Abstract
Cognitive diagnostic assessment (CDA) allows for diagnosing second language (L2) learners’ strengths and weaknesses of attributes in a specific domain. Exploring the little-known territory of CDA, the current study retrofitted the reading section of the International English Language Testing System (IELTS) with a cognitive diagnostic model (CDM). It aimed to identify the attributes involved in successfully implementing IELTS reading, analyze the overall and individual test-takers’ reading performance, and, finally, explore the IELTS reading differences of Iranian students in engineering and veterinary domains. Based on think-aloud protocols and expert judgement, an initial Q-matrix was developed. Using R package CDM, the generalized deterministic inputs, noisy “and” gate (G-DINA) model was applied to IELTS reading data to refine and validate the initial Q-matrix and estimate the mastery probabilities of 1025 test-takers on each attribute. The final Q-matrix consisted of 6 attributes assumed to be involved in IELTS reading. Moreover, the overall test-takers and the individuals demonstrated different mastery/non-mastery across the 6 IELTS reading attributes on both macro and micro levels. Further, significant differences were found between IELTS reading performances of Iranian engineering and veterinary students. The findings supported the assumption that CDA can provide instructors and IELTS candidates with detailed diagnostic feedback to promote test-takers’ IELTS reading performance.
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