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Croissant Charts: Modulating the Performance of Normal Distribution Visualizations with Affordances

Racquel Fygenson, Enrico Bertini, Lace M. Padilla

Abstract

Affordances, originating in psychology, describe how an object's design influences the physical and cognitive actions users may take. Past work applied affordance theory to visualization to explain how design decisions can impact the cognitive actions of visualization readers. In this work, we demonstrate that affordances can complement effectiveness rankings by further explaining the root causes behind visualizations' task performance. To do so, we conduct a case study on static normal probability density function plots, identifying their current affordances. Next, we identify the optimal affordances for a common probability-comparison task and develop a novel affordance-driven visualization, the Croissant Chart, to support them. We empirically validate the design's effectiveness through a preregistered study (n = 808), demonstrating how affordances can inform predictable changes in task performance. Our findings underscore the potential for affordance-based approaches to enhance visualization effectiveness and inform future design decisions.

Croissant Charts: Modulating the Performance of Normal Distribution Visualizations with Affordances

Abstract

Affordances, originating in psychology, describe how an object's design influences the physical and cognitive actions users may take. Past work applied affordance theory to visualization to explain how design decisions can impact the cognitive actions of visualization readers. In this work, we demonstrate that affordances can complement effectiveness rankings by further explaining the root causes behind visualizations' task performance. To do so, we conduct a case study on static normal probability density function plots, identifying their current affordances. Next, we identify the optimal affordances for a common probability-comparison task and develop a novel affordance-driven visualization, the Croissant Chart, to support them. We empirically validate the design's effectiveness through a preregistered study (n = 808), demonstrating how affordances can inform predictable changes in task performance. Our findings underscore the potential for affordance-based approaches to enhance visualization effectiveness and inform future design decisions.

Paper Structure

This paper contains 22 sections, 1 equation, 8 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background
  3. Cognitive affordances in visualization
  4. Probability Density Visualizations
  5. Study Materials and Methods
  6. Affordances of probability density visualizations
  7. An affordance-motivated redesign
  8. Investigative Questions and Hypotheses
  9. Stimuli
  10. Experimental Design
  11. Participants
  12. Procedure
  13. Analysis
  14. Experimental Results
  15. Task Performance: Investigating Hypotheses
  16. ...and 7 more sections

Figures (8)

  • Figure 1: Top: The task we test. Bottom: PDFs' afforded mental actions from our pilot study. Some actions yield correct results for equal-area PDFs (left), but not for equal-height PDFs (right). See Section \ref{['sec:pilot']} for more detail.
  • Figure 2: Why would someone scale PDFs to equal-heights? (a) different variances can cause overlap and occlusion (b) separating them requires more space (c) equal-height scaling yields a compact, statistically correct figure.
  • Figure 3: QDPs' afforded mental actions from our pilot study.
  • Figure 4: Croissant charts' intended affordances. PDF shape for expressiveness. Minimal slices with gaps afford continuity and parts of a whole. Dots afford counting and equality across slices.
  • Figure 5: Stimuli overview. Left: Between-subjects; different visualization techniques (PDF, QDP, Croissant-10, Croissant-20) under two scaling conditions (Equal Area, Equal Height). Right: within-subjects; standard deviation pairs and position variations.
  • ...and 3 more figures