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|Title:||Have we got the selection process right? The validity of selection tools for predicting academic performance in the first year of undergraduate medicine||Contributor(s):||Lynagh, Marita (author); Kelly, Brian (author); Regan, Tim (author); McElduff, Patrick (author); David, Michael (author); Horton, Graeme (author); Walker, Ben (author); Powis, David (author); Bore, Miles (author); Munro, Donald (author); Symonds, Ian (author); Jones, Graham L (author) ; Nagle, Amanda (author)||Publication Date:||2017||Open Access:||Yes||DOI:||10.15694/mep.2017.000042||Handle Link:||https://hdl.handle.net/1959.11/20772||Open Access Link:||http://dx.doi.org/10.15694/mep.2017.000042||Abstract:||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.||Publication Type:||Journal Article||Source of Publication:||MedEdPublish, 6(1), p. 1-14||Publisher:||Association for Medical Education in Europe||Place of Publication:||United Kingdom||ISSN:||2312-7996||Field of Research (FOR):||119999 Medical and Health Sciences not elsewhere classified||Peer Reviewed:||Yes||HERDC Category Description:||C1 Refereed Article in a Scholarly Journal||Statistics to Oct 2018:||Visitors: 54
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