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

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

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.

Details

OriginalspracheEnglisch
Titel2022 IEEE Visualization and Visual Analytics (VIS)
Erscheinungsort Oklahoma City, OK, USA
Herausgeber (Verlag)IEEE
Seiten90-94
Seitenumfang5
ISBN (elektronisch)978-1-6654-8812-9
ISBN (Print)978-1-6654-8813-6
PublikationsstatusVeröffentlicht - 16 Okt. 2022
Peer-Review-StatusJa

Publikationsreihe

ReiheInternational Conference on Visualisation, VIS

Konferenz

Titel2022 IEEE Visualization Conference, VIS 2022
Dauer16 - 21 Oktober 2022
StadtVirtual, Online
LandUSA/Vereinigte Staaten

Externe IDs

Mendeley 4f580078-3651-39c9-b89a-bed3cd2047dc
ORCID /0000-0002-1952-8302/work/142239531
ORCID /0000-0002-4280-6534/work/142251677
ORCID /0000-0002-2176-876X/work/151435439

Schlagworte

Schlagwörter

  • Human-centered computing, Information Visualization, online survey, User Experience, User Study, Visualization, Visualization Adaptation, Visualization Competence, Visualization design and evaluation methods, Visualization Literacy, On-line Survey