The Effect of Revenue and Local Economic Indicators on Texas Public Two-Year College Enrollment for the Fiscal Years Ending 2007-2016

Document Type

Dissertation

Degree Name

Doctor of Education (Ed.D)

Department

Higher Edu and Learning Technology

Date of Award

Spring 2020

Abstract

The researcher examined the relationship between revenue and county economic variables and enrollment based on community college district size for Texas public two-year colleges for the fiscal years ending 2007-2016 utilizing multiple regression, specifically block entry method. In addition, the researcher examined similarities and differences among the variables within this study based on community college district size, as defined by the THECB, utilizing independent-samples t-tests. For small-to-medium community college districts for five years of increasing enrollment, the House Price Index is significant with p values < .05. Revenue is significant with p values < .001. This model explained 59% of enrollment for small-to-medium community college districts for the fiscal years 2007 through 2011. For small-to-medium community college districts for the five years of decreasing enrollment, Revenue is the only significant variable with p values < .001. This model explained 55% of enrollment for small-to-medium community college districts for the fiscal years 2012 through 2016. For large-to-very-large community college districts, the only significant variable is Revenue with p values < .001. The model explained between 89 to 91% of enrollment for large-to-very-large community college districts, dependent upon enrollment period trends. As for similarities or differences among variables based on community college district size, the largest magnitude of the difference was in the means for the All-Transactions House Price Index for small-to-medium community college districts and large-to-very-large community college districts, which was moderate. For small-to-medium community college districts and large-to-very-large community college districts, the magnitude of the difference in the means for the Unemployment rate and Equifax Subprime Credit Population, and Per Capita Personal Income and Estimate of Median Household Income was very small to small. Given the magnitude of difference the multiple regression model indicated for explanation of the aggregated revenue on enrollment based on size, community college administrators and state legislatures should consider community college district size in considering funding and predicting enrollment at a particular institution.

Advisor

Seung Won Yoon

Subject Categories

Education | Educational Administration and Supervision

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