Designing item pools to optimize the functioning of a computerized adaptive test

Computerized adaptive testing (CAT) is a testing procedure that can result in improved precision for a specified test length or reduced test length with no loss of precision. However, these attractive psychometric features of CATs are only achieved if appropriate test items are available for administration. This set of test items is commonly called an “item pool.” This paper discusses the optimal characteristics for an item pool that will lead to the desired properties for a CAT. Then, a procedure is described for designing the statistical characteristics of the item parameters for an optimal item pool within an item response theory framework. Because true optimality is impractical, methods for achieving practical approximations to optimality are described. The results of this approach are shown for an operational testing program including comparisons to the results from the item pool currently used in that testing program.