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评估呼吸治疗专业申请者的非认知领域:基于梅西克框架对多重迷你面试的评价

Assessing noncognitive domains of respiratory therapy applicants: Messick's framework appraisal of the multiple mini-interview.

作者信息

Zaccagnini Marco

机构信息

Department of Anesthesia & Critical Care, McGill University Health Centre, Montréal, QC, Canada.

出版信息

Can J Respir Ther. 2019 Mar 13;55:31-35. doi: 10.29390/cjrt-2019-002. eCollection 2019.

DOI:10.29390/cjrt-2019-002
PMID:31297445
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6591782/
Abstract

Educators who assess incoming applicants into a health professional training program are looking for a wide array of cognitive and noncognitive skills that best predict success in the program and as a future practicing professional. While aptitude tests generally measure cognitive skills, noncognitive constructs are more difficult to measure appropriately. The traditional method of measuring noncognitive constructs has been the panel interview. Panel interviews have been described as inconsistent in measuring noncognitive domains and consistently reported as unreliable and susceptible to bias. An alternate interview method used in many health professions schools is the multiple mini-interview (MMI) that was specifically designed to assess noncognitive domains in health professions education. This paper discusses the purpose of using the MMI, how the MMI is conducted, specific domains of focus for the MMI, and the feasibility of creating an MMI. Finally, the paper uses Messick's framework on validity to guide the consideration of the MMI.

摘要

评估进入健康专业培训项目的申请者的教育工作者正在寻找一系列广泛的认知和非认知技能,这些技能能够最好地预测在该项目中以及未来作为执业专业人员的成功。虽然能力倾向测试通常衡量认知技能,但非认知结构更难进行适当测量。测量非认知结构的传统方法是小组面试。小组面试在测量非认知领域方面被描述为不一致,并且一直被报告为不可靠且容易受到偏见影响。许多健康专业学校使用的另一种面试方法是多重迷你面试(MMI),它专门设计用于评估健康专业教育中的非认知领域。本文讨论了使用MMI的目的、MMI的实施方式、MMI的具体关注领域以及创建MMI的可行性。最后,本文使用梅西克的效度框架来指导对MMI的考量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b05/6591782/1d49015aa6a3/cjrt-2019-002-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b05/6591782/1d49015aa6a3/cjrt-2019-002-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b05/6591782/1d49015aa6a3/cjrt-2019-002-g001.jpg