Retention as Predicted by a Student Profile at a Hispanic Serving Institution

Autor/in	Silvas, Rebeka A.
Titel	Retention as Predicted by a Student Profile at a Hispanic Serving Institution
Quelle	(2017), (105 Seiten) PDF als Volltext Verfügbarkeit Ed.D. Dissertation, Texas A&M University - Corpus Christi
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
ISBN	978-0-3555-9568-0
Schlagwörter	Hochschulschrift; Dissertation; Academic Persistence; College Students; Predictor Variables; Age Differences; Gender Differences; Racial Differences; Ethnicity; College Admission; High School Students; Grade Point Average; Scores; College Entrance Examinations; Correlation; Hispanic American Students; ACT Assessment; SAT (College Admission Test) + Suchen Sie Ihr Suchwort? Thesis; Dissertations; Academic thesis; Collegestudent; Prädiktor; Age; Difference; Age difference; Altersunterschied; Geschlechterkonflikt; Rassenunterschied; Ethnizität; Hochschulzugang; Hochschulzulassung; Zulassung; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Aufnahmeprüfung; Korrelation; Hispanic; Hispanic Americans; Hispanoamerikaner; Assessment; Eignungsprüfung; Eignungstest
Abstract	Retention is high on the list of priorities for both college and university administrators, as well as policy makers. It raises the question what high school data are known before a student attends a college that are predictive of student retention? This study examined 3445 first-time-in-college students from three academic years. Predictors included, age, gender, ethnicity, admission status, high school GPA, ranking percentile, and ACT/SAT scores. The outcome variable was college retention. Data analyses involved chi-square of independence and logistic regression. Results indicated ranking percentile, ACT/SAT scores, and admission status were statistically significant for retention. However, the relationships were weak and the model did not increase predictive values for retention. Although some demographic information and pre-college variables can predict retention, the type of predictors needs to expand to provide a stronger predictive model. Admissions processes may need to consider non-traditional information to include for both admissions and retention prediction. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01