A data-based model to predict case classification of educational attainment in Central Appalachia

Date of Award

2016

Degree Name

Ph.D. in Educational Leadership

Department

Department of Educational Leadership

Advisor/Chair

Advisor: Barbara M. De Luca

Abstract

The purpose of this study was to develop a data-based model to predict case classification of students' educational attainment levels into one of three categories: will not enroll in post-secondary education; will enroll in, but not complete a bachelor's degree; and will enroll in and complete a bachelor's degree. Using a nationally representative longitudinal study, Educational Longitudinal Study of 2002, as a training dataset for this study it was possible to develop a data-based model that can be used to correctly predict future case classification. This study applies these analyses to an under studied population in central Appalachia. Central Appalachia has a semi-homogenous history, economy, challenges, attitudes, and educational attainment rates. Central Appalachia was chosen because it has recently been noted that it is an area of particular concern" by the Appalachian Regional Commission, a U.S. government agency."

Keywords

Appalachians (People) Education, Education Demographic aspects, High school graduates Appalachian Region, College dropouts Appalachian Region, College students Appalachian Region, Education, Higher, Education, Public Policy, Economics, Appalachia, Educational Attainment, Economy, Discriminant Model, Quantitative

Rights Statement

Copyright © 2016, author

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