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

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.

Media: Videos, Slides, and Supplemental Material

Pre-Recorded Talk @ IEEE VIS ’22

Soon!

25 seconds Preview

https://youtu.be/yYP5_4_xugs

Link to the 25 seconds preview video.

Download the Author Version of the Paper:

Download the Appendix:

Supplemental Material

With this publication we also provide all the data connected to the study. As we conducted the online experiment via LimeSurvey, you can find an exported *.pdf of the LimeSurvey study structure. Further, the created visualizations as well as the data set can be found here as well. For the data analysis process, we made use of python to pre-process the data, performed some basic statistical, and created the visualization seen in this publication. Lastly, we used JASP to create and calculate the linear mixed models presented in this study.
Files

Related Publication

Related Student Theses

Acknowledgments

We thanks Vincent Schmidt for the study support. This work was funded by the Deutsche Forschungsgemeinschaft (DFG) by DFG grant 319919706/RTG 2323, by DFG grant 389792660 as part of TRR 248 – CPEC (see https://perspicuous-computing.science), and as part of Germany’s Excellence Strategy – EXC- 2050/1 – 390696704 – Cluster of Excellence “Centre for Tactile Internet with Human-in-the-Loop” (CeTI) of TU Dresden.