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

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...

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Main Authors: Serkan Varol, Serkan Catma
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Education Sciences
Subjects:
Online Access:https://www.mdpi.com/2227-7102/11/9/508
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spelling doaj-a4980e420c234f63b1fc6595ca54907d2021-09-26T00:02:04ZengMDPI AGEducation Sciences2227-71022021-09-011150850810.3390/educsci11090508Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. CollegesSerkan Varol0Serkan Catma1Department of Engineering Management and Technology, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USADepartment of Business Administration, University of South Carolina Beaufort, Bluffton, SC 29909, USAStudent 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.https://www.mdpi.com/2227-7102/11/9/508student retentionspatial factordistancemetropolitan areainstitutional characteristicsclustering
collection DOAJ
language English
format Article
sources DOAJ
author Serkan Varol
Serkan Catma
spellingShingle Serkan Varol
Serkan Catma
Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges
Education Sciences
student retention
spatial factor
distance
metropolitan area
institutional characteristics
clustering
author_facet Serkan Varol
Serkan Catma
author_sort Serkan Varol
title Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges
title_short Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges
title_full Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges
title_fullStr Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges
title_full_unstemmed Assessing the Impact of a Distance-Based Spatial Factor on Retention in the U.S. Colleges
title_sort assessing the impact of a distance-based spatial factor on retention in the u.s. colleges
publisher MDPI AG
series Education Sciences
issn 2227-7102
publishDate 2021-09-01
description 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.
topic student retention
spatial factor
distance
metropolitan area
institutional characteristics
clustering
url https://www.mdpi.com/2227-7102/11/9/508
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