Divided Attention Amplifies the Importance of Expectation-Aligned Visualization Design

Authors

Jiho Kim (University of Wisconsin-Madison), Anna L Chinni (University of Wisconsin - Madison), Karen Schloss (University of Wisconsin - Madison), Michael Gleicher (University of Wisconsin - Madison)

Presentation

Session

Did you see that? Are you sure?

Time

Wednesday, Nov 11, 13:36 – 13:48 (US/Eastern) · session 13:00 – 14:30

Location

Hall Essex center

Keywords

Divided attention, multitasking, visual reasoning, inferred mappings, color cognition

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.

For Practitioners

This paper is relevant to practitioners who design visualizations that people read while doing something else: a nurse scanning a patient dashboard while responding to alarms, a city operator monitoring traffic maps while handling radio messages, a teacher showing a heatmap during a lecture, or a journalist presenting a map briefly on a news. When viewers are distracted or time-constrained, designs should avoid asking them to reinterpret familiar mappings such as dark-is-more or high-is-more. In practice, this means choosing encodings that make the intended interpretation match viewers’ likely first guess.