Author(s):
Sketching is a crucial skill in engineering, yet sketching education has continued to take a smaller role in engineering curriculum since the transition to Computer-Aided Design (CAD). There is a critical need for an educational solution that can both teach sketching effectively and provide the necessary human-like feedback without additional burden to or expertise needed by the engineering instructor. Using artificial intelligence (AI) and machine learning (ML), a sketch-recognition based tutoring system allows students to sketch just as they would with pencil and paper while also providing iterative, real-time, and personalized feedback on their sketching ability. Sketchtivity is a tutoring system for teaching engineering students the critical skill of freehand sketching. This workshop showcases Sketchtivity and presents research on sketching in engineering through three main topics: (1) Educational impacts – classroom implementation of Sketchtivity and empirical learning outcomes, (2) Sketching in Engineering – empirical results on the measurement of sketching and its relation to design creativity, and (3) Software experience – freehand sketching lessons followed by an opportunity to practice on Sketchtivity*. Sketchtivity sets a model for providing feedback on skills that previously have required more hands-on, qualitative instruction. This unique format of the workshop allows researchers to see the impacts of this tool through analysis and first-hand experience.*Attendees are invited to bring their own tablets with pens—these are the ideal tools to experience Sketchtivity. We will have a limited number of tablets for attendees. After the workshop, attendees will have access to the software to continue to explore its features.
Coauthors
Morgan Weaver, mweaver43@gatech.edu; Hillary Merzdorf, hmerzdor@purdue.edu
