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Identifying Students at Risk Using Prior Performance versus a Machine Learning Algorithm. REL 2021-126
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Cattell, Lindsay; Bruch, Julie – Regional Educational Laboratory Mid-Atlantic, 2021
This report provides information for administrators in local education agencies who are considering early warning systems to identify at-risk students. Districts use early warning systems to target resources to the most at-risk students and intervene before students drop out. Schools want to ensure the early warning system accurately identifies…
Descriptors: At Risk Students, Identification, Artificial Intelligence, Dropout Prevention
The Predictive Validity of the Structured Assessment of Violence Risk in Youth in Secondary Educational Settings
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McGowan, Mark R.; Horn, Robert A.; Mellott, Ramona N. – Psychological Assessment, 2011
Current developments in violence risk assessment warrant consideration for use within educational settings. Using a structured professional judgment (SPJ) model, the present study investigated the predictive validity of the Structured Assessment of Violence in Youth (SAVRY) within educational settings. The predictive accuracy of the SAVRY scales…
Descriptors: Predictive Validity, Measures (Individuals), Violence, Risk
Data Driven Identification and Selection Algorithms for At-Risk Students Likely to Benefit from High School Academic Support Services
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Lacefield, Warren E.; Applegate, E. Brooks; Zeller, Pamela J.; Van Kannel-Ray, Nancy; Carpenter, Shelly – Online Submission, 2011
This study describes a well-defined data-driven diagnostic identification and selection procedure for choosing students at-risk of academic failure for appropriate academic support services. This algorithmic procedure has been validated both by historical quantitative studies of student precedents and outcomes as well as by current qualitative…
Descriptors: Academic Failure, At Risk Students, Identification, Information Systems
ADHD and Achievement: Meta-Analysis of the Child, Adolescent, and Adult Literatures and a Concomitant Study with College Students
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Frazier, Thomas W.; Youngstrom, Eric A.; Glutting, Joseph J.; Watkins, Marley W. – Journal of Learning Disabilities, 2007
This article presents results from two interrelated studies. The first study conducted a meta-analysis of the published literature since 1990 to determine the magnitude of achievement problems associated with attention-deficit/hyperactivity disorder (ADHD). Effect sizes were significantly different between participants with and without ADHD…
Descriptors: Parent Attitudes, Student Attitudes, College Students, Standardized Tests