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…

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…

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,…

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…

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).…