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Using Data from Schools and Child Welfare Agencies to Predict Near-Term Academic Risks. REL 2020-027
Peer reviewed
Download full textBruch, 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
