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Enhancing UEQ Questionnaire Data Visualizations with AttrakDiff Visualization Techniques

Authors: Gómez Segura, Carlos Adrián; López Herrera, Gustavo; Quesada, Luis;

Enhancing UEQ Questionnaire Data Visualizations with AttrakDiff Visualization Techniques

Abstract

The research analyzes how applying AttrakDiff visualization techniques can improve User Experience Questionnaire (UEQ) data representations. Although the UEQ is a commonly used instrument for assessing user experience, the visualizations are can provide more insights. The study adapts AttrakDiff visualizations to UEQ and also proposes new visualizations. According to the study’s findings, participants responded favorably to AttrakDiff-like visualizations’ ability to accurately portray UEQ data. Participants in a sizable majority agreed that the AttrakDiff-like visualizations and proposed ones successfully captured user experience data. The results also showed that the new proposed visuals were simple to comprehend, and most participants praised their clarity.

UCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ciencias de la Computación e Informática

Country
Costa Rica
Related Organizations
Keywords

Questionnaires, Evaluation methods, Human machine interaction, AttrakDiff, User experi ence evaluation, Data analysis, Visualizations, User Experience Questionnaire (UEQ)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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