01583nas a2200133 4500008003900000245012700039210006900166300001200235490000700247520111200254100001701366700001301383856005301396 2013 d00aThe Application of the Monte Carlo Approach to Cognitive Diagnostic Computerized Adaptive Testing With Content Constraints0 aApplication of the Monte Carlo Approach to Cognitive Diagnostic a482-4960 v373 a
The Monte Carlo approach which has previously been implemented in traditional computerized adaptive testing (CAT) is applied here to cognitive diagnostic CAT to test the ability of this approach to address multiple content constraints. The performance of the Monte Carlo approach is compared with the performance of the modified maximum global discrimination index (MMGDI) method on simulations in which the only content constraint is on the number of items that measure each attribute. The results of the two simulation experiments show that (a) the Monte Carlo method fulfills all the test requirements and produces satisfactory measurement precision and item exposure results and (b) the Monte Carlo method outperforms the MMGDI method when the Monte Carlo method applies either the posterior-weighted Kullback–Leibler algorithm or the hybrid Kullback–Leibler information as the item selection index. Overall, the recovery rate of the knowledge states, the distribution of the item exposure, and the utilization rate of the item bank are improved when the Monte Carlo method is used.
1 aMao, Xiuzhen1 aXin, Tao uhttp://apm.sagepub.com/content/37/6/482.abstract