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…

Although childhood shyness has been associated with school-adjustment difficulties in contemporary research in China, the conceptual mechanisms that may underlie these relations remain underinvestigated. The goal of this study was to examine a complex theoretical model that explicates the roles of both peer preference and teacher-child…

As charter school waitlists around the United States continue to grow, it is important to analyze the factors that are possibly attracting parents away from the traditional public school setting and into the charter school system. Using waitlist data from Pennsylvania to proxy for parental valuation, the article examines numerous factors that…