Who benefits from Visualization Adaptations? Towards a better Understanding of the Influence of Visualization Literacy

TL;DR

This study investigates how visualization literacy influences the effectiveness of visualization adaptations, specifically De-Emphasis, on user performance and experience across different visualization types.

Contribution

It provides empirical evidence that visualization adaptations benefit users differently depending on their visualization literacy levels.

Findings

De-Emphasis adaptation improves performance across all users.

VL interacts with adaptation to influence task completion time for bar charts.

The study highlights the importance of considering VL in designing visualization adaptations.

Abstract

The ability to read, understand, and comprehend visual information representations is subsumed under the term visualization literacy (VL). One possibility to improve the use of information visualizations is to introduce adaptations. However, it is yet unclear whether people with different VL benefit from adaptations to the same degree. We conducted an online experiment (n = 42) to investigate whether the effect of an adaptation (here: De-Emphasis) of visualizations (bar charts, scatter plots) on performance (accuracy, time) and user experiences depends on users' VL level. Using linear mixed models for the analyses, we found a positive impact of the De-Emphasis adaptation across all conditions, as well as an interaction effect of adaptation and VL on the task completion time for bar charts. This work contributes to a better understanding of the intertwined relationship of VL and visual adaptations and motivates future research.