Eye-Tracking Evaluation of User Focus on Color-Coded Elements in Yi Graphics

Color-coded elements are commonly integrated into data visualizations to enhance clarity, direct user attention, and highlight critical information. This study examines the effectiveness of color coding in Yi Graphics, focusing on how different color applications influence user attention, perception, and cognitive load during data interpretation. Using eye-tracking technology, gaze patterns of 40 participants were recorded as they interacted with 10 Yi Graphics that displayed the same dataset through various formats, including bar charts, scatter plots, and line graphs. The study aimed to identify which color-coded elements attract the most attention, determine how color coding supports data comprehension, and assess the cognitive load experienced during visual processing. Results showed that color coding increased user attention toward key data points, although participants spent more time analyzing color-coded elements. Heatmaps and gaze plots indicated that warmer colors drew greater visual focus, particularly in simpler visualizations such as bar charts. Cognitive load was higher in complex formats like scatter plots, which affected accurate interpretation. Cultural differences also emerged: Western participants focused more on high-value points, while Eastern participants exhibited a more holistic viewing pattern. The study emphasizes the importance of thoughtful color usage to minimize user strain and improve interpretation. It also highlights the need for culturally adaptive color schemes, color-blind-friendly designs, and further research on interactive features to enhance accessibility. Overall, the findings present practical implications for improving color-based data visualization and guiding future design strategies across disciplines

Bar chart · Cognition · Cognitive Load · Color-coding · Eye tracking · Gaze · Graphics · Visualization · Data Visualization and Analytics · Gaze Tracking and Assistive Technology · Visual and Cognitive Learning Processes