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Improving the Measurement of School Climate Using Item Response Theory
The U.S. government has become increasingly focused on school climate, as recently evidenced by its inclusion as an accountability indicator in the Every Student Succeeds Act. Yet, there remains considerable variability in both conceptualizing and measuring school climate. To better inform the resea...
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Published in: | Educational measurement, issues and practice issues and practice, 2019-12, Vol.38 (4), p.99-107 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The U.S. government has become increasingly focused on school climate, as recently evidenced by its inclusion as an accountability indicator in the Every Student Succeeds Act. Yet, there remains considerable variability in both conceptualizing and measuring school climate. To better inform the research and practice related to school climate and its measurement, we leveraged item response theory (IRT), a commonly used psychometric approach for the design of achievement assessments, to create a parsimonious measure of school climate that operates across varying individual characteristics. Students (n = 69,513) in 111 secondary schools completed a school climate assessment focused on three domains of climate (i.e., safety, engagement, and environment), as defined by the U.S. Department of Education. Item and test characteristics were estimated using the mirt package in R using unidimensional IRT. Analyses revealed measurement difficulties that resulted in a greater ability to assess less favorable perspectives on school climate. Differential item functioning analyses indicated measurement differences based on student academic success. These findings support the development of a broad measure of school climate but also highlight the importance of work to ensure precision in measuring school climate, particularly when considering use as an accountability measure. |
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ISSN: | 0731-1745 1745-3992 |
DOI: | 10.1111/emip.12296 |