Why Combining Text and Visualization Could Improve Bayesian Reasoning: A Cognitive Load Perspective

TL;DR

This study investigates how combining text and visualization, specifically icon arrays, can enhance Bayesian reasoning by reducing cognitive load, especially for individuals with low working memory capacity, thereby improving accuracy and reducing effort.

Contribution

The paper provides empirical evidence that combining text and icon arrays reduces cognitive load and improves Bayesian reasoning accuracy for individuals with low working memory capacity.

Findings

Icon arrays decrease errors in Bayesian reasoning for low working memory individuals.

Visualization reduces subjective workload compared to text-only presentations.

Individuals with higher working memory capacity show less benefit from visualization.

Abstract

Investigations into using visualization to improve Bayesian reasoning and advance risk communication have produced mixed results, suggesting that cognitive ability might affect how users perform with different presentation formats. Our work examines the cognitive load elicited when solving Bayesian problems using icon arrays, text, and a juxtaposition of text and icon arrays. We used a three-pronged approach to capture a nuanced picture of cognitive demand and measure differences in working memory capacity, performance under divided attention using a dual-task paradigm, and subjective ratings of self-reported effort. We found that individuals with low working memory capacity made fewer errors and experienced less subjective workload when the problem contained an icon array compared to text alone, showing that visualization improves accuracy while exerting less cognitive demand. We believe these findings can considerably impact accessible risk communication, especially for individuals with low working memory capacity.