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…

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…