A Geographic-Information-Systems-Based Approach to Analysis of Characteristics Predicting Student Persistence and Graduation

Abstract

This study sought to provide empirical evidence regarding the use of spatial analysis in enrollment management to predict persistence and graduation. The research utilized data from the 2000 U.S. Census and applicant records from The University of Arizona to study the spatial distributions of enrollments. Based on the initial results, stepwise logistic regression was used to identify spatially associated student and neighborhood characteristics predicting persistence and graduation.The findings of this research indicate spatial analysis can be used as a valuable resource for enrollment management. Using a theoretical framework of the forms of capital and social reproduction, cultural and social capital characteristics were found to influence persistence at statistically significant levels. Most notably, the social capital proxy of neighborhood education levels, and the cultural capital proxies of the number of standardized tests a student has taken, and when the application for admission is submitted all significantly influenced a student's probability to persistence and graduate. When disaggregating by race and ethnicity, resident Hispanic students from highly Hispanic neighborhoods were found to persist at higher levels in the first year of college attendance. Also, resident Native Americans were found to have a higher probability to persist when evidencing cultural capital characteristics. Since spatially based student and neighborhood characteristics can be quantified and mapped, target populations can be identified and subsequently recruited, resulting in retention-focused admissions.