Show Me or Tell Me: Designing Avatars for Feedback

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dc.contributor.authorScott, Michelleko
dc.contributor.authorPereira, Lucasko
dc.contributor.authorOakley, Ianko
dc.date.accessioned2023-09-21T07:01:06Z-
dc.date.available2023-09-21T07:01:06Z-
dc.date.created2023-09-21-
dc.date.created2023-09-21-
dc.date.created2023-09-21-
dc.date.issued2015-07-
dc.identifier.citationINTERACTING WITH COMPUTERS, v.27, no.4, pp.458 - 469-
dc.identifier.issn0953-5438-
dc.identifier.urihttp://hdl.handle.net/10203/312814-
dc.description.abstractAvatars can be employed as a motivational tool, for example, allowing non-verbal communication that can be close to human communication. We describe two lab studies where we presented participants with avatars that communicated verbally via text and visually via expressions. In the first study, participants rated five different categories of captions and corresponding avatars. Results showed that the most persuasive, consistent and trustworthy verbal feedback was given in a humanized form. The second study was an exhaustive forced choice experiment where participants chose the happiest avatar from a pair displayed. Results showed participants found visual avatars more expressive and easier to understand than their verbal counterparts, and that users respond differently when presented with negative or positive emotions. This paper contributes to a better understanding of how to design feedback for expressive avatars.-
dc.languageEnglish-
dc.publisherOXFORD UNIV PRESS-
dc.titleShow Me or Tell Me: Designing Avatars for Feedback-
dc.typeArticle-
dc.identifier.wosid000361835100006-
dc.identifier.scopusid2-s2.0-84936763223-
dc.type.rimsART-
dc.citation.volume27-
dc.citation.issue4-
dc.citation.beginningpage458-
dc.citation.endingpage469-
dc.citation.publicationnameINTERACTING WITH COMPUTERS-
dc.identifier.doi10.1093/iwc/iwu008-
dc.contributor.localauthorOakley, Ian-
dc.contributor.nonIdAuthorScott, Michelle-
dc.contributor.nonIdAuthorPereira, Lucas-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthoragent-based interaction-
dc.subject.keywordAuthoravatars-
dc.subject.keywordAuthoruser studies-
dc.subject.keywordPlusEMOTIONS-
dc.subject.keywordPlusMOTIVATION-
dc.subject.keywordPlusRESPONSES-
dc.subject.keywordPlusREWARDS-
dc.subject.keywordPlusAGENTS-
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