Divided Attention Amplifies the Importance of Expectation-Aligned Visualization Design

2026-08-10

AI Summary

This study addresses a critical gap in visualization research by examining how divided attention in real-world multitasking scenarios affects users’ interpretation of visualizations—contrary to the prevailing single-task assumption in existing literature. Through two behavioral experiments integrated with the Linear Ballistic Accumulator (LBA) cognitive model, the work systematically compares user performance under single- and dual-task conditions when interpreting visual designs that either align with or violate viewer expectations (e.g., in color schemes or spatial-semantic mappings). The findings reveal, for the first time, that distraction significantly amplifies the impact of expectation consistency on response times, accuracy, and time-constrained judgment capabilities. These results underscore the crucial importance of expectation-aligned design in authentic multitasking contexts and demonstrate how process-oriented computational modeling can elucidate the underlying cognitive mechanisms.

Abstract

Studies have shown that visualization design affects interpretability when visualization interpretation is the user's sole task. However, in real-world settings, users often engage with visualizations while performing concurrent tasks, such as when users simultaneously monitor alerts or respond to messages. Such divided attention may alter how users interpret visualizations, potentially increasing the importance of designs that align with viewer expectations. We investigated this possibility through two experiments comparing visualization interpretation under single-task and dual-task conditions. Specifically, we examined how well-established inferred mappings between color, spatial position, and semantic concepts affect interpretation when users perform a concurrent task, both with unlimited viewing time (Exp. 1) and under limited viewing time (Exp. 2). Our results show that divided attention amplifies the performance gap between expectation-aligned and expectation-violating designs, affecting response time, interpretation accuracy, and the ability to produce a judgment under time constraints. To explain these results, we model the user's decision-making process using a Linear Ballistic Accumulator (LBA) framework. Our findings highlight the increased importance of aligning visualization designs with viewer expectations under divided attention and introduce a process-oriented modeling approach to understanding how expectation and multitasking shape visualization interpretation.

Problem

• divided attention
• visualization design
• expectation alignment
• interpretation accuracy
• multitasking

Innovation

• divided attention
• expectation-aligned design
• visualization interpretation
• Linear Ballistic Accumulator
• dual-task paradigm