Exposing Movement Correlates of Presence Experience in Virtual Reality Using Parametric Maps

Genuine experiences where users feel a deep level of connection are the key quality of room-scale virtual reality (VR). The freedom to move promises natural sensory experiences stimulating a feeling of presence. However, users differ in their eagerness to move, some prefer movement by teleportation while others would keep walking forever. Such individual differences challenge the inclusive design necessary for bestseller applications. In this methodological research contribution, we propose to study user behavior and experience using parametric maps based on general linear models (GLM) to overcome limitations of traditional data aggregation techniques. In the investigated study, participants explored invisible mazes touching hidden walls for brief moments of visual guidance. We demonstrate that experienced presence correlated with where participants spent time exploring the VR. We found an increase in presence coinciding with participants being less likely to collide with invisible walls and spending more time in segments critical for navigational success.