Analysis of Risk Factors for Student Retention

Student attrition is an important issue for higher education as it brings about grave costs to both students and institutions. This article investigates the 2-year persistence rate of students enrolled at a large 4-year public institution in California in Fall 2016 to Fall 2020. Predictors considered include student demographic information, socioeconomic variables, academic preparation, and their academic performance at the institution. Two analytical approaches are used, discrete-time survival analysis and random forest (RF). The results indicate that academic performance variables after enrollment are most strongly associated with 2-year persistence. In particular, monitoring and providing help promptly to students with earned-units below 6 or GPA below 2.0 in the first term may prevent them from dropping out. Among socioeconomic variables available for analysis, first-generation status seems to be more directly related to student attrition. It is also illustrated how the RF model may be used to provide individualized prediction of 2-year persistence.