Improving the Retention of First-Year College Students: A Temporal Model of Assessment and Intervention

This investigation sought to determine when colleges should conduct assessments to identify first-year students at risk of dropping out. Thirty-five variables were used to predict the persistence of 2,024 first-year students from four universities in the southeastern United States. The predictors were subdivided into groups according to when they became available during the students' first college year: (a) indices obtained during the admissions process, (b) measures that could be gathered at matriculation, and (c) variables requiring interactions with the school's academic and social environments. Sequential logistic regression found statistically significant and practically important increments in the ability to predict retention with the addition of each temporal group. Variables dependent upon interactions with the academic and social environments were the best predictors of retention. The resulting temporal model was used to generate strategies for when and how college personnel should intervene to increase retention.