Exploring the relationship between student background characteristics and college performance indicators with learning community student persistence

Abstract

The purpose of this study was to explore the relationship between student background characteristics and college performance indicators with learning community student persistence. The learning community design was tailored for students who required remediation in both math and English. The research site was a rural community college located in the northeastern United States. The sample included 424 students who enrolled in this learning community during their first semester in college. Binary logistic regression techniques were used to examine both the direct association and interactive association of select theoretically relevant variables with student persistence. The direct associations tested in this study representing student background characteristics (e.g., age, race/ethnicity, gender, high school GPA, and receipt of financial aid) were included in various models, along with select college performance indicators (e.g., pass remedial math course, pass remedial English course, pass student success course, and college GPA), in relationship with the likelihood of future semester persistence. Interactive variables were introduced representing combinations of student background characteristics and college performance indicators to explore the effects additional variables have within the models. Results indicated passing the required remedial coursework, particularly the math and the student success course, are important in improving the likelihood of persistence. Discussion focused on improving remedial education successful course completion, early identification of students underperforming, and possibilities for methodological replication.