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EXAMINING STATISTICAL MODELS TO PREDICT ACADEMIC SUCCESS IN EARLY COLLEGE USING MIDDLE SCHOOL DATA
| Title: | EXAMINING STATISTICAL MODELS TO PREDICT ACADEMIC SUCCESS IN EARLY COLLEGE USING MIDDLE SCHOOL DATA. |
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| Name(s): |
Timar, Agnes A. , author Vaughan, Michelle , Thesis advisor Florida Atlantic University, Degree grantor Department of Curriculum, Culture, and Educational Inquiry College of Education |
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| Type of Resource: | text | |
| Genre: | Electronic Thesis Or Dissertation | |
| Date Created: | 2023 | |
| Date Issued: | 2023 | |
| Publisher: | Florida Atlantic University | |
| Place of Publication: | Boca Raton, Fla. | |
| Physical Form: | application/pdf | |
| Extent: | 191 p. | |
| Language(s): | English | |
| Abstract/Description: | The study explored whether middle school students’ select academic (grade point average [GPA], Accuplacer mathematics, reading, and writing scores, admission interview scores) and non-academic characteristics (race, ethnicity, the middle school they attended, their gender, their parents’ educational level) have any predictive power with regard to their success at an early college high school. This study compared binary logistic regression (BLR) and predictive discriminant analysis (PDA) statistical models. First-year early college academic success can be predicted using BLR and only six input factors from middle school (Accuplacer math scores, interview scores, gender, and race, as three dummy variables) with a 91% accuracy. However, a student academic success prediction model using middle school data for a student’s first year college success could not be built. This finding asserts Astin’s Student Development Theory (1993, 1999a, 1999b), the theoretical framework that guided this study, that students can grow and improve over time and educators need to focus on cultivating and developing students’ smartness through high level instruction and coaching instead of identifying and celebrating smartness by accepting only the most prospective students into colleges (Astin, 1977, 1993, 1999a, 2017, 2018). | |
| Identifier: | FA00014161 (IID) | |
| Degree granted: | Dissertation (PhD)--Florida Atlantic University, 2023. | |
| Collection: | FAU Electronic Theses and Dissertations Collection | |
| Note(s): | Includes bibliography. | |
| Subject(s): |
Prediction of scholastic success Middle school education Universities and colleges--Admission |
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| Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00014161 | |
| 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. |
