TY - GEN
T1 - Visual Engagement in Immersive VR
T2 - 9th International Conference on Computer-Human Interaction Research and Applications, CHIRA 2025
AU - Lopez-Ozieblo, Renia
AU - Shen, Daniel
AU - Nurgissayeva, Aru
AU - Lam, Gibson
AU - Gonzales, Wilkinson Daniel Wong
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026/5
Y1 - 2026/5
N2 - Immersive Virtual Reality (VR) environments create new opportunities for interactive learning by integrating embodied control, real-time feedback, and spatial attention. To understand how learners engage with these environments, we use gaze-ray casting—a lightweight proxy for attention based on headset orientation—to examine how visual focus on avatar gestures shapes task behaviour and perceived system interactivity. Our findings show that gaze predicted system interaction (β=0.726,R2=0.61), but this effect only enhanced presence for learners with high technological efficiency (interaction β=0.59). Crucially, gaze only predicted task activity when the UI overlays did not compete with avatar gestures. When interface elements occluded gesture space, gaze engagement dropped, and presence declined. Nonlinear analyses also revealed a tipping point: when both gaze and efficacy were high, dizziness reports spiked, an overload pattern missed in linear models. These results suggest that gaze-based engagement fosters immersion only when learners can fluently interpret system cues. Without adaptive support, active users may encounter strain rather than flow. Gaze-ray data, thus, offer a scalable diagnostic for detecting alignment, or friction, between learner attention and system design. Designing for immersive learning requires synchronising visual demands with user confidence and capacity, ensuring that interaction remains a source of motivation, not disruption.
AB - Immersive Virtual Reality (VR) environments create new opportunities for interactive learning by integrating embodied control, real-time feedback, and spatial attention. To understand how learners engage with these environments, we use gaze-ray casting—a lightweight proxy for attention based on headset orientation—to examine how visual focus on avatar gestures shapes task behaviour and perceived system interactivity. Our findings show that gaze predicted system interaction (β=0.726,R2=0.61), but this effect only enhanced presence for learners with high technological efficiency (interaction β=0.59). Crucially, gaze only predicted task activity when the UI overlays did not compete with avatar gestures. When interface elements occluded gesture space, gaze engagement dropped, and presence declined. Nonlinear analyses also revealed a tipping point: when both gaze and efficacy were high, dizziness reports spiked, an overload pattern missed in linear models. These results suggest that gaze-based engagement fosters immersion only when learners can fluently interpret system cues. Without adaptive support, active users may encounter strain rather than flow. Gaze-ray data, thus, offer a scalable diagnostic for detecting alignment, or friction, between learner attention and system design. Designing for immersive learning requires synchronising visual demands with user confidence and capacity, ensuring that interaction remains a source of motivation, not disruption.
KW - Eye-gaze tracking
KW - Presence
KW - Virtual reality
UR - https://www.scopus.com/pages/publications/105040532443
U2 - 10.1007/978-3-032-16448-3_8
DO - 10.1007/978-3-032-16448-3_8
M3 - Conference article published in proceeding or book
AN - SCOPUS:105040532443
SN - 9783032164476
T3 - Communications in Computer and Information Science
SP - 134
EP - 151
BT - Computer-Human Interaction Research and Applications - 9th International Conference, CHIRA 2025, Proceedings
A2 - Krems, Josef F.
A2 - da Silva, Hugo Plácido
A2 - Cipresso, Pietro
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 20 October 2025 through 21 October 2025
ER -