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Predicting Graduation Rates at Non-Residential Research Universities

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Date Issued:
2016
Summary:
The purpose of this study was to develop a prediction model for graduation rate at non-residential research universities. As well, this study investigated, described, and compared the student characteristics of non-residential and residential institutions. Making distinctions between significant predictor variables at non-residential research universities and significant predictor variables at residential institutions was also an aim. The researcher obtained data from the Integrated Postsecondary Data System. Student and institutional variables were analyzed using descriptive statistics, independent samples t-tests, analysis of variance, and regression analyses. Results indicated that student and institutional characteristics can be used to significantly predict graduation rate at nonresidential institutions with student variables yielding greater predictive power than institutional variables. As well, residential status was found to moderate the relationship between undergraduate enrollment and graduation rate.
Title: Predicting Graduation Rates at Non-Residential Research Universities.
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Name(s): Harrison, Jamonique K., author
Floyd, Deborah L., Thesis advisor
Laanan, Frankie Santos, Thesis advisor
Florida Atlantic University, Degree grantor
College of Education
Department of Educational Leadership and Research Methodology
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2016
Date Issued: 2016
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 182 p.
Language(s): English
Summary: The purpose of this study was to develop a prediction model for graduation rate at non-residential research universities. As well, this study investigated, described, and compared the student characteristics of non-residential and residential institutions. Making distinctions between significant predictor variables at non-residential research universities and significant predictor variables at residential institutions was also an aim. The researcher obtained data from the Integrated Postsecondary Data System. Student and institutional variables were analyzed using descriptive statistics, independent samples t-tests, analysis of variance, and regression analyses. Results indicated that student and institutional characteristics can be used to significantly predict graduation rate at nonresidential institutions with student variables yielding greater predictive power than institutional variables. As well, residential status was found to moderate the relationship between undergraduate enrollment and graduation rate.
Identifier: FA00004603 (IID)
Degree granted: Dissertation (Ph.D.)--Florida Atlantic University, 2016.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Dropout behavior, Prediction of
College dropouts--Prevention.
Education--Research--Philosophy.
Education, Higher--Administration.
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Links: http://purl.flvc.org/fau/fd/FA00004603
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00004603
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.