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Large-scale standardized tests are regularly used to measure student achievement overall and for student subgroups. These uses assume tests provide comparable measures of outcomes across student subgroups, but prior research suggests score comparisons across gender groups may be complicated by the type of test items used. This paper presents evidence that among nationally representative samples of 15-year-olds in the United States participating in the 2009, 2012, and 2015 PISA math and reading tests, there are consistent item format by gender differences. On average, male students answer multiple-choice items correctly relatively more often and female students answer constructed-response items correctly relatively more often. These patterns were consistent across 34 additional participating PISA jurisdictions, although the size of the format differences varied and were larger on average in reading than math. The average magnitude of the format differences is not large enough to be flagged in routine differential item functioning analyses intended to detect test bias but is large enough to raise questions about the validity of inferences based on comparisons of scores across gender groups. Researchers and other test users should account for test item format, particularly when comparing scores across gender groups.
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Accounting for Rater Effects With the Hierarchical Rater Model Framework When Scoring Simple Structured Constructed Response Tests
Abstract Many large‐scale assessments are designed to yield two or more scores for an individual by administering multiple sections measuring different but related skills. Multidimensional tests, or more specifically, simple structured tests, such as these rely on multiple multiple‐choice and/or constructed responses sections of items to generate multiple scores. In the current article, we propose an extension of the hierarchical rater model (HRM) to be applied with simple structured tests with constructed response items. In addition to modeling the appropriate trait structure, the multidimensional HRM (M‐HRM) presented here also accounts for rater severity bias and rater variability or inconsistency. We introduce the model formulation, test parameter recovery with a focus on latent traits, and compare the M‐HRM to other scoring approaches (unidimensional HRMs and a traditional multidimensional item response theory model) using simulated and empirical data. Results show more precise scores under the M‐HRM, with a major improvement in scores when incorporating rater effects versus ignoring them in the traditional multidimensional item response theory model.
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- Award ID(s):
- 1324587
- PAR ID:
- 10114320
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Educational Measurement
- Volume:
- 56
- Issue:
- 3
- ISSN:
- 0022-0655
- Page Range / eLocation ID:
- p. 547-581
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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