A structural equation modeling approach for examining position effects in large-scale assessments

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• 作者：Okan Bulut ; Qi Quo ; Mark J. Gierl
• 关键词：Position effect ; Large ; scale assessment ; Structural equation modeling ; Item response theory
• 刊名：Large-scale Assessments in Education
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：5
• 期：1
• 全文大小：1832KB
• 刊物主题：Assessment, Testing and Evaluation; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law; Educational Policy and Politics;
• 出版者：Springer US
• ISSN：2196-0739
• 卷排序：5

文摘

Position effects may occur in both paper–pencil tests and computerized assessments when examinees respond to the same test items located in different positions on the test. To examine position effects in large-scale assessments, previous studies often used multilevel item response models within the generalized linear mixed modeling framework. Using the equivalence of the item response theory and binary factor analysis frameworks when modeling dichotomous item responses, this study introduces a structural equation modeling (SEM) approach that is capable of estimating various types of position effects. Using real data from a large-scale reading assessment, the SEM approach is demonstrated for investigating form, passage position, and item position effects for reading items. The results from a simulation study are also presented to evaluate the accuracy of the SEM approach in detecting item position effects. The implications of using the SEM approach are discussed in the context of large-scale assessments.