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 affordances when developing visualization guidelines.
@article{arxiv.2410.04686,
title = {From Perception to Decision: Assessing the Role of Chart Types Affordances in High-Level Decision Tasks},
author = {Yixuan Li and Emery D. Berger and Minsuk Kahng and Cindy Xiong Bearfield},
journal= {arXiv preprint arXiv:2410.04686},
year = {2025}
}