Abstract
The growing demand for personalized online learning underscores the
necessity for diagnostic assessments that are tailored to the cognitive
abilities of individual examinees. The combination of cognitive
diagnostic models (CDMs) with computerized multistage testing (MST)
holds potential for meeting these educational needs. However, research
on the integration of MST with cognitive diagnosis (CD-MST) has been
limited, largely due to the challenges in establishing criteria for
constructing test modules and defining routing rules prior to
administering the test. This study aims to introduce an innovative
design approach for CD-MST that employs a strategy of partitioning the
skill-space, which encompasses all possible attribute mastery profiles,
to address the challenges. By partitioning the skill-space into groups
of attribute profiles, distinct modules tailored to each partitioned
group can be constructed, ensuring that each examinee is adaptively
routed to the most suitable module at each testing stage. Item
information functions for CD-MST are also proposed by defining the
information conditionally on an attribute profile, in order to quantify
an item’s discrimination power for each profile. Furthermore, a
strategic approach for automated module assembly in CD-MST is developed
to construct modules that maximize information for each attribute
profile group while satisfying all practical constraints. Simulation
results indicate that the proposed CD-MST improves estimation accuracy
compared to traditional linear test and can effectively utilize a wider
range of item types from the item bank.