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Stephen M. Leach; Jason C. Immekus; Jeffrey C. Valentine; Prathiba Batley; Dena Dossett; Tamara Lewis; Thomas Reece – Assessment for Effective Intervention, 2025
Educators commonly use school climate survey scores to inform and evaluate interventions for equitably improving learning and reducing educational disparities. Unfortunately, validity evidence to support these (and other) score uses often falls short. In response, Whitehouse et al. proposed a collaborative, two-part validity testing framework for…
Descriptors: School Surveys, Measurement, Hierarchical Linear Modeling, Educational Environment
Wang, Xi; Dai, Minhao; Mathis, Robin – International Journal of STEM Education, 2022
Background: Given the relatively low graduation and retention rate in undergraduate engineering programs in the United States, the factors that influence student success outcomes need to be examined. However, limited research systematically studied both student- and school-level factors and how they influenced undergraduate engineering student…
Descriptors: Student Characteristics, Institutional Characteristics, Influences, Engineering Education
Lee LeBoeuf; Jacob Goldstein-Greenwood; Angeline S. Lillard – Journal of Research on Educational Effectiveness, 2024
Common methods of measuring discipline disproportionality can produce contradictory results and obscure base-rate information. In this paper, we show how using multilevel modeling to analyze discipline disparities resolves ambiguities inherent in traditional measures of disparities: relative rate ratios and risk differences. One previous study…
Descriptors: Discipline, Disproportionate Representation, Measurement Techniques, Hierarchical Linear Modeling
Wang, Cixin; La Salle, Tamika; Wu, Chaorong; Liu, Jia Li – School Psychology Review, 2022
Support from parents and school staff are important for adolescent well-being. However, few studies have examined the role of parental involvement and adult social support at school on high school students' mental health, specifically, suicidal thoughts and behaviors (STBs). Data were collected from 362,980 high school students (51.85% female)…
Descriptors: Parent Participation, Adults, Social Support Groups, Suicide
Lee LeBoeuf; Jacob Goldstein-Greenwood; Angeline S Lillard – Grantee Submission, 2023
Common methods of measuring discipline disproportionality can produce contradictory results and obscure base-rate information. In this paper, we show how using multilevel modeling to analyze discipline disparities resolves ambiguities inherent in traditional measures of disparities: relative rate ratios and risk differences. One previous study…
Descriptors: Discipline, Disproportionate Representation, Measurement Techniques, Hierarchical Linear Modeling
Forrow, 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

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