An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

Two methods for estimating the reliability of a computerized adaptive test (CAT) without using item response theory are presented. The data consist of CAT and paper-and-pencil scores from identical or equivalent samples, and scores for all examinees on one or more covariates, using the Armed Services Vocational Aptitude Battery. (TJH)

Proposes an item-selection algorithm for neutralizing the differential effects of time limits on computerized adaptive test scores. Uses a statistical model for distributions of examinees' response times on items in a bank that is updated each time an item is administered. Demonstrates the method using an item bank from the Armed Services…

When the network-flow algorithm (NFA) and the average growth approximation algorithm (AGAA) were used for automated test assembly with American College Test and Armed Services Vocational Aptitude Battery item banks, results indicate that reasonable error in item parameters is not harmful for test assembly using NFA or AGAA. (SLD)

This book documents the research, development, and implementation efforts that allowed the U.S. Department of Defense to initiate the Computerized Adaptive Testing Armed Services Vocational Aptitude Battery Program for enlistment testing. Traces the history of this program over 30 years. (SLD)