Advancing Formative Assessment in MCAD Education: The Visual Analytics of Parametric Feature-Based Solid Models

Advancing formative assessment in MCAD education is an important but difficult problem. Success in this endeavor requires feature-based MCAD model assessment to consider the quality of a model from various viewpoints. That includes the absolute criteria that are associated with technical domain knowledge and also criteria related to model deficiencies. For the latter, this entails assessing the results of wrong or inappropriately applied system commands, and of partial or entire modeling strategies. Here, an approach that combines the perceptual abilities, creativity, and domain knowledge of the human user with the computational power of current desktop computing has great potential to contribute to solving the problem. The aim of the current paper is two-fold. Firstly, it presents a novel approach to analyzing feature-based characteristics of MCAD models, an approach that is aimed at advancing formative assessment in the educational context. This approach is based on visual analytics and efforts to combine visualization, human factors, and data analytics. Secondly, it reports on the technical architecture and concrete implementation of a newly developed visualization environment for a software tool to enable and put into practice this novel MCAD model assessment approach. The development of this new visualization environment is based on an advanced visualization pipeline that employs radial visualization, while supporting dedicated user interaction techniques to facilitate analytical processes