This brief overview notes that an adaptive test differs from standardized achievement tests in that it does not consist of a certain set of items that are administered to a group of examinees. Instead, the test is individualized for each examinee. The items administered to the examinee are selected from a large pool of items on the basis of the correctness of the examinee's previous responses. Several steps are involved in constructing a computerized adaptive test (CAT): (1) the item pool must be developed; (2) some item characteristics must be calculated for each item; and (3) a strategy for deleting items from the item pool must be chosen, along with a scoring procedure. Latent trait theory assumes that an underlying trait is the sole determinant of an examinee's responses to test items, and that performance on an item is governed by two factors: the examinee's ability and the item's difficulty. Several item selection strategies have been developed, including the Robbins Monro procedure, fixed step size, the flexilevel method, the Bayesian approach, and the stratified-adaptive approach. Advantages of CAT are its increased efficiency, optimization of the difficulty level of the test for each examinee, and administration convenience. The most obvious constraint on the use of CAT is the problem of availability of appropriate computer hardware and software. (LMO)