英文摘要 |
Many studies showed that the ability estimate from the reviewable computerized adaptive test would be more précised than that from the non-reviewable computerized adaptive test. Current reviewable computerized adaptive tests were developed based on item response theory and were designed to offer the examinee a summary report of a latent continuous trait rather than to provide sufficient diagnostic information. Cognitive diagnostic models could estimate the mastery status of the examinees’ cognitive attributes which would have a great benefit to the remedial instruction. The purpose of this study was to develop a dynamic block-review computerized adaptive testing algorithms based on Deterministic Inputs, Noisy “And” Gate model (DINA model). The performance of the proposed algorithms was investigated by a simulation study with various settings, Q-matrix, item parameters, item review mode, size of review block, review behavior, and review probability. Under most situation, the results of this study indicated that the proposed algorithm provided higher estimation accuracy than the traditional non-reviewable cognitive diagnostic computerized adaptive test. |