South Western Sydney Clinical School, Faculty of Medicine, University of New South Wales, Sydney, Australia.
BMC Med Educ. 2014 Apr 23;14:86. doi: 10.1186/1472-6920-14-86.
This paper is an evaluation of an integrated selection process utilising previous academic achievement [Universities Admission Index (UAI)], a skills test [Undergraduate Medicine and Health Sciences Admission Test (UMAT)], and a structured interview, introduced (in its entirety) in 2004 as part of curriculum reform of the undergraduate Medicine Program at the University of New South Wales (UNSW), Australia. Demographic measures of gender, country of birth, educational background and rurality are considered.
Admission scores and program outcomes of 318 students enrolled in 2004 and 2005 were studied. Regression analyses were undertaken to determine whether selection scores predicted overall, knowledge-based and clinical-based learning outcomes after controlling for demographics.
UAI attained the highest values in predicting overall and knowledge-based outcomes. The communication dimension of the interview achieved similar predictive values as UAI for clinical-based outcomes, although predictive values were relatively low. The UMAT did not predict any performance outcome. Female gender, European/European-derived country of birth and non-rurality were significant predictors independent of UAI scores.
Results indicate promising validity for an integrated selection process introduced for the Medicine Program at UNSW, with UAI and interview predictive of learning outcomes. Although not predictive, UMAT may have other useful roles in an integrated selection process. Further longitudinal research is proposed to monitor and improve the validity of the integrated student selection process.
本文评估了一种综合选拔流程,该流程综合利用了先前的学术成绩[大学入学指数(UAI)]、一项技能测试[本科医学与健康科学入学考试(UMAT)]和结构化面试,该流程于 2004 年作为澳大利亚新南威尔士大学(UNSW)本科医学课程课程改革的一部分引入(完整引入)。考虑了性别、出生地、教育背景和农村背景等人口统计学指标。
研究了 2004 年和 2005 年入学的 318 名学生的入学成绩和课程成绩。进行回归分析,以确定在控制人口统计学因素的情况下,选拔成绩是否可以预测整体、基于知识和基于临床的学习成绩。
UAI 在预测整体和基于知识的成绩方面得分最高。面试的沟通维度与 UAI 对临床成绩的预测具有相似的预测值,尽管预测值相对较低。UMAT 不能预测任何表现结果。女性、欧洲/欧洲血统的出生地和非农村背景是独立于 UAI 分数的重要预测因素。
结果表明,UNSW 医学课程采用的综合选拔流程具有良好的有效性,UAI 和面试可预测学习成绩。虽然 UMAT 不具有预测性,但它在综合选拔流程中可能具有其他有用的作用。建议进行进一步的纵向研究,以监测和提高综合学生选拔流程的有效性。