viskillz-blender—A Python package to generate assets of Mental Cutting Test exercises using Blender

Autor: Róbert Tóth, Bálint Tóth, Miklós Hoffmann, Marianna Zichar
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: SoftwareX, Vol 22, Iss , Pp 101328- (2023)
Druh dokumentu: article
ISSN: 2352-7110
DOI: 10.1016/j.softx.2023.101328
Popis: Several different methods are used to test the spatial abilities or visual skills of people. One of them is the Mental Cutting Test (MCT), the exercises of which offer a 2D projection of a 3D shape and a 2D plane, and testees should determine the shape of their intersection. MCT exercises need various 2D and 3D assets that should be developed before publishing a test. In recent decades, very few exercises have been available to instructors and researchers. In 2019, we published our first solution that could be used to calculate the intersections of MCT scenarios, then render or export their assets using Blender. This paper proposes an extended, open-source package for Blender that generates assets of MCT exercises by permuting predefined shapes, cutting planes, rotation, and scale operators. The additional wrapper script helps users use the package for various purposes, such as developing exercise offering methods, designing exercises, practicing, or organizing exams and measurements.
Databáze: Directory of Open Access Journals