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Early identification of struggling learners: using prematriculation and early academic performance data

INTRODUCTION: A perennial difficultly for remediation programmes in medical school is early identification of struggling learners so that resources and assistance can be applied as quickly as is practical. Our study investigated if early academic performance has predictive validity above and beyond...

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Autores principales: Bennion, Layne D., Torre, Dario, Durning, Steven J., Mears, David, Schreiber-Gregory, Deanna, Servey, Jessica T, Cruess, David F., Yoon, Michelle, Dong, Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bohn Stafleu van Loghum 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820636/
https://www.ncbi.nlm.nih.gov/pubmed/31562635
http://dx.doi.org/10.1007/s40037-019-00539-2
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author Bennion, Layne D.
Torre, Dario
Durning, Steven J.
Mears, David
Schreiber-Gregory, Deanna
Servey, Jessica T
Cruess, David F.
Yoon, Michelle
Dong, Ting
author_facet Bennion, Layne D.
Torre, Dario
Durning, Steven J.
Mears, David
Schreiber-Gregory, Deanna
Servey, Jessica T
Cruess, David F.
Yoon, Michelle
Dong, Ting
author_sort Bennion, Layne D.
collection PubMed
description INTRODUCTION: A perennial difficultly for remediation programmes in medical school is early identification of struggling learners so that resources and assistance can be applied as quickly as is practical. Our study investigated if early academic performance has predictive validity above and beyond pre-matriculation variables. METHODS: Using three cohorts of medical students, we used logistic regression modelling and negative binomial regression modelling to assess the strength of the relationships between measures of early academic performance and outcomes—later referral to the academic review and performance committee and total module score. RESULTS: We found performance on National Board of Medical Examiners (NBME) exams at approximately 5 months into the pre-clerkship curriculum was predictive of any referral as well as the total number of referrals to an academic review and performance committee during medical school (MS)1, MS2, MS3 and/or MS4 years. DISCUSSION: NBME exams early in the curriculum may be an additional tool for early identification of struggling learners.
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spelling pubmed-68206362019-11-06 Early identification of struggling learners: using prematriculation and early academic performance data Bennion, Layne D. Torre, Dario Durning, Steven J. Mears, David Schreiber-Gregory, Deanna Servey, Jessica T Cruess, David F. Yoon, Michelle Dong, Ting Perspect Med Educ Original Article INTRODUCTION: A perennial difficultly for remediation programmes in medical school is early identification of struggling learners so that resources and assistance can be applied as quickly as is practical. Our study investigated if early academic performance has predictive validity above and beyond pre-matriculation variables. METHODS: Using three cohorts of medical students, we used logistic regression modelling and negative binomial regression modelling to assess the strength of the relationships between measures of early academic performance and outcomes—later referral to the academic review and performance committee and total module score. RESULTS: We found performance on National Board of Medical Examiners (NBME) exams at approximately 5 months into the pre-clerkship curriculum was predictive of any referral as well as the total number of referrals to an academic review and performance committee during medical school (MS)1, MS2, MS3 and/or MS4 years. DISCUSSION: NBME exams early in the curriculum may be an additional tool for early identification of struggling learners. Bohn Stafleu van Loghum 2019-09-27 2019-10 /pmc/articles/PMC6820636/ /pubmed/31562635 http://dx.doi.org/10.1007/s40037-019-00539-2 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Bennion, Layne D.
Torre, Dario
Durning, Steven J.
Mears, David
Schreiber-Gregory, Deanna
Servey, Jessica T
Cruess, David F.
Yoon, Michelle
Dong, Ting
Early identification of struggling learners: using prematriculation and early academic performance data
title Early identification of struggling learners: using prematriculation and early academic performance data
title_full Early identification of struggling learners: using prematriculation and early academic performance data
title_fullStr Early identification of struggling learners: using prematriculation and early academic performance data
title_full_unstemmed Early identification of struggling learners: using prematriculation and early academic performance data
title_short Early identification of struggling learners: using prematriculation and early academic performance data
title_sort early identification of struggling learners: using prematriculation and early academic performance data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820636/
https://www.ncbi.nlm.nih.gov/pubmed/31562635
http://dx.doi.org/10.1007/s40037-019-00539-2
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