%0 Journal Article %J Journal of Educational Measurement %D 2015 %T Variable-Length Computerized Adaptive Testing Using the Higher Order DINA Model %A Hsu, Chia-Ling %A Wang, Wen-Chung %X Cognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent continuous traits is available. To facilitate the utility of cognitive diagnosis models, corresponding computerized adaptive testing (CAT) algorithms were developed. Most of them adopt the fixed-length rule to terminate CAT and are limited to ordinary cognitive diagnosis models. In this study, the higher order deterministic-input, noisy-and-gate (DINA) model was used as an example, and three criteria based on the minimum-precision termination rule were implemented: one for the latent class, one for the latent trait, and the other for both. The simulation results demonstrated that all of the termination criteria were successful when items were selected according to the Kullback-Leibler information and the posterior-weighted Kullback-Leibler information, and the minimum-precision rule outperformed the fixed-length rule with a similar test length in recovering the latent attributes and the latent trait. %B Journal of Educational Measurement %V 52 %P 125–143 %U http://dx.doi.org/10.1111/jedm.12069 %R 10.1111/jedm.12069 %0 Journal Article %J Applied Psychological Measurement %D 2013 %T Variable-Length Computerized Adaptive Testing Based on Cognitive Diagnosis Models %A Hsu, Chia-Ling %A Wang, Wen-Chung %A Chen, Shu-Ying %X

Interest in developing computerized adaptive testing (CAT) under cognitive diagnosis models (CDMs) has increased recently. CAT algorithms that use a fixed-length termination rule frequently lead to different degrees of measurement precision for different examinees. Fixed precision, in which the examinees receive the same degree of measurement precision, is a major advantage of CAT over nonadaptive testing. In addition to the precision issue, test security is another important issue in practical CAT programs. In this study, the authors implemented two termination criteria for the fixed-precision rule and evaluated their performance under two popular CDMs using simulations. The results showed that using the two criteria with the posterior-weighted Kullback–Leibler information procedure for selecting items could achieve the prespecified measurement precision. A control procedure was developed to control item exposure and test overlap simultaneously among examinees. The simulation results indicated that in contrast to no method of controlling exposure, the control procedure developed in this study could maintain item exposure and test overlap at the prespecified level at the expense of only a few more items.

%B Applied Psychological Measurement %V 37 %P 563-582 %U http://apm.sagepub.com/content/37/7/563.abstract %R 10.1177/0146621613488642