact on users' experience. Utilizing a VR museum of Chinese bronze chime bells as the experimental platform, the study employs systematic linguistic modulation to vary the AI guide's personality while maintaining visual and technical consistency. Through a between-subjects experiment (N=30), we analyzed how these personality-driven traits shape psychological immersion and knowledge acquisition. Our findings reveal critical trade-offs between guidance styles, demonstrating that extraverted traits significantly foster emotional resonance and active participation. This work extends agent design theory into the VR domain, providing an actionable design strategies for personality-embedded AI guides in cultural education.",
keywords = "Cultural Heritage Learning, Embodied AI Agents, Extraversion, Social Presence, Virtual Reality",
author = "Yuhan Ji and Eugene Ch'ng and Dingtao Huang and Qiaoyu Hu and Yancheng Peng",
note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2026 ; Conference date: 21-03-2026 Through 25-03-2026",
year = "2026",
doi = "10.1109/VRW70859.2026.00009",
language = "English",
series = "Proceedings - 2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2026",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "10--16",
booktitle = "Proceedings - 2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2026",
address = "United States",
}