Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…

Geometry is a strand of mathematics that can benefit individuals in many areas of life. Test results, such as the TIMSS results, indicate that geometry is an area for growth among American students. With a need for students to better understand geometry, several academic standards have been created to direct geometry instruction in the United…

Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…