Have we got the selection process right? The validity of selection tools for predicting academic performance in the first year of undergraduate medicine
| Autor: | Amanda Nagle, Patrick McElduff, Graham L. Jones, Michael David, Brian Kelly, Marita Lynagh, David Powis, Ben Walker, Ian Symonds, Tim Regan, Miles Bore, Donald Munro, Graeme Horton |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Medical education
lcsh:LC8-6691 020205 medical informatics lcsh:Special aspects of education business.industry Process (engineering) education lcsh:R lcsh:Medicine 06 humanities and the arts 02 engineering and technology 0603 philosophy ethics and religion admissions 0202 electrical engineering electronic engineering information engineering Medicine 060301 applied ethics business Selection Selection (genetic algorithm) |
| Zdroj: | MedEdPublish, Vol 6, Iss 1 (2017) |
| ISSN: | 2312-7996 |
| Popis: | This article was migrated. The article was marked as recommended. Content: There remains much debate over the 'best' method for selecting students in to medicine. This study aimed to assess the predictive validity of four different selection tools with academic performance outcomes in first-year undergraduate medical students. Methods: Regression analyses were conducted between admission scores on previous academic performance - the Australian Tertiary Admission Rank (ATAR), the Undergraduate Medicine and Health Sciences Admission Test (UMAT), Multiple-Mini Interview (MMI) and the Personal Qualities Assessment (PQA) with student performance in first-year assessments of Multiple Choice Questions, Short Answer Questions, Objective Structured Clinical Examinations (OSCE) and Problem-Based Learning (PBL) Tutor ratings in four cohorts of students (N = 604, 90%). Results: All four selection tools were found to have significant predictive associations with one or more measures of student performance in Year One of undergraduate medicine. UMAT, ATAR and MMI scores consistently predicted first year performance on a number of outcomes. ATAR was the only selection tool to predict the likelihood of making satisfactory progress overall. Conclusions: All four selection tools play a contributing role in predicting academic performance in first year medical students. Further research is required to assess the validity of selection tools in predicting performance in the later years of medicine. |
| Databáze: | OpenAIRE |
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