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模式识别作为国家执业资格考试中多项选择题的一种理念。

Pattern recognition as a concept for multiple-choice questions in a national licensing exam.

作者信息

Freiwald Tilo, Salimi Madjid, Khaljani Ehsan, Harendza Sigrid

机构信息

Department of Internal Medicine, University Hospital Hamburg-Eppendorf, Martinistr, 52, 20246 Hamburg, Germany.

出版信息

BMC Med Educ. 2014 Nov 14;14:232. doi: 10.1186/1472-6920-14-232.

Abstract

BACKGROUND

Multiple-choice questions (MCQ) are still widely used in high stakes medical exams. We wanted to examine whether and to what extent a national licensing exam uses the concept of pattern recognition to test applied clinical knowledge.

METHODS

We categorized all 4,134 German National medical licensing exam questions between October 2006 and October 2012 by discipline, year, and type. We analyzed questions from the four largest disciplines: internal medicine (n = 931), neurology (n = 305), pediatrics (n = 281), and surgery (n = 233), with respect to the following question types: knowledge questions (KQ), pattern recognition questions (PRQ), inverse PRQ (IPRQ), and pseudo PRQ (PPRQ).

RESULTS

A total 51.1% of all questions were of a higher taxonomical order (PRQ and IPRQ) with a significant decrease in the percentage of these questions (p <0.001) from 2006 (61.5%) to 2012 (41.6%). The proportion of PRQs and IPRQs was significantly lower (p <0.001) in internal medicine and surgery, compared to neurology and pediatrics. PRQs were mostly used in questions about diagnoses (71.7%). A significantly higher (p <0.05) percentage of PR/therapy questions was found for internal medicine compared with neurology and pediatrics.

CONCLUSION

The concept of pattern recognition is used with different priorities and to various extents by the different disciplines in a high stakes exam to test applied clinical knowledge. Being aware of this concept may aid in the design and balance of MCQs in an exam with respect to testing clinical reasoning as a desired skill at the threshold of postgraduate medical education.

摘要

背景

多项选择题(MCQ)仍广泛应用于高风险的医学考试中。我们想要研究一项国家执业资格考试是否以及在多大程度上运用模式识别概念来测试应用临床知识。

方法

我们将2006年10月至2012年10月期间德国国家医学执业资格考试的所有4134道题目按学科、年份和类型进行分类。我们分析了四个最大的学科(内科,n = 931;神经科,n = 305;儿科,n = 281;外科,n = 233)的题目,涉及以下题型:知识题(KQ)、模式识别题(PRQ)、反向模式识别题(IPRQ)和伪模式识别题(PPRQ)。

结果

所有题目中,共有51.1%属于较高分类层次(PRQ和IPRQ),从2006年(61.5%)到2012年(41.6%),这些题目的比例显著下降(p <0.001)。与神经科和儿科相比,内科和外科中PRQ和IPRQ的比例显著更低(p <0.001)。PRQ大多用于诊断相关题目(71.7%)。与神经科和儿科相比,内科中PR/治疗相关题目的比例显著更高(p <0.05)。

结论

在一项高风险考试中,不同学科以不同的优先级和不同程度运用模式识别概念来测试应用临床知识。了解这一概念可能有助于在考试中设计和平衡多项选择题,以测试临床推理这一研究生医学教育入门阶段所需的技能。

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