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Melissa Dan Wang – Large-scale Assessments in Education, 2025
Although self-report surveys are widely used for data collection, data quality can vary across populations because certain groups are more likely to engage in insufficient effort responding (IER). Our study examined how different levels of the educational system--student groups, schools, and cultural contexts--affect data quality due to IER, using…
Descriptors: Responses, Response Style (Tests), Questionnaires, Surveys
Ercikan, Kadriye; Guo, Hongwen; He, Qiwei – Educational Assessment, 2020
Comparing group is one of the key uses of large-scale assessment results, which are used to gain insights to inform policy and practice and to examine the comparability of scores and score meaning. Such comparisons typically focus on examinees' final answers and responses to test questions, ignoring response process differences groups may engage…
Descriptors: Data Use, Responses, Comparative Analysis, Test Bias
Wu, Mike; Davis, Richard L.; Domingue, Benjamin W.; Piech, Chris; Goodman, Noah – International Educational Data Mining Society, 2020
Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially improving test scoring and better informing public policy. Yet larger…
Descriptors: Item Response Theory, Accuracy, Data Analysis, Public Policy
Lu, Yi – ProQuest LLC, 2012
Cross-national comparisons of responses to survey items are often affected by response style, particularly extreme response style (ERS). ERS varies across cultures, and has the potential to bias inferences in cross-national comparisons. For example, in both PISA and TIMSS assessments, it has been documented that when examined within countries,…
Descriptors: Item Response Theory, Attitude Measures, Response Style (Tests), Cultural Differences

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