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Shao, Lucy; Ieong, Martin; Levine, Richard A.; Stronach, Jeanne; Fan, Juanjuan – Strategic Enrollment Management Quarterly, 2022
Accurately forecasting course enrollment rates in higher education is of great concern in order to minimize unnecessary administrative costs as well as burden to both students and faculty. This research aimed to first recreate course enrollment predictions based on a conditional probability analysis using student data from San Diego State…
Descriptors: Artificial Intelligence, Prediction, Enrollment, Courses
Pelaez, Kevin – Journal of Educational Data Mining, 2019
Higher education institutions often examine performance discrepancies of specific subgroups, such as students from underrepresented minority and first-generation backgrounds. An increase in educational technology and computational power has promoted research interest in using data mining tools to help identify groups of students who are…
Descriptors: At Risk Students, College Students, Identification, Multivariate Analysis