Eye-Tracking-Based Evaluation of Visual Search Efficiency in Simulated VR Menu Interfaces: Effects of Card Layout...

Understanding how interface layout influences visual search performance is important for optimizing virtual reality (VR) interfaces. This study investigated visual search efficiency and gaze behavior in simulated VR menu interfaces using a screen-based eye-tracking experiment. To enable controlled measurement of gaze behavior and isolate layout-driven perceptual effects, the interfaces were evaluated using a desktop-based VR simulation. The experiment examined two independent variables: menu layout structure and target spatial quadrant. Two representative VR menu layout structures were compared: a grid-based layout arranged as a 4 × 4 matrix and a gallery-based layout consisting of four large and twelve small cards, forming a size-based visual hierarchy. Target locations were distributed across four spatial quadrants: lower-left, lower-right, upper-left, and upper-right. Participants (N = 39) completed visual search tasks while accuracy (ACC), reaction time (RT), and eye-tracking metrics, including total visit duration (TVD) and total fixation count (TFC), were recorded. The results showed that the gallery-based layout supported more efficient visual search than the grid-based layout, as reflected in shorter RTs, reduced overall TVD, and lower overall TFC. Behavioral and eye-tracking analyses also revealed systematic spatial asymmetries, with the upper-right quadrant showing the fastest responses and reduced gaze-based search effort. Importantly, the advantage of the gallery-based layout was most consistent in the upper-right quadrant, indicating that layout structure and target spatial quadrant jointly shaped visual search efficiency. Gaze-distribution heatmaps provided qualitative visual support for these patterns. These findings provide early-stage perceptual evidence for optimizing layout hierarchy in simulated VR menu interfaces and demonstrate the value of screen-based eye-tracking sensors as quantitative tools for evaluating attentional allocation before further validation in immersive HMD-based VR environments.