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Sage, Andrew J.; Cervato, Cinzia; Genschel, Ulrike; Ogilvie, Craig A. – Journal of College Student Retention: Research, Theory & Practice, 2021
Students are most likely to leave science, technology, engineering, and mathematics (STEM) majors during their first year of college. We developed an analytic approach using random forests to identify at-risk students. This method is deployable midway through the first semester and accounts for academic preparation, early engagement in university…
Descriptors: Majors (Students), Identification, Student Satisfaction, At Risk Students
Espinoza, Penelope; Genna, Gaspare M. – Journal of College Student Retention: Research, Theory & Practice, 2021
Performance during the first year of college and in introductory courses has been widely identified as critical to college students' retention and success. Accordingly, interventions to assist beginning college students in gateway courses have gained increased attention in higher education. This study tested such an intervention using learning…
Descriptors: Identification, Intervention, Class Size, Introductory Courses
Campbell, Corbin M.; Mislevy, Jessica L. – Journal of College Student Retention: Research, Theory & Practice, 2013
Along with the massification of higher education and increasing costs, the pressure on institutions to retain all students to degree completion has been mounting. Early identification of students who are at risk of leaving an institution may help institutions to target and retain these students. This study investigated whether freshmen behaviors,…
Descriptors: Identification, At Risk Students, School Holding Power, Enrollment
Silverman, Loretta H.; Seidman, Alan – Journal of College Student Retention: Research, Theory & Practice, 2012
The majority of college students are not ready for college-level math courses, which, when completed, have been shown to increase graduation and transfer rates. To address this problem, the Math My Way (MMW) program was developed to integrate module-based curriculum and mastery learning approaches. The program is based on Seidman's retention…
Descriptors: Control Groups, Grade Point Average, Academic Achievement, Mastery Learning
Whalen, Don; Saunders, Kevin; Shelley, Mack – Journal of College Student Retention: Research, Theory & Practice, 2010
Logistic regression models of students' 1-year retention and 6-year retention/graduation for the fall 2000 entering class of students at a research-extensive university in the Midwest were estimated by combining university, financial aid, and Cooperative Institutional Research Program data (n = 1,905; 45% female, 87% Caucasian, 75% in-state).…
Descriptors: Research Universities, School Holding Power, Academic Persistence, Identification