On the Identifiability of Cognitive Diagnostic Models: Diagnosing Students’ Translation Ability

Background. In recent years Cognitive Diagnostic Models (CDMs) have attracted a great deal of attention from researchers in a variety of educational fields. However, they have not been taken into consideration in Translation Quality Assessment (TQA), in the aims of presenting fine-grained information about the strengths and weaknesses of translation students. Purpose. The present study compares the ACDM, DINO, DINA, HO-DINA, and G-DINA models, in order to define the strengths and weaknesses of Iranian translation students and to examine whether the required translation attributes are compensatory, non-compensatory, additive, or hierarchical. Methods. 200 BA translation students translated a two-English-text translation, which  was scored by three experienced translation raters using the Translation Quality Assessment Rubric (TQAR). The professional translators, established the relationships between the TQAR items and the nine proposed target translation attributes by constructing a Q-matrix. Results. Based on the results, HO-DINA can be considered the best-fitting model. Bibliography and technical skills, together with work methodology skills, are shown to be the most difficult attributes for translation students. Conclusion. HO-DINA is a non-compensatory model, thus the study findings assert that for a correct response to a test item, all measurable attributes need to be mastered.