A Comparison of the Three Adaptive Testing Strategies Using Microcat

Author: Rong-Guey Ho (Department of Information and Computer Education)

Abstract：

The purpose of this study was to investigate the empirical performance of the three adaptive strategies. The following conclusions emerged from the data analyses: (1) The modal-Bayesian strategy was the most efficient one among the strategies used. The Bayesian strategy, however, yielded much reliable ability estimates. The maximum likelihood strategy was found to be inconsistent under most testing situations. (2) The effect, of selected bank sizes seemed minimum except in the low ability level where the starting point was higher than the true ability of the examinee. Under this condition, a bank size of 86 items using a maximum number of 22 items as the termination criterion was insufficient to differentiate the benefits of the selected strategies. (3) More accurate estimate of the ability could be obtained if the starting point was equal to or lower than the true ability of the examinee. (4) There were interactions between bank type and the adaptive testing strategy, and between bank type and ability level. Using the bank with the easiest items, the performance of the maximum likelihood strategy improved substantially, especially in the low ability level. However, the performance of the other strategies was still better. (5) The differences between the statistical characteristics of never-selected items and frequently-selected items were relatively small.

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