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A Cognition-Based Classification Scheme for Design Techniques

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Conference

2011 ASEE Annual Conference & Exposition

Location

Vancouver, BC

Publication Date

June 26, 2011

Start Date

June 26, 2011

End Date

June 29, 2011

ISSN

2153-5965

Conference Session

Design Communications & Cognition II

Tagged Division

Design in Engineering Education

Page Count

14

Page Numbers

22.20.1 - 22.20.14

Permanent URL

https://peer.asee.org/17302

Download Count

42

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Paper Authors

biography

Kathryn W. Jablokow Pennsylvania State University

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Dr. Kathryn W. Jablokow is an Associate Professor of Mechanical Engineering and STS (Science, Technology, and Society) at the Pennsylvania State University. A graduate of The Ohio State University (Ph.D., Electrical Engineering), Dr. Jablokow's teaching and research interests include problem solving, invention, and creativity in science and engineering, as well as robotics and computational dynamics. In addition to her membership in ASEE, she is a Senior Member of IEEE and a Fellow of ASME; she also serves as an ABET Program Evaluator and as Chair of ASME's Technology & Society Division. Dr. Jablokow is the architect of a unique 4-course graduate-level module focused on problem solving leadership and is currently developing a new methodology for cognition-based design. She also founded and directs the Problem Solving Research Group, whose 50+ collaborating members include faculty and students from multiple universities (e.g., Penn State, Temple, Virginia Tech, U. Florida), as well as industrial representatives, military leaders, and corporate consultants.

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biography

Philip Samuel BMGI

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Dr. Phil Samuel is a Senior Vice President at BMGI, Inc., a management-consulting firm specializing in performance excellence and design thinking. An integral part of BMGI’s management team since 2005, Phil brings more than a decade of experience to his role of helping clients insource creativity and increase organic growth potential. Phil’s counsel is invaluable during the strategy deployment phase of any enterprise transformation initiative, and he has become a trusted advisor for executives in a variety of industries.

With more than 20 years of technical and management experience related to engineering, manufacturing and service processes, Phil has led countless performance improvement initiatives. His extensive consulting background includes clients in aerospace, automotives, oil and gas, health care, retail, pharmaceutical and high technology, as well as regulatory agencies such as Environment Canada, the Alberta Research Council, and the National Science and Engineering Research Council of Canada. Phil holds a Ph.D. in Mechanical Engineering from the University of Calgary in Canada, and an MBA from Arizona State University. He is a registered professional engineer, and an active member of several professional organizations.

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Abstract

A Cognition-Based Classification Scheme for Design TechniquesAbstractAlthough models of the design process may differ in their details, most of them share afundamental functional architecture that mirrors the stages and flow found in general modelsof problem solving. In a simplified form, these stages can be described as follows: (1) definethe design opportunity, (2) discover new ideas, (3) develop the details of the design, and (4)demonstrate the solution. Within each of these four stages, different techniques can be usedto assist in meeting the appropriate design objectives. There are dozens (if not hundreds) ofsuch techniques available in the design and problem solving literature, but challenges remainin utilizing and applying them successfully in practice.In the classroom, one of these challenges is knowing which technique to apply when – andwhat to expect in terms of student outcomes in each case (i.e., what kinds of ideas are likelyto result, student motivation to apply particular techniques); with limited time available,instructors cannot include them all. As a result, only a handful of techniques are typicallyintroduced, usually based on recommendations from the textbook or the instructor’sexperience – rather than any deep understanding of which techniques are most likely to leadto successful solutions in different situations.In this paper, our aim is to help students and their instructors make more effective use of thetechniques available for design through a new cognition-based classification scheme that isbased on well-established cognitive constructs from the literature (e.g., Guilford1, Kirton2,Sternberg3). The proposed classification scheme is based on four key components: 1. Stages/sub-stages of the design process (e.g., define, discover, develop, demonstrate) 2. Primary cognitive operation supported (e.g., divergent vs. convergent thinking) 3. Cognitive level required for mastery of the technique (low to high) 4. Cognitive style simulated by the technique (more adaptive to more innovative)In reference to the fourth component: techniques that simulate more adaptive thinking can beused to help students generate ideas that support and refine the structure of a system (makingit more efficient), while those that simulate more innovative thinking can be used to helpstudents generate ideas that loosen or reframe the system’s structure in tangential ways.Clearly, many styles of thinking are required within any complex design effort, so it isimportant for students (and their instructors) to be able to choose techniques wisely. Inaddition, based on a student’s own cognitive level and preferred cognitive style, differentamounts of coping behavior will be required, which will impact motivation and performance.We will describe and map a diverse selection of techniques commonly used during thedifferent stages of design onto the new classification scheme. We will also discuss howdesign students and practitioners of different cognitive levels and styles tend to work throughthe design process and how they make use of and respond to these techniques, highlightingthe importance of recognizing and rewarding cognitive diversity within student design teams.References[1] Guilford, J. P. (1967). The nature of human intelligence. New York: McGraw-Hill.[2] Kirton, M. J. (2003). Adaption-Innovation in the context of diversity and change. London: Routledge.[3] Sternberg, R. J. (1997). Thinking styles. Cambridge: Cambridge University Press. 2

Jablokow, K. W., & Samuel, P. (2011, June), A Cognition-Based Classification Scheme for Design Techniques Paper presented at 2011 ASEE Annual Conference & Exposition, Vancouver, BC. https://peer.asee.org/17302

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