This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

Despite advances made in broadening access to higher education, some evidence suggests that college completion rates have actually declined over time, and attainment gaps stemming from race/ethnicity and socioeconomic background have remained stubbornly persistent (Bound, Lovenheim, & Turner, 2010; National Center for Education Statistics,…

Education leaders need valid metrics to predict students' long-term success. We use a unique data set with cognitive skills, self-regulation, behavior, course performance, and test scores for eighth-grade students from a Northeast school district. We link these data to students' high school outcomes, college enrollment, persistence, and on-time…