Linking errors introduced by rapid guessing responses when employing multigroup concurrent IRT scaling

Abstract Background Test score comparability in international large-scale assessments (LSAs) is greatly important to ensure test fairness. To effectively compare test scores on an international scale, score linking is widely used to convert raw scores from different linguistic version of test forms into a common score scale. An example is the multigroup concurrent IRT calibration method, which is used for estimating item and ability parameters across multiple linguistic groups of test-takers. Although prior researchers demonstrated its effectiveness in offering greater global comparability in score scales, they assumed comparable test-taking efforts across cultural and linguistic populations. This assumption may not hold true due to differential rapid guessing (RG) rates, potentially biasing item parameter estimation. To address this gap, this study aimed to investigate the linking errors introduced by RG responses when employing multigroup concurrent IRT calibration. Method In the analysis, RG responses were identified using response time data. The study utilized data from the Arabic and Chinese groups in the PISA 2018 Form 18 science module. Test scores for these two linguistic groups were linked through multigroup concurrent IRT calibration, which applies common item parameters across most items and groups, while allowing a select few items to have group-specific parameters. The fit of the item-level model was assessed to identify items requiring group-specific parameters. Results The Arabic group showed a notably higher RG rates for the selected test form when comparing to the Chinese group. Despite observed differential RG, the multigroup concurrent IRT calibration procedure showed robustness to anchor and misfit item identification and ability estimation. However, differential RG was found to have the potential to reduce the precision of individual ability estimation. Findings suggest that RG can influence the multigroup concurrent IRT calibration process, potentially compromising the fairness of test scores in international LSAs. Conclusion This study highlights the critical need to identify and address noneffortful test-taking behaviors, such as RG, to ensure comparability of test scores across different linguistic versions of an assessment. Additionally, documenting variations in test-taking efforts across countries and languages is essential for accurate student performance evaluation and informed educational decisions.

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Publication Details

Journal
Large-scale Assessments in Education
Published
2025-08-14
DOI
https://doi.org/10.1186/s40536-025-00265-8
Citations
1
Primary Topic
Psychometric Methodologies and Testing
Type
article
Field-Weighted Citation Impact
2.11

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article

Linking errors introduced by rapid guessing responses when employing multigroup concurrent IRT scaling

Jiayi Deng
1 citations
Large-scale Assessments in Education
Psychometric Methodologies and Testing
2.11
article

Linking errors introduced by rapid guessing responses when employing multigroup concurrent IRT scaling

Jiayi Deng
article en
1 citations

Abstract

Abstract Background Test score comparability in international large-scale assessments (LSAs) is greatly important to ensure test fairness. To effectively compare test scores on an international scale, score linking is widely used to convert raw scores from different linguistic version of test forms into a common score scale. An example is the multigroup concurrent IRT calibration method, which is used for estimating item and ability parameters across multiple linguistic groups of test-takers. Although prior researchers demonstrated its effectiveness in offering greater global comparability in score scales, they assumed comparable test-taking efforts across cultural and linguistic populations. This assumption may not hold true due to differential rapid guessing (RG) rates, potentially biasing item parameter estimation. To address this gap, this study aimed to investigate the linking errors introduced by RG responses when employing multigroup concurrent IRT calibration. Method In the analysis, RG responses were identified using response time data. The study utilized data from the Arabic and Chinese groups in the PISA 2018 Form 18 science module. Test scores for these two linguistic groups were linked through multigroup concurrent IRT calibration, which applies common item parameters across most items and groups, while allowing a select few items to have group-specific parameters. The fit of the item-level model was assessed to identify items requiring group-specific parameters. Results The Arabic group showed a notably higher RG rates for the selected test form when comparing to the Chinese group. Despite observed differential RG, the multigroup concurrent IRT calibration procedure showed robustness to anchor and misfit item identification and ability estimation. However, differential RG was found to have the potential to reduce the precision of individual ability estimation. Findings suggest that RG can influence the multigroup concurrent IRT calibration process, potentially compromising the fairness of test scores in international LSAs. Conclusion This study highlights the critical need to identify and address noneffortful test-taking behaviors, such as RG, to ensure comparability of test scores across different linguistic versions of an assessment. Additionally, documenting variations in test-taking efforts across countries and languages is essential for accurate student performance evaluation and informed educational decisions.

Large-scale Assessments in EducationVol. 13(1)
Human Resources Research Organization (US)
University of Minnesota
Openalex Percentile: Top 10%
Psychometric Methodologies and Testing
2.11
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