From Perception to Decision: Assessing the Role of Chart Types Affordances in High-Level Decision Tasks
Yixuan Li, Emery D. Berger, Minsuk Kahng, Cindy Xiong Bearfield

TL;DR
This study examines whether different chart types, like bar and pie charts, influence high-level decision-making in real-world contexts, finding minimal impact despite known perceptual differences.
Contribution
It highlights the limited influence of chart type on high-level decisions, emphasizing the need to evaluate visualizations in real-world scenarios.
Findings
Minimal decision differences between chart types in real-world tasks
Perceptual affordances may not directly affect high-level decisions
Importance of context-specific visualization evaluation
Abstract
Visualization design influences how people perceive data patterns, yet most research focuses on low-level analytic tasks, such as finding correlations. The extent to which these perceptual affordances translate to high-level decision-making in the real world remains underexplored. Through a case study of academic mentorship selection using bar charts and pie charts, we investigated whether chart types differentially influence how students evaluate faculty research profiles. Our crowdsourced experiment revealed only minimal differences in decision outcomes between chart types, suggesting that perceptual affordances established in controlled analytical tasks may not directly translate to high-level decision scenarios. These findings emphasize the importance of evaluating visualizations within real-world contexts and highlight the need to distinguish between perceptual and decision…
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Taxonomy
TopicsData Visualization and Analytics
