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…

Background: The purpose of the present study was to test a maternal attachment model of behavior problems in early childhood using phase I data from the NICHD Study of Early Child Care, a prospective study of 1,364 children from birth through sixth grade. Methods: Mothers' and caregivers' ratings of children's internalizing and externalizing…