## 4 Experimental Design
### Participants and Equipment  
This experiment is based on the eye-tracking data of a single participant with normal vision, enabling a detailed dynamic analysis. While most eye-tracking studies tend to focus  
Figure 10: Visualization of viewing process information—visual selection. Figure 9: (**a**) Distribution of fixation clusters. (**b**) Relationship pathways between AOI pairs. (**c**) Structural connection strength visualization. Different colors are used solely for visual distinction between connection lines. on group-level pattern analysis [88], an in-depth case study of an individual participant holds unique value during the methodological development phase. To strengthen the presentation of the proposed method and to examine its preliminary stability, two additional participants were included in the study, and their data were analyzed using the same computational process. All three participants were graduate students in design from National Yunlin University of Science and Technology, with backgrounds in visual literacy and an interest in art appreciation. The resulting visual structures are presented in Figure 11a-c. While some individual variations in gaze behavior were observed, the overall segmentation, connection layout, and fixation clustering patterns remained highly consistent, suggesting that the proposed framework is replicable and potentially extensible. In addition to eye-tracking data, think-aloud verbal utterances were collected throughout the viewing process. All twenty utterances were initially categorized according to a semantic classification framework developed in our prior study [37], which includes four types: evaluative judgment, spatial context, image-text interaction, and object recognition. Importantly, the selection of segments for detailed analysis was determined by a dual criterion: semantic relevance and noticeable gaze dynamics. Only segments that satisfied both conditions were included, resulting in eight key segments for integrative analysis. Notably, each utterance was temporally aligned with a specific segment of the eye-tracking data, allowing time to serve as the binding element connecting linguistic and visual streams. This temporal alignment ensured that the multimodal analysis was anchored in precise gaze-verbal correspondence. The study employs the ET vision eye-tracking system by Argus Science, a lightweight (56 g) wearable binocular tracking device that accommodates participants who wear glasses. ET vision features a high refresh rate of 180 Hz and a dual-eye accuracy of 0.5\({}^{\circ}\), allowing for precise tracking of gaze movements. The system is equipped with a 720 p high-resolution scene camera and includes an automatic dual-eye orientation correction function. Additionally, the system supports single-point or multi-point calibration options, provides real-time left and right eye movement data visualization, and features network connectivity for external devices. These attributes collectively ensure both participant comfort and the reliability of the experimental data. Figure 11: (**a**) Distribution of fixation clusters. (**b**) Relationship pathways. (**c**) Structural connection strength. Experimental Setting  
Before the experiment began, the participant familiarized themselves with the display space and experimental procedures. The wireless eye-tracking device was then worn, and ETVision was activated to capture binocular pupil images. Chinese landscape paintings were selected as the viewing material in this study due to their unique artistic expression, which elicits rich visual exploration behaviors [37]. Compared to Western artworks, Chinese landscape paintings adopt a more scattered perspective and layered spatial composition, which guide viewers to generate diverse browsing trajectories rather than forming concentrated fixation points [37]. This visual exploration pattern is particularly well suited for studying the relational connections between fixation blocks.