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…

An existing school program in which therapy dogs are integrated into the reading curriculum was analyzed to determine the effect on student reading. Previous literature suggests an improvement in both reading skills and attitudes towards reading when students read in the presence of a therapy dog. Using a mixed method model, the researchers…

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…

This report is a longitudinal examination of "Preschool for All" (PFA) participants, tracking students' experiences across their first four years in elementary school. It builds upon a 2009 study that found that PFA graduates in San Mateo County were better prepared for kindergarten than their classmates who had not attended preschool…

How many students repeat a grade each year? How do retention rates vary across states and over time? Despite extensive research on the predictors and consequences of grade retention, there is no systematic way to quantify state-level retention rates; even national estimates rely on imperfect proxy measures. We present a conceptually simple…