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Neuro-cognitive Differences Among Engineering Students when Using Unstructured, Partially Structured, and Structured Design Concept Generation Techniques

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2018 ASEE Annual Conference & Exposition


Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

Studies in Engineering Design

Tagged Division

Design in Engineering Education

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Paper Authors


Mo Hu Virginia Tech

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Mo Hu is a Ph.D. student in Civil and Environmental Engineering Department at Virginia Tech. Her research interest is applying neuroscience methods in engineering to provide better solutions for sustainability.

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Tripp Shealy Virginia Tech

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Tripp Shealy is an Assistant Professor of Civil and Environmental Engineering at Virginia Tech.

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John S. Gero University of North Carolina, Charlotte

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John Gero is Research Professor in Computer Science and Architecture at UNCC, Research Professor in Krasnow Institute for Advanced Study, and Research Professor in Computational Social Science at George Mason University. He was formerly Professor of Design Science, University of Sydney. He has edited/authored over 50 books and published over 650 research papers. He has been a professor of mechanical engineering, civil engineering, architecture, cognitive science, and computer science at MIT, UC-Berkeley, UCLA, Columbia and CMU in the USA, at Strathclyde and Loughborough in the UK, at INSA-Lyon and Provence in France and at EPFL in Switzerland.

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This paper presents an experimental study measuring engineering students’ neuro-cognition when generating solutions using three concept generation techniques: unstructured (brainstorming), partially structured (morphological analysis), and structured (TRIZ). Twelve engineering students were given the same three design tasks and one of the three concept generation techniques for each task. Students generated concepts while a functional near infrared spectroscopy system captured their physical changes in oxygenated blood to the prefrontal cortex in their brain. While there is literature describing which brain regions support particular cognitive functions, far less is known about how this supports concept generation and how cognitive processes differ when using varying techniques. The results suggest that different concept generation techniques lead to significantly different patterns of activation and coordination among brain regions, which might influence divergent thinking and creativity during design. Increased coordination between the left and right hemisphere was observed when using TRIZ, while an increase in coordination only in the right hemisphere was observed during brainstorming and an increase only in the left hemisphere during morphological analysis. Brainstorming and TRIZ also resulted in an increase in cognitive activation in the region of the brain associated with abstract reasoning and cognitive flexibility. Through better understanding of the neuro-cognitive patterns during design, future research can begin to explore specific elements of the engineering curriculum that may contribute to student ability to generate concepts and solve engineering design problems. This interdisciplinary study is meant to generate conversation about engineering design and offer a new tool through neuroimaging to understand differences in design cognition and the effect of tools, techniques, and education.

Hu, M., & Shealy, T., & Gero, J. S. (2018, June), Neuro-cognitive Differences Among Engineering Students when Using Unstructured, Partially Structured, and Structured Design Concept Generation Techniques Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30835

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