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Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
Bettinger, Eric; Fox, Lindsay; Loeb, Susanna; Taylor, Eric – Stanford Center for Education Policy Analysis, 2015
Online college courses are a rapidly expanding feature of higher education, yet little research identifies their effects. Using an instrumental variables approach and data from DeVry University, this study finds that, on average, online course-taking reduces student learning by one-third to one-quarter of a standard deviation compared to…
Descriptors: Online Courses, Conventional Instruction, Delivery Systems, Intermode Differences