Eye-Tracking Based Measurement Framework For Quantifying Visual Attention In Screen-Based Interactive Digital Art Environments.

This article presents a gaze-enabled measurement framework designed to quantify visual attention during interactive digital art experiences and to link attention dynamics to experiential outcomes. Unlike traditional static art viewing, interactive digital art involves dynamic media, multi-source information, and continuous feedback loops, which challenge standard eye-tracking methodologies. The proposed system integrates eye-tracking acquisition, interaction logging, timestamp synchronization, dynamic Area of Interest (AOI) mapping, and metric computation into a unified pipeline. The protocol outlines the development of a reproducible data workflow that aligns gaze data with specific interaction events, enabling precise calculations of attention allocation, switching costs, and exploratory entropy. The experimental design involves both free exploration and goal-directed tasks, as demonstrated in a study with 37 participants. Results from applying this protocol indicate high perceived user-friendliness and satisfaction, with measurement modeling supporting a two-construct model of usability and satisfaction. Furthermore, outcome modeling confirms that perceived usability acts as a foundational predictor for overall user satisfaction, while the single-case demonstration validates the pipeline's capacity to quantify context-aware attention shifts. This protocol provides researchers and designers with a rigorous, reproducible toolset for analyzing how interaction design elements-such as feedback latency and guidance intensity-shape user attention and subsequent subjective experiences in immersive digital environments.