Detection of Known Items in Adaptive Testing with a Statistical Quality Control Method

Wim J. J. Veerkamp · Cees A. W. Glas

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Psychometric Methodologies and Testing Educational Assessment and Pedagogy Educational Technology and Assessment

Abstract

Due to previous exposure of items in adaptive testing, items may become known to a substantial portion of examinees. A disclosed item is bound to show drift in the item parameter values. In this paper it is suggested to use a statistical quality control method for the detection of known items. The method is worked out in detail for the 1-PL and 3-PL models. Adaptive test data are used to re-estimate the item parameters, and these estimates are used in a test of parameter drift. The method is illustrated in a number of simulation studies, including a power study.

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References

1992Introduction to Statistical Quality Control 2012Applications of Item Response Theory To Practical Testing Problems 1989Weighted Likelihood Estimation of Ability in Item Response Theory 1995Rasch models: foundations, recent developments and applications 1994Methods for Identifying Biased Test Items 1986Bayes Modal Estimation in Item Response Models 1986DIFFERENTIAL ITEM FUNCTIONING AND THE MANTEL‐HAENSZEL PROCEDURE 1989Procedures for Selecting Items for Computerized Adaptive Tests

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2013Monitoring Scale Scores over Time via Quality Control Charts, Model-Based Approaches, and Time Series Techniques 2019The use of item scores and response times to detect examinees who may have benefited from item preknowledge 2004Detection of Item Parameter Drift over Multiple Test Administrations 2022A practical application of statistical process control to evaluate the performance rate of academic programmes: implications and suggestions

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