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dc.contributor.authorKovacevic, Nikolaen_US
dc.contributor.authorWampfler, Rafaelen_US
dc.contributor.authorSolenthaler, Barbaraen_US
dc.contributor.authorGross, Markusen_US
dc.contributor.authorGünther, Tobiasen_US
dc.contributor.editorKerren, Andreas and Garth, Christoph and Marai, G. Elisabetaen_US
dc.date.accessioned2020-05-24T13:52:05Z
dc.date.available2020-05-24T13:52:05Z
dc.date.issued2020
dc.identifier.isbn978-3-03868-106-9
dc.identifier.urihttps://doi.org/10.2312/evs.20201059
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evs20201059
dc.description.abstractDecades of research in psychology on the formal measurement of emotions led to the concept of affective states. Visualizing the measured affective state can be useful in education, as it allows teachers to adapt lessons based on the affective state of students. In the entertainment industry, game mechanics can be adapted based on the boredom and frustration levels of a player. Visualizing the affective state can also increase emotional self-awareness of the user whose state is being measured, which can have an impact on well-being. However, graphical user interfaces seldom visualize the user's affective state, but rather focus on the purely objective interaction between the system and the user. This paper proposes two graphical user interface widgets that visualize the user's affective state, ensuring a compact and unobtrusive visualization. In a user study with 644 participants, the widgets were evaluated in relation to a baseline widget and were tested on intuitiveness and understandability. Particularly in terms of understandability, the baseline was outperformed by our two widgets.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectHuman centered computing
dc.subjectEmpirical studies in visualization
dc.subjectUser studies
dc.subjectInformation visualization
dc.titleGlyph-Based Visualization of Affective Statesen_US
dc.description.seriesinformationEuroVis 2020 - Short Papers
dc.description.sectionheadersRepresentation, Perception, and ML
dc.identifier.doi10.2312/evs.20201059
dc.identifier.pages121-125


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License