Computerized adaptive testing (CAT) is the redesign of psychological and educational measuring instruments for delivery by interactive computers. CAT can be used for tests of ability or achievement and for measures of personality and attitudinal variables. Its objective is to select, for each examinee, the set of test questions from a pre-calibrated item bank that simultaneously most effectively and efficiently measures that person on the trait.
The First Adaptive Test: Binet's IQ Test
A Computer-Delivered More Efficient Variation of the Binet Test
CAT Using Item Response Theory
Non-IRT Approaches to CAT
Not all approaches to CAT use IRT. When a test is being used to classify an examinee, the problem can be approached from an IRT perspective or from a decision theory perspective. For example, Lawrence Rudner has proposed a measurement decision theory (MDT) approach to making mastery or other dichotomous classification decisions. His MDT Web site describes how this approach works and provides an interactive tutorial on MDT, as well as other resources and references on MDT and related issues.