Designing for Wayfinding in VR: Linking Navigation Interfaces to Spatial Learning and Cognitive Mapping

要旨

Various virtual locomotion techniques and visual transition methods are used in VR-based navigation research, yet few studies have systematically examined their effects on spatial learning, cognitive map formation, and navigational performance in complex indoor environments. We conducted a between-subjects study (N=142) in two high-fidelity VR hospital contexts, including free exploration and task-based wayfinding, while treating locomotion and viewpoint transitions as experimental factors. Spatial learning was measured through pointing, distance estimation, and sketch-map accuracy; performance was measured through completion time and distance traveled; and experience was measured through cybersickness, perceived presence, and usability. Locomotion techniques affected task completion time, with teleportation associated with faster performance in the task-based context. Spatial learning effects were mixed, with patterns indicating that techniques without viewpoint transitions may better support cognitive mapping. Empirical insights and guidelines are provided to improve the reliability and real-world applicability of VR-based wayfinding research.

著者
Armin Mostafavi
Cornell University, Ithaca, New York, United States
Zhiwen Qiu
Cornell University, Ithaca, New York, United States
Tong Bill. Xu
Cornell University, Ithaca, New York, United States
Wenqian Niu
Cornell University, Ithaca, New York, United States
Saleh Kalantari
Cornell University, Ithaca, New York, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: XR Navigation

Area 1 + 2 + 3: theatre
7 件の発表
2026-04-15 20:15:00
2026-04-15 21:45:00