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How Effective Are Eye-Tracking Data in Identifying Problematic Questions?

[Zeitschriftenartikel]

Neuert, Cornelia

Abstract

To 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 tec... mehr

To 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.... weniger

Thesaurusschlagwörter
Datengewinnung; Datenqualität; Fragebogen; Antwortverhalten; Umfrageforschung

Klassifikation
Erhebungstechniken und Analysetechniken der Sozialwissenschaften

Freie Schlagwörter
eye tracking; pupillometry

Sprache Dokument
Englisch

Publikationsjahr
2020

Seitenangabe
S. 793-802

Zeitschriftentitel
Social Science Computer Review, 38 (2020) 6

DOI
https://doi.org/10.1177/0894439319834289

ISSN
1552-8286

Status
Veröffentlichungsversion; begutachtet (peer reviewed)

Lizenz
Deposit Licence - Keine Weiterverbreitung, keine Bearbeitung


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Home  |  Impressum  |  Betriebskonzept  |  Datenschutzerklärung
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.