In this simulation study, the classification and agreement of MLE, MAP, and EAP which are methods
to estimate examinees’ ability parameters under the DINA model. For the purpose of ensuring
differentiation from the previous studies, various simulation factors were considered such as quality of test
items, test lengths, ability distributions, correlations among cognitive attributes, and natures of test. The
results showed that the accuracy of estimating each individual cognitive attribute was higher than about
75% in all conditions using any of three methods. It was relatively difficult, however, to accurately
estimate all the cognitive attributes together. Especially, when the number of test items is small, the
classification accuracy has decreased to the early 50%. It was better to use EAP when estimating
individual cognitive attribute. If it was more important to accurately estimate mastery pattern, however, it
is better to choose MLE/MAP. Next, the Q-matrix configuration appeared to affect the accuracy of ability
estimation. As the number of cognitive attributes came to be relatively larger compared to the number of
related test items, the classification accuracy tended to be lower. The higher the number of items and the
better the quality of items, the higher the classification accuracy. Interestingly, if the number of items that
measure a specific cognitive attribute were more than 5, the ability estimation accuracy could be kept
relatively high even though the quality of items dropped somewhat. Also, the amounts of correlations
among cognitive attributes appeared not to be related to the accuracy of ability estimation.