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Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees’ specific strengths and weaknesses of a set of skills or attributes within a domain. Recently, several methodological developments have been added to the CDM literature, which include the development of general and reduced CDMs, various absolute and relative fit measures at both the test and item levels, and a general Q-matrix validation procedure. Building on these developments, this research proposes a systematic procedure to diagnostically model extant large-scale assessment data. The procedure can be divided into four phases: construction of initial attributes and Q-matrices, construction of final attributes and Q-matrix, evaluation of reduced CDMs, and crossvalidation of the selected model. Working with language experts, we use data from the PISA 2000 reading assessment to illustrate the procedure.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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