Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges

Abstract

Student retention is a wide-reaching issue that causes a concern to postsecondary institutions and policy-makers. This research aimed to examine the impact of a geo-spatial factor—distance to the closest metropolitan area—on student retention from a multi-institutional perspective, through the data collected from the Integrated Postsecondary Education Data System (2017) of the U.S. Department of Education. Using the K-means clustering technique, 329 geographically dispersed higher education institutions with similar characteristics were identified. A spatial lag model was adopted to account for spatial autocorrelation detected within the dataset. A series of hierarchical regression was then conducted to measure how well the spatial variable explained student retention rate after accounting for institutional level attributes. The student retention rate was found to decrease as a university is located away from the closest metropolitan area. This finding has crucial policy and administrative implications if analyzed within the context of rural–urban discrepancies in higher education. Extending the spatial scope of retention analysis is an important step in accurately determining the set of factors that provides a better understanding of this complex problem.

Keywords

• student retention
• spatial factor
• distance
• metropolitan area
• institutional characteristics
• clustering