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C. J. Appleton; Dara Shifrer; Cesar J. Rebellon – Journal of Early Adolescence, 2024
The literature linking adulthood criminality to cumulative disadvantage and early school misbehavior demonstrates that understanding the mechanisms underlying student behavior and the responses of teachers and administrators is crucial in comprehending racial/ethnic disparities in actual or perceived school misbehavior. We use data on 19,160 ninth…
Descriptors: Data Use, Racial Differences, Behavior Problems, Student Behavior
Ohio Department of Education, 2021
For the second consecutive school year, Ohio's students and adults faced unique and challenging circumstances because of the ongoing global pandemic. The information in this report card reflects these teaching and learning conditions and should be reviewed while considering the resulting disruptions that, in many cases, affected students'…
Descriptors: COVID-19, Pandemics, Report Cards, Academic Achievement
Ilene Kantrov; Katherine A. Shields – Grantee Submission, 2020
As career and technical education (CTE) has evolved, many school districts that offer high-quality CTE programs such as career academies have found that these programs attract disproportionate numbers of students from historically advantaged populations. Drawing on data from a study of career academies in a large California school district, this…
Descriptors: Data Use, Educational Improvement, Equal Education, Vocational Education
Swain-Bradway, Jessica; Gulbrandson, Kim; Galston, Anthony; McIntosh, Kent – Technical Assistance Center on Positive Behavioral Interventions and Supports, 2019
This evaluation brief describes how Wisconsin is implementing an equitable multi-level system of supports (MLSS) framework, also known as a multi-tiered system of supports (MTSS), and how schools implementing this framework with both a behavior and reading focus have shown positive outcomes for all students. The data analyzed in this brief were…
Descriptors: Behavior Modification, Academic Support Services, Discipline, Student Needs
Using Data from Schools and Child Welfare Agencies to Predict Near-Term Academic Risks. REL 2020-027
Bruch, Julie; Gellar, Jonathan; Cattell, Lindsay; Hotchkiss, John; Killewald, Phil – Regional Educational Laboratory Mid-Atlantic, 2020
This report provides information for administrators, researchers, and student support staff in local education agencies who are interested in identifying students who are likely to have near-term academic problems such as absenteeism, suspensions, poor grades, and low performance on state tests. The report describes an approach for developing a…
Descriptors: At Risk Students, Data Use, Child Welfare, Predictor Variables
Bos, Johannes M.; Dhillon, Sonica; Borman, Trisha – American Institutes for Research, 2019
This is the final report of a large-scale independent evaluation of the Building Assets and Reducing Risks (BARR) model in ninth grade in eleven high schools in Maine, California, Minnesota, Kentucky, and Texas. This sample of schools included large and small schools in urban, suburban, and rural areas, serving students from a wide range of…
Descriptors: Grade 9, High Schools, High School Freshmen, Program Effectiveness
Bulgakov-Cooke, Dina; Singh, Malkeet – Wake County Public School System, 2018
The Multi-Tiered System of Support (MTSS) framework, which uses a systems approach to promote school improvement and support all students in improving academics and behavior using data-based problem-solving, is a key part of the Wake County Public Schools System (WCPSS) Strategic Plan. As of 2017-18, MTSS schools were at the initial stages of MTSS…
Descriptors: Program Effectiveness, Reading Achievement, Academic Achievement, Student Behavior

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