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Modeling the Psychometric Properties of Complex Performance Assessment Tasks Using Confirmatory Factor Analysis: A Multistage Model for Calibrating Tasks

机译:使用验证性因子分析对复杂绩效评估任务的心理计量学特性建模:用于校准任务的多阶段模型

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Item-level information, such as difficulty and discrimination are invaluable to the test assembly, equating, and scoring practices. Estimating these parameters within the context of large-scale performance assessments is often hindered by the use of unbalanced designs for assigning examinees to tasks and raters because such designs result in very sparse data matrices. This article addresses some of the issues using a multistage confirmatory factor analytic approach. The approach is illustrated using data from a performance test in medicine for which examinees encounter multiple patients with medical problems (tasks), with each problem portrayed by a different trained patient (rater). A series of models was fit to rating data (1) to obtain alternative task difficulty and discrimination parameters and (2) to evaluate the observed improvement in the goodness of model fit due to accounted rater and test site effects. The results suggest that availability of alternative task parameter estimates can be useful in practice for making decisions related to task banking, rater training, and test assembly.View full textDownload full textRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/08957347.2012.635510
机译:项目级别的信息(例如难度和辨别力)对于测试程序集,等同性和计分方法来说是无价的。在大型绩效评估的背景下估计这些参数通常会因使用不平衡设计来将考生分配给任务和评估者而受到阻碍,因为此类设计会导致数据矩阵非常稀疏。本文使用多阶段验证性因素分析方法解决了一些问题。使用来自医学性能测试的数据来说明该方法,针对该测试,考生遇到多个患有医学问题(任务)的患者,每个问题都由不同的受过训练的患者(评估者)描述。一系列模型适合于评级数据(1)获得替代的任务难度和判别参数,以及(2)评估由于考虑到评估者和测试地点的影响而在模型拟合优度方面观察到的改善。结果表明,替代任务参数估计值的可用性在实践中对于与任务银行,评估师培训和测试程序集相关的决策很有用。查看全文下载全文相关的var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,service_compact: “ citeulike,netvibes,twitter,technorati,美味,linkedin,facebook,stumbleupon,digg,google,更多”,发布:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/08957347.2012.635510

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