10/30/2022 0 Comments Paket soal toefl reading docThe fit indices suggested that a six-attribute structure and the G-DINA model were best fitted for the reading comprehension assessment. Q-matrices were compared and refined using the model-data fit and an empirical validation procedure, and five representative cognitive diagnostic models (CDMs) were compared for optimal performance. The assessment was administered to a large population of students ( N = 21,466) in grades 2–6 from 20 schools in a district of Changchun City, China. Then, the tentative attributes were used to construct three booklets of reading comprehension items for 2–6 graders at three key stages. Reading attributes were synthesized based on a literature review, the national curriculum criteria, the results of expert panel judgments, and student think-aloud protocols. This study explored the development and validation of the Diagnostic Chinese Reading Comprehension Assessment (DCRCA) for primary students under the CDA framework. Critical issues in CDA involve the scarcity of research to develop diagnostic tests and the lack of reliability and validity evidence. To date, most cognitive diagnostic studies on reading tests have focused on retrofitting a single booklet from a large-scale assessment (e.g., PISA and PIRLS). The findings of this study highlighted the process and considerations pertinent to model selection in applications of CDMs with reading tests.Ĭognitive diagnostic assessment (CDA) has been developed rapidly to provide fine-grained diagnostic feedback on students’ subskills and to provide insights on remedial instructions in specific domains. 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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