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Download full textForrow, Lauren; Starling, Jennifer; Gill, Brian – Regional Educational Laboratory Mid-Atlantic, 2023
The Every Student Succeeds Act requires states to identify schools with low-performing student subgroups for Targeted Support and Improvement or Additional Targeted Support and Improvement. Random differences between students' true abilities and their test scores, also called measurement error, reduce the statistical reliability of the performance…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
Regional Educational Laboratory Mid-Atlantic, 2023
This Snapshot highlights key findings from a study that used Bayesian stabilization to improve the reliability (long-term stability) of subgroup proficiency measures that the Pennsylvania Department of Education (PDE) uses to identify schools for Targeted Support and Improvement (TSI) or Additional Targeted Support and Improvement (ATSI). The…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
Regional Educational Laboratory Mid-Atlantic, 2023
The "Stabilizing Subgroup Proficiency Results to Improve the Identification of Low-Performing Schools" study used Bayesian stabilization to improve the reliability (long-term stability) of subgroup proficiency measures that the Pennsylvania Department of Education (PDE) uses to identify schools for Targeted Support and Improvement (TSI)…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
Direct linkGottfried, Michael A.; Johnson, Erica L. – Education and Urban Society, 2014
Identifying sources of variation has been used extensively in educational research as a tool to identify potential drives of variances in student achievement. However, prior research predominantly relied on findings from national- or international-level data, and thus their conclusions remain very broad-based. This study contributes new insight by…
Descriptors: Equal Education, Urban Schools, Standardized Tests, Achievement Tests
Fantuzzo, John W.; LeBoeuf, Whitney A.; Rouse, Heather L. – Educational Researcher, 2014
This study investigated the unique relations between school concentrations of student risk factors and measures of reading, mathematics, and attendance. It used an integrated administrative data system to create a combined data set of risks (i.e., birth risks, teen mother, low maternal education, homelessness, maltreatment, and lead exposure) for…
Descriptors: At Risk Students, Well Being, Correlation, Early Parenthood
