The RRUM was slightly worse than the ACDM and G-DINA in terms of model fit and classification results, whereas the more restrictive DINA and DINO performed much worse than the other three models. Compared to the saturated G-DINA model, the ACDM showed comparable model fit and similar skill classification results. In the present study, we compared the performance of a saturated model (G-DINA), two compensatory models (DINO, ACDM), and two non-compensatory models (DINA, RRUM) with the Michigan English Language Assessment Battery (MELAB) reading test. However, the assumptions and performances of different CDMs and their applications in regard to reading comprehension tests are not fully understood. Cognitive diagnostic models (CDMs) have great promise for providing diagnostic information to aid learning and instruction, and a large number of CDMs have been proposed.
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