Lynagh Marita, Kelly Brian, Horton Graeme, Walker Ben, Powis David, Bore Miles, Munro Donald, Symonds Ian, Jones Graham, Nagle Amanda, Regan Tim, McElduff Patrick, David Michael
University of Newcastle.
University of New England.
MedEdPublish (2016). 2017 Mar 9;6:42. doi: 10.15694/mep.2017.000042. eCollection 2017.
This article was migrated. The article was marked as recommended. 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. 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%). 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. 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.
本文已迁移。该文章被标记为推荐文章。关于选拔医学生的“最佳”方法仍存在诸多争议。本研究旨在评估四种不同选拔工具对本科一年级医学生学业成绩结果的预测效度。对以往学业成绩的录取分数——澳大利亚高等教育入学排名（ATAR）、本科医学与健康科学入学考试（UMAT）、多站迷你面试（MMI）和个人素质评估（PQA）与四个学生队列（N = 604，90%）在一年级选择题、简答题、客观结构化临床考试（OSCE）和基于问题的学习（PBL）导师评分中的学生成绩进行了回归分析。发现所有四种选拔工具与本科医学一年级学生成绩的一项或多项指标均存在显著的预测关联。UMAT、ATAR和MMI分数始终能预测一年级多项成绩结果。ATAR是唯一能预测总体取得满意进步可能性的选拔工具。所有四种选拔工具在预测一年级医学生学业成绩方面都发挥了作用。需要进一步研究以评估选拔工具预测医学后期成绩的效度。
