Semi-automated assessment in fundamental BIM pedagogy for large cohorts

Due to the increasing relevance of Building Information Modeling (BIM) in students’ curricula, BIM courses are increasingly in demand. Hence, to advance the quality of teaching and practical application, the Technical University of Munich split BIM teaching into four consecutive parts: BIM.fundamentals, BIM.project, BIM.advanced, and BIM.infra. For the fundamental BIM course, we use graded assignments in the fields of geometric and semantic modeling, model checking, and rendering, which add to voluntary exercise tutorials. However, individual support and evaluation of the assignments cannot be offered for large cohorts exceeding more than 400 students but requires means to streamline feedback provision. We developed a semi-automated workflow for practical assignments using State-of-the-Art digital methods to efficiently evaluate these individually and fairly, even for large numbers of students. To support the objective of geometric and semantic modeling using open BIM technology, we utilize semi-automated, rule-based model-checking approaches. Additionally, based on parametric design generation, we provide individual IFC models to enhance the object of exercising BIM collaboration tasks, such as clash detection and BCF-based communication. To evaluate the use case implementation of model visualization, we aim to use Computer Vision techniques to semi-automatically assess the rendering quality.