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[journal article]

dc.contributor.authorNeuert, Corneliade
dc.date.accessioned2023-03-02T10:59:24Z
dc.date.available2023-03-02T10:59:24Z
dc.date.issued2020de
dc.identifier.issn1552-8286de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/85336
dc.description.abstractTo collect high-quality data, survey designers aim to develop questions that each respondent can understand as intended. A critical step to this end is designing questions that minimize the respondents' burden by reducing the cognitive effort required to comprehend and answer them. One promising technique for identifying problematic survey questions is eye tracking. This article investigates the potential of eye movements and pupil dilations as indicators for evaluating survey questions. Respondents were randomly assigned to either a problematic or an improved version of six experimental questions. By analyzing fixation times, fixation counts, and pupil diameters, it was examined whether these parameters could be used to distinguish between the two versions. Identifying the improved version worked best by comparing fixation times, whereas in most cases, it was not possible to differentiate between versions on the basis of pupil data. Limitations and practical implications of the findings are discussed.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.othereye tracking; pupillometryde
dc.titleHow Effective Are Eye-Tracking Data in Identifying Problematic Questions?de
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.identifier.urllocalfile:/var/tmp/crawlerFiles/deepGreen/ff15b22dd8d348dbac246a7d85af6a4a/ff15b22dd8d348dbac246a7d85af6a4a.pdfde
dc.source.journalSocial Science Computer Review
dc.source.volume38de
dc.publisher.countryUSAde
dc.source.issue6de
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.subject.thesozDatenqualitätde
dc.subject.thesozdata qualityen
dc.subject.thesozFragebogende
dc.subject.thesozquestionnaireen
dc.subject.thesozAntwortverhaltende
dc.subject.thesozresponse behavioren
dc.subject.thesozUmfrageforschungde
dc.subject.thesozsurvey researchen
dc.identifier.urnurn:nbn:de:0168-ssoar-85336-7
dc.rights.licenceDeposit Licence - Keine Weiterverbreitung, keine Bearbeitungde
dc.rights.licenceDeposit Licence - No Redistribution, No Modificationsen
ssoar.contributor.institutionGESISde
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10040547
internal.identifier.thesoz10055811
internal.identifier.thesoz10037914
internal.identifier.thesoz10035808
internal.identifier.thesoz10040714
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo793-802de
internal.identifier.classoz10105
internal.identifier.journal645
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.1177/0894439319834289de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence3
internal.identifier.pubstatus1
internal.identifier.review1
ssoar.wgl.collectiontruede
internal.dda.referencecrawler-deepgreen-188@@ff15b22dd8d348dbac246a7d85af6a4a


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