The Effects of Item Calibration Sample Size and Item Pool Size on Adaptive Testing

A simulation study of the effects of varying the item calibration sample size on varying size item pools was run for the maximum information adap-tive test. Items were calibrated on the three-pa-rameter logistic model on sample sizes of 500, 1,000, and 2,000. Item pools of 100, 200, or 300 items were developed from the three calibration sample sizes. Fixed-length adaptive tests of 10, 15, 20, 25, 30, and 35 items were given to a different group of 500 simulated subjects for each combina-tion of item pool size and calibration sample size. Results indicated that high correlations between ability and estimated ability would be obtained in any testing if a sufficient number of items were ad-ministered. The reduction of absolute error of abil-ity estimation was found to require at least 200 items calibrated on 2,000 subjects. Adaptive, or tailored, testing refers to a series of techniques for finding and scoring the most useful set of items to be administered to an indi-vidual. Adaptive testing techniques range from strictly mechanical (Weiss, 1973) to mathemati-cally elegant models (Owen, 1969). In all these techniques, the basic components are pa-rameters representing the items, some method for ability estimation, a method for item selec-tion, and rules for the initiation and termination of testing. Development of item pools can b