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Direct linkKaren Blackburn Hoeve – ProQuest LLC, 2021
High stakes test-based accountability systems primarily rely on aggregates and derivatives of scores from tests that were originally developed to measure individual student mastery of content specifications. Current validity models do not explicitly address this use of aggregate scores to measure the performance of teachers, administrators, and…
Descriptors: Accountability, Test Validity, High Stakes Tests, Hierarchical Linear Modeling
Peer reviewedPrior, Lucy; Goldstein, Harvey; Leckie, George – School Effectiveness and School Improvement, 2021
Education systems around the world increasingly rely on school value-added models to monitor school performance and hold schools to account. These models typically focus on a limited number of academic outcomes. We explore how the traditional multilevel modelling approach to school value-added models can be extended to simultaneously analyse…
Descriptors: Value Added Models, Foreign Countries, Accountability, Outcomes of Education
Ekpenyong, John A.; Owan, Valentine J.; Ogar, Joseph O.; Undie, John A. – Cogent Education, 2022
Research has assessed the diverse characteristics of principals and teachers in analysing students' educational outcomes at various levels. However, these studies often focus on the cognitive domain of learning, ignoring the affective and psychomotor aspects. Bridging this gap, we used hierarchical linear regression to link two inputs of teachers…
Descriptors: Hierarchical Linear Modeling, Outcomes of Education, Secondary School Students, Foreign Countries
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
