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

[journal article]

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... view more

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.... view less

Keywords
data capture; data quality; questionnaire; response behavior; survey research

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
eye tracking; pupillometry

Document language
English

Publication Year
2020

Page/Pages
p. 793-802

Journal
Social Science Computer Review, 38 (2020) 6

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

ISSN
1552-8286

Status
Published Version; peer reviewed

Licence
Deposit Licence - No Redistribution, No Modifications


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