Student involvement: A developmental theory for higher education. Economics of Education Review, 71, 120–134. Student loans in Japan: Current problems and possible solutions. Permutation importance: A corrected feature importance measure. Īltmann, A., Tolosi, L., Sander, O., & Lengauer, T. Predicting time to graduation at a large enrollment American university. M., De Bin, R., Hjorth-Jensen, M., & Caballero, M. Retrieved September 10, 2021, from Īiken, J. Department of Education, Office of Vocational and Adult Education. The toolbox revisited: Paths to degree completion from high school through college. Retrieved September 10, 2021, from Īdelman, C. Department of Education, National Institute on Postsecondary Education, Libraries, and Lifelong Learning. Academic intensity, attendance patterns, and bachelor’s degree attainment. Identified students included many who may be missed by established university protocols, such as students with high financial need who are making adequate but not strong degree progress.Īdelman, C. Applying the machine learning algorithms to currently enrolled students allowed identification of those who could benefit from added support. We predicted students’ graduation outcomes with an overall accuracy of 79%. Credit hours earned, college and high school grade point averages, estimated family (financial) contribution, and enrollment and grades in required gateway courses within a student’s major were all important predictors of graduation outcome. Here we empirically develop machine learning algorithms, specifically Random Forest, to accurately predict if and when first-time-in-college undergraduates will graduate based on admissions, academic, and financial aid records two to six semesters after matriculation. This problem emphasizes the need to identify students who may benefit from support to encourage timely graduation. The majority of those remaining will take longer than 4 years to complete their degree at “4-year” institutions. About one-third of college students drop out before finishing their degree.
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