VARIABLES THAT AFFECT GRADUATION IN A COMMUNITY COLLEGE

Abstract

This study examined whether the use of variables—age, sex, remediation, and financial aid— could be used to predict persistence to graduation in a community college sample. The study also asked if these same variables could be used to predict number of semesters completed in this sample. Archival data were gathered from a community college with multiple campuses and a single state-wide accreditation from the Higher Learning Commission of the North Central Association of Colleges and Schools. Logistic regression, ordinary least squares regression, and Pearson r correlation were used to analyze data. Results suggested overall model significance in the logistic regression with the variables of age and remediation identified as significant predictors of persistence to graduation. The ordinary least squares regression was not significant, but the individual variable of age was significant, albeit at a level that provided no practical application. Correlational analyses revealed a significant positive relationship between age and remediation and a significant positive relationship between financial aid and remediation. Discussion centered on how these findings could be used to design interventions to increase student persistence to graduation in community colleges.