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Evaluating an Intelligent Sketching Feedback Tool for Scalable Spatial Visualization Skill Training

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Engineering Design Graphics Division Technical Session 4: A Potpourri of Ideas

Tagged Division

Engineering Design Graphics

Page Count

12

Permanent URL

https://peer.asee.org/37102

Download Count

30

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Paper Authors

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Tiffany Wenting Li University of Illinois at Urbana-Champaign

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Tiffany Li is a Ph.D. student in computer science at the University of Illinois at Urbana-Champaign. Her research interest lies in human-computer interaction and educational technology.

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Ziang Xiao University of Illinois at Urbana-Champaign

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Ziang Xiao is a graduate student from the computer science department at the University of Illinois at Urbana-Champaign. His primary research interest is in human-computer interaction.

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Molly H. Goldstein University of Illinois at Urbana - Champaign Orcid 16x16 orcid.org/0000-0002-2382-4745

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Molly H. Goldstein is Teaching Assistant Professor in Industrial and Enterprise Systems Engineering at University of Illinois, Urbana-Champaign. She previously worked as an environmental engineer specializing in air quality influencing her focus in engineering design with environmental concerns. Her research interests center on engineering design in undergraduate and precollege settings. She obtained her BS in General Engineering (Systems and Design) and MS in Systems and Entrepreneurial Engineering from the University of Illinois and PhD in Engineering Education from Purdue University.

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Michael L. Philpott PhD. University of Illinois at Urbana - Champaign

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Mike Philpott is an Emeritus Associate Professor of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC). He is also Founder and Chief Scientist of aPriori inc., an Enterprise Cost Management (ECM) software company offering the first CAD-integrated solution for real-time, predictive and precise cost estimating throughout the entire product development and product delivery process. The patented enabling technology for this was developed over 10 years of R&D at UIUC, funded primarily by John Deere. Mike has over 50 publications in this area, primarily in Design-to-Cost, Design-for-Manufacture, and Design-for-Assembly. He directed the research in process cost modeling and the development of the aPriori technology, and his graduate student team won the Harvard Business Plan competition in 2003. In 2004, the company achieved $4.5M venture capital 1st round funding from Bain Capital and Sigma Partners, and has since grown to 150+ employees. Mike received his MS in 1979 and PhD in 1986 from Cranfield Institute of Technology, England, and worked for a number of years as a design engineer in the British automotive and machine tool industry, specifically Land Rover, Jaguar, and Molins Machine Tool.

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Brian Woodard University of Illinois at Urbana - Champaign

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Dr. Woodard received his Ph.D. in Aerospace Engineering from the University of Illinois at Urbana-Champaign in 2011. His Aerospace research interests currently focus on the effects of icing on the aerodynamics of swept-wing aircraft. In engineering education, he is also interested in project-based learning and spatial visualization. He teaches courses at the University of Illinois where he serves as the Director of Undergraduate Programs for the Department of Aerospace Engineering.

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Abstract

Spatial visualization skills are essential and fundamental to studying STEM subjects. The increasing need for STEM education poses scalability challenges in spatial visualization skill training. Many researchers and practitioners face a major challenge of supporting sketching, an essential component in spatial visualization training, at scale. Because of the enormous error space, traditionally, a significant amount of human effort is required to grade and provide individualized feedback for students' technical drawings. Our team leveraged data mining and unsupervised learning techniques to build an intelligent sketching feedback tool. The tool not only allowed students to practice their sketching skills in a scalable manner but also graded students' sketches and provided customized and actionable feedback based on the error patterns in real-time. We deployed our tool in a university-level spatial visualization class with about 60 students. Students interacted with our tool for eight weeks. We performed an interview study to understand students’ experience and attitudes towards using such an automated feedback tool for practicing spatial visualization skills. Through a grounded theory approach, we identified themes that informed our future improvement of the tool. We discuss the future design of sketching feedback tools in spatial visualization training in general.

Li, T. W., & Xiao, Z., & Goldstein, M. H., & Philpott, M. L., & Woodard, B. (2021, July), Evaluating an Intelligent Sketching Feedback Tool for Scalable Spatial Visualization Skill Training Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37102

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