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Managing Uncertainty in CAD-enabled Engineering Design Tasks

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2021 ASEE Virtual Annual Conference Content Access


Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Best in DEED

Tagged Division

Design in Engineering Education

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Paper Authors


Ying Ying Seah Purdue University, West Lafayette Orcid 16x16

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Ying Ying Seah is a Ph.D. candidate in Technology in the Department of Computer Information Technology at Purdue University. Her research interest mainly focuses on developing and validating novel
curricular approaches and technology-enhanced learning environments in STEM education, integrating
scientific and engineering thinking in the relevant disciplines. Specifically, her current project focuses
on designing, implementing, and validating a Learning by Design curricular approach in science classrooms across education levels. Combined with a CAD design task, as well as argumentation scaffold,
her research project aims to help students develop better argumentation skills as well as informed design decision-making skills. She has implemented this project in two middle schools in the Indiana’s
Tippecanoe county, a Physics course for pre-service teachers at Purdue University, and summer camps for
Engineering Minority Program at Purdue University.

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Tugba Karabiyik Purdue University, West Lafayette

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Dr. Tugba Karabiyik is an interdisciplinary postdoctoral researcher at Purdue University. She holds an MS and Ph.D. degrees both from Florida State University. Before her appointment at Purdue University, she worked as a lecturer and Visiting Assistant Professor at Sam Houston State University for three years. Her research interests include data-driven decision making through data visualizations, economic decision making in engineering design, and applications of game-theoretic and agent-based modeling in computational science, finance, information technology, and engineering fields. Dr. Karabiyik is an expert in conflict, competition, strategic decision-making. She has been working on developing and applying mathematical and statistical models in various domains, including educational settings.

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Alejandra J. Magana Purdue University, West Lafayette Orcid 16x16

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Alejandra Magana is the W.C. Furnas Professor in Enterprise Excellence in the Department of Computer and Information Technology and an affiliated faculty at the School of Engineering Education at Purdue University. She holds a B.E. in Information Systems, a M.S. in Technology, both from Tec de Monterrey; and a M.S. in Educational Technology and a Ph.D. in Engineering Education from Purdue University. Her research is focused on identifying how model-based cognition in STEM can be better supported by means of expert technological and computing tools such as cyber-physical systems, visualizations, and modeling and simulation tools.

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Having to deal with uncertainty is a central feature of engineering design due to its open-ended, ill-structured, and underdetermined nature. While engaging in engineering design tasks, student designers might encounter uncertainty related to unfamiliar math and science concepts, as well as the uncertainty associated with using novel technological tools. It is important for students to learn how to deal with uncertainty as it is a crucial element of engaging in engineering and science practices. In addition, it is also important for educators to know how to engage and help students with the uncertainty faced. In the past, studies have been done in the science domain, focusing on studying how students deal with uncertainty through argumentation. However, studies of similar nature still lack in the domain of engineering design. In addition, studies that focus on CAD-enabled engineering design tasks are also missing. Therefore, this study examined the ways first-year undergraduate students managed uncertainty while engaging in CAD-enabled engineering design tasks. Data were gathered through the think-aloud protocol (i.e., students’ verbalized thoughts while working on the engineering design tasks), as well as the recordings of students’ computer screens as they worked on the engineering design tasks. Data analysis entailed the use of verbal protocol analysis/video analysis. Findings from this study presented the different types of uncertainty faced by students, how they managed them, as well as how that impacted their design performance. Implications of this study include a better understanding of the various ways students dealt with uncertainty, suggestions for how educators can help students manage uncertainty more effectively, as well as increased knowledge of ways that CAD can be used to help students manage uncertainty in engineering design tasks.

Seah, Y. Y., & Karabiyik, T., & Magana, A. J. (2021, July), Managing Uncertainty in CAD-enabled Engineering Design Tasks Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37479

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