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Direct linkSorensen, Lucy C. – Educational Administration Quarterly, 2019
Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…
Descriptors: At Risk Students, Dropouts, Data Collection, Data Analysis
Lane, Kathleen Lynne; Oakes, Wendy Peia; Swogger, Emily D.; Schatschneider, Christopher; Menzies, Holly Mariah; Sanchez, Jeremy – Behavioral Disorders, 2015
We report findings of a convergent validity study examining the internalizing subscale (SRSS-I5) of the newly adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE12) with the internalizing subscale of the Teacher Report Form (TRF; Achenbach, 1991) conducted in 13 schools across three states with 195 kindergarten…
Descriptors: Screening Tests, Behavior Problems, Cutting Scores, Decision Making
Download full textBerg, Juliette; Torrente, Catalina; Aber, J. Lawrence; Jones, Stephanie M.; Brown, Joshua L. – Society for Research on Educational Effectiveness, 2010
The 4Rs Program (Reading, Writing, Respect and Resolution) is a "dual focus" whole school universal intervention designed to promote literacy development and social-emotional learning, that is currently being rigorously evaluated using a school-randomized trial of 18 elementary schools (9 intervention, 9 control) in New York City. The…
Descriptors: Intervention, Educational Change, Data, Program Evaluation
