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Baker, Ryan S.; Berning, Andrew W.; Gowda, Sujith M.; Zhang, Shizhu; Hawn, Aaron – Journal of Education for Students Placed at Risk, 2020
Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students' discipline, attendance, course-taking,…
Descriptors: At Risk Students, High School Students, Dropout Prevention, Student Diversity
Botelho, Anthony F.; Varatharaj, Ashvini; Patikorn, Thanaporn; Doherty, Diana; Adjei, Seth A.; Beck, Joseph E. – IEEE Transactions on Learning Technologies, 2019
The increased usage of computer-based learning platforms and online tools in classrooms presents new opportunities to not only study the underlying constructs involved in the learning process, but also use this information to identify and aid struggling students. Many learning platforms, particularly those driving or supplementing instruction, are…
Descriptors: Student Attrition, Student Behavior, Early Intervention, Identification