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Conceptualization of an artificial intelligence-assisted tutoring system for teaching technical drawing skills to undergraduate students

Published online by Cambridge University Press:  16 May 2024

Jonas Fastabend*
Affiliation:
University of Stuttgart, Germany
Benedikt Müller
Affiliation:
University of Stuttgart, Germany
Daniel Roth
Affiliation:
University of Stuttgart, Germany
Matthias Kreimeyer
Affiliation:
University of Stuttgart, Germany

Abstract

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In design education, technical drawing training requires a large amount of resources. The aim of this paper is to propose a concept for an artificial intelligence-based tutoring system that partly automates technical drawing education. The educational needs of the students are defined via an error analysis of 100 corrected drawing exercises and the definition of 3 error clusters with 134 different error types. Three sub-concepts with a collection of training exercises are proposed for the tutoring system to mitigate these errors. The resulting concept is validated by a survey with 29 students.

Type
Design Education
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

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