Replenishing item pools for on-line ability testing requires innovative and efficient data collection. A method is proposed to collect test item calibration data in an on-line testing environment sequentially using locally D-optimum designs, thereby achieving high Fisher information for the item parameters. (SLD)

A practical application of generalizability theory, demonstrating how the variance components contribute to understanding and interpreting the data collected to evaluate a program, is described. The evaluation concerned 120 learning modules developed for the Dental Auxiliary Education Project. The goals of the project were to design, implement,…