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Designing Item Pools for Adaptive Testing

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Part of the book series: Statistics for Social and Behavioral Sciences ((SSBS))

Abstract

In existing adaptive testing programs, each successive item in the test is chosen to optimize an objective. Examples of well-known objectives aremaximizing the information in the test at the ability estimate for the test taker or minimizing the deviation of its information froma target value at the estimate. In addition, item selection is required to realize a set of content specifications for the test. For example, item content may be required to follow a certain taxonomy or the answer-key distribution for the test must not deviate too much from uniformity. Content specifications are generally defined in terms of combinations of attributes the items in the test should have. They are typically realized by imposing a set of constraints on the item-selection process. The presence of both an objective and a set of constraints in adaptive testing leads to the notion of adaptive testing as constrained (sequential) optimization problem; for a more formal introduction to this notion, see van der Linden (this volume, chap. 2).

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Veldkamp, B.P., van der Linden, W.J. (2009). Designing Item Pools for Adaptive Testing. In: van der Linden, W., Glas, C. (eds) Elements of Adaptive Testing. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-0-387-85461-8_12

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