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认知测试中准确性和置信度测量的拉施模型

Rasch modeling of accuracy and confidence measures from cognitive tests.

作者信息

Paek Insu, Lee Jihyun, Stankov Lazar, Wilson Mark

机构信息

Educational Psychology and Learning Systems, Florida State University, Tallahassee, FL 32306-4453, USA.

出版信息

J Appl Meas. 2013;14(3):232-48.

PMID:23816612
Abstract

The use of IRT models has not been rigorously applied in studies of the relationship between test-takers' confidence and accuracy. This study applied the Rasch measurement models to investigate the relationship between test-takers' confidence and accuracy on English proficiency tests, proposing potentially useful measures of under or overconfidence. The Rasch approach provided the scaffolding to formulate indices that can assess the discrepancy between confidence and accuracy at the item or total test level, as well as at particular ability levels locally. In addition, a "disattenuated" measure of association between accuracy and confidence, which takes measurement error into account, was obtained through a multidimensional Rasch modeling of the two constructs where the latent variance-covariance structure is directly estimated from the data. The results indicate that the participants tend to show overconfidence bias in their own cognitive abilities.

摘要

IRT模型尚未被严格应用于研究考生信心与准确性之间的关系。本研究应用Rasch测量模型来调查考生在英语水平测试中的信心与准确性之间的关系,提出了可能有用的过度自信或信心不足的测量方法。Rasch方法提供了框架,以制定能够在项目或总体测试水平以及局部特定能力水平上评估信心与准确性之间差异的指标。此外,通过对两个结构进行多维Rasch建模,获得了一个考虑测量误差的准确性与信心之间的“去衰减”关联度量,其中潜在方差协方差结构直接从数据中估计。结果表明,参与者在自身认知能力方面往往表现出过度自信偏差。

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