عنوان مقاله [English]
Cognitive diagnostic assessment has been introduced as a new issue in educational measurement. In this approach, more information were examined about how people learn and master on cognitive attribute in the school. There are several issues of modeling data in cognitive diagnostic assessment due to differences with other statistical modeling. In present study, science data of grade eight in TIMSS was analyzed by cognitive diagnostic assessment, as an empirical example, and the problems were entitled as modeling challenges. Each challenge has been explained in order to highlight differences with usual statistical modeling. The challenges included; unidimensiality versus multidimensiality, number of attribute, correlation between attributes, number of items in each attribute, operationalization of attribute, reliability of attribute, validity, item parameters, fit of model, identification and specification, convergence, and complex sampling. Each of topics was discussed in context of modeling TIMSS data in science course and experience of solving these challenges were shared.