Changes to the design and development of our educational assessments are resulting in the unprecedented demand for a large and continuous supply of content-specific test items. One way to address this growing demand is with automatic item generation (AIG). AIG is the process of using item models to generate test items with the aid of computer…

This paper presents a framework to provide a structured approach for developing score reports for cognitive diagnostic assessments ("CDAs"). Guidelines for reporting and presenting diagnostic scores are based on a review of current educational test score reporting practices and literature from the area of information design. A sample diagnostic…

The purpose of this paper is to define and evaluate the categories of cognitive models underlying at least three types of educational tests. We argue that while all educational tests may be based--explicitly or implicitly--on a cognitive model, the categories of cognitive models underlying tests often range in their development and in the…

In this paper I describe and illustrate the Roussos-Stout (1996) multidimensionality-based DIF analysis paradigm, with emphasis on its implication for the selection of a matching and studied subtest for DIF analyses. Standard DIF practice encourages an exploratory search for matching subtest items based on purely statistical criteria, such as a…

Describes some recent advances in the study of differential group performance and illustrates some of the ways that substantive analyses can be integrated with multidimensional, bundles-based statistical methods using test specifications to organize the analyses. Highlights some future directions for the analysis of differential item functioning.…

Discusses the logic of the rule-space model (K. Tatsuoka, 1983) as it applies to test development and analysis. The rule-space model is a statistical method for classifying examinees' test item responses into a set of attribute-mastery patterns associated with different cognitive skills. Directs readers to a tutorial that may be downloaded. (SLD)