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Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1
Student applications for admission to the University of Georgia College of Veterinary Medicine include the following information: undergraduate grade point average (GPA), GPA in science courses (GPAScience), GPA for the last 45 credit hours (GPALast45hrs), results for the Graduate Record Examination...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7559586/ https://www.ncbi.nlm.nih.gov/pubmed/32872392 http://dx.doi.org/10.3390/vetsci7030120 |
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author | Holladay, Steven D. Gogal, Robert M. Moore, Parkerson C. Tuckfield, R. Cary Burgess, Brandy A. Brown, Scott A. |
author_facet | Holladay, Steven D. Gogal, Robert M. Moore, Parkerson C. Tuckfield, R. Cary Burgess, Brandy A. Brown, Scott A. |
author_sort | Holladay, Steven D. |
collection | PubMed |
description | Student applications for admission to the University of Georgia College of Veterinary Medicine include the following information: undergraduate grade point average (GPA), GPA in science courses (GPAScience), GPA for the last 45 credit hours (GPALast45hrs), results for the Graduate Record Examination Quantitative and Verbal Reasoning Measures (GRE-QV), results for the GRE Analytical Writing Measure (GRE-AW), and grades received for 10 required prerequisite courses. In addition, three faculty members independently review and score subjective information in applicants’ files (FileScore). The admissions committee determines a composite Admission Score (AdmScore), which is based on GPA, GPAScience, GPALast45hrs, GRE-QV, GRE-AW, and the FileScore. The AdmScore is generally perceived to be a good predictor of class rank at the end of year 1 (CREY1). However, this has not been verified, nor has it been determined which components of the AdmScore have the strongest correlation with CREY1. The present study therefore compared each component of the AdmScore for correlation with CREY1, for the three classes admitted in 2015, 2016 and 2017 (Class15, Class16, Class17). Results suggest that only a few components of the application file are needed to make strong predictive statements about the academic success of veterinary students during the first year of the curriculum. |
format | Online Article Text |
id | pubmed-7559586 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75595862020-10-29 Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1 Holladay, Steven D. Gogal, Robert M. Moore, Parkerson C. Tuckfield, R. Cary Burgess, Brandy A. Brown, Scott A. Vet Sci Article Student applications for admission to the University of Georgia College of Veterinary Medicine include the following information: undergraduate grade point average (GPA), GPA in science courses (GPAScience), GPA for the last 45 credit hours (GPALast45hrs), results for the Graduate Record Examination Quantitative and Verbal Reasoning Measures (GRE-QV), results for the GRE Analytical Writing Measure (GRE-AW), and grades received for 10 required prerequisite courses. In addition, three faculty members independently review and score subjective information in applicants’ files (FileScore). The admissions committee determines a composite Admission Score (AdmScore), which is based on GPA, GPAScience, GPALast45hrs, GRE-QV, GRE-AW, and the FileScore. The AdmScore is generally perceived to be a good predictor of class rank at the end of year 1 (CREY1). However, this has not been verified, nor has it been determined which components of the AdmScore have the strongest correlation with CREY1. The present study therefore compared each component of the AdmScore for correlation with CREY1, for the three classes admitted in 2015, 2016 and 2017 (Class15, Class16, Class17). Results suggest that only a few components of the application file are needed to make strong predictive statements about the academic success of veterinary students during the first year of the curriculum. MDPI 2020-08-29 /pmc/articles/PMC7559586/ /pubmed/32872392 http://dx.doi.org/10.3390/vetsci7030120 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Holladay, Steven D. Gogal, Robert M. Moore, Parkerson C. Tuckfield, R. Cary Burgess, Brandy A. Brown, Scott A. Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1 |
title | Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1 |
title_full | Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1 |
title_fullStr | Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1 |
title_full_unstemmed | Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1 |
title_short | Predictive Value of Veterinary Student Application Data for Class Rank at End of Year 1 |
title_sort | predictive value of veterinary student application data for class rank at end of year 1 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7559586/ https://www.ncbi.nlm.nih.gov/pubmed/32872392 http://dx.doi.org/10.3390/vetsci7030120 |
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