IEEE VIS 2025 Content: From Perception to Decision: Assessing the Role of Chart Type Affordances in High-Level Decision Tasks

From Perception to Decision: Assessing the Role of Chart Type Affordances in High-Level Decision Tasks

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 Yixuan Li -

 Emery Berger -

 Minsuk Kahng -

 Cindy Xiong Bearfield -

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Image not found — Practitioners such as data visualization designers and user experience designers would be most interested in this paper, as it provides insights into how different chart types influence high-level decision-making, which they can apply to design visualizations that are not only perceptually effective but also decision-aware in real-world contexts.

Keywords

Visual Affordances, Decision-Making, Perception

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 affordances when developing visualization guidelines.