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首页> 外文期刊>Kybernetes: The International Journal of Systems & Cybernetics >Classification techniques for person-job matching: an illustration using the US army
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Classification techniques for person-job matching: an illustration using the US army

机译:人身匹配的分类技术:以美国陆军为例

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摘要

This paper presents the case for personnel systems based on maximizing the differential information gathered about individual abilities and their match to jobs. In the context of assignment to multiple jobs, such systems are shown to be more effective than those based on the currently dominant paradigm of maximizing predictive validity. The latter paradigm favours the measurement of general cognitive ability over multiple specific aptitudes. Recent differential approaches use computer simulation modelling of alternative hypothetical systems to evaluate potential efficiency. The paper reviews the theoretical background on the structure of human abilities which has led to these contrasting approaches to personnel system design, and presents evidence, based on the US Army selection and classification system, in support of the alternative approach. Individual test/aptitude profiles improve the efficiency of personnel selection and classification as well as academic, vocational and career counselling. They also provide a broader potentially fairer definition of talent than a unidimensional indicator of cognitive ability, and a foundation for the design of learning and decision environments around learner and user profiles.
机译:本文介绍了基于最大程度地收集有关个人能力及其与工作匹配的差异信息的人事系统的案例。在分配给多个工作的情况下,这种系统显示出比基于当前占主导地位的最大化预测效度范式的系统更有效。后一种范式倾向于对一般认知能力的测量,而不是对多种特定能力的测量。最近的差分方法使用替代假设系统的计算机仿真模型来评估潜在效率。这篇论文回顾了人类能力结构的理论背景,这导致了这些相反的人事系统设计方法,并在美国陆军选择和分类系统的基础上提出了支持替代方法的证据。个性化的测试/能力配置文件可提高人员选拔和分类以及学术,职业和职业咨询的效率。与认知能力的一维指标相比,它们还为人才提供了更广泛,更公平的定义,并为围绕学习者和用户个人资料设计学习和决策环境奠定了基础。

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