Improving Retention and Enrollment Forecasting in Part-Time Programs

This article describes a model that can be used to analyze student enrollment data and can give insights for improving retention of part-time students and refining institutional budgeting and planning efforts. Adult higher-education programs are often challenged in that part-time students take courses less reliably than full-time students. For many institutions, part-time adult students are also less likely to graduate and complete a credential program. The model presented in this article is unique in that it "de-cohortizes" student enrollment data and then uses students' own enrollments as a predictor of future enrollments. The benefits of such a model are twofold. First, students' past enrollments are, in fact, predictive of future enrollments. Second, insofar as students' enrollment patterns are constantly changing each quarter, the predictive power of the model increases over time for each student. (Contains 3 figures, 1 table and 3 endnotes.)