Cognitive Diagnostic Models-based Automatic Item Generation

Yu Bai

One of the most significant challenges for test developers is the creation and production of effective test items. Automatic Item Generation (AIG) presents a highly-efficient approach to developing items at a relatively low cost. Research is conducted on the AIG system to explore item characteristics (or features) that impact item parameters, and to develop the appropriate calibration models for the items generated. Current research has focused on developing the AIG system within a framework of Item Response Theory. However, there may be additional benefits to developing an AIG system based on Cognitive Diagnostic Models (CDM), since both AIG and CDM development start with developing cognitive models. It remains to be seen, however, to what extent the cognitive model of CDMs (Q-matrix) may be helpful to the AIG system. This research aims to assess the feasibility of adopting Q-matrix...