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Exploring the Impact of Cognitive Style and Academic Discipline on Design Prototype Variability

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Conference

2014 ASEE Annual Conference & Exposition

Location

Indianapolis, Indiana

Publication Date

June 15, 2014

Start Date

June 15, 2014

End Date

June 18, 2014

ISSN

2153-5965

Conference Session

Design Realization

Tagged Division

Design in Engineering Education

Page Count

13

Page Numbers

24.587.1 - 24.587.13

DOI

10.18260/1-2--20478

Permanent URL

https://peer.asee.org/20478

Download Count

153

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Paper Authors

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Kathryn Jablokow Pennsylvania State University

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Dr. Kathryn Jablokow is an associate professor of mechanical engineering and engineering design at Pennsylvania State University. A graduate of 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. Dr. Jablokow is the architect of a unique, four-course module focused on creativity and problem-solving leadership and is currently developing a new methodology for cognition-based design. She is one of three instructors for Penn State’s massive open online course (MOOC) on Creativity, Innovation, and Change, and is the founding director of the Problem Solving Research Group, whose 50+ collaborating members include faculty and students from several universities, as well as industrial representatives, military leaders, and corporate consultants.

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Katja N. Spreckelmeyer Stanford University, Dept. of Psychology

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Jacob Hershfield

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Max Hershfield Stanford University

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Carolyn McEachern Stanford University

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Carolyn McEachern is a third-year undergraduate student at Stanford University, working towards a bachelor's of science degree in engineering: product design. Her focus is human-centered design, with an interest in user testing and prototyping.

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Martin Steinert NTNU (Norwegian University of Science and Technology)

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Dr. Martin Steinert is a professor of engineering design and innovation in the department of engineering design and materials at the Norwegian University of Science and Technology (NTNU). He teaches fuzzy front-end engineering for radical new product/service/system concepts and graduate research seminars for Ph.D. students engaged in topics related to new product design and development. His various research projects are usually multidisciplinary (ME/CS/EE/Neuro- and cognitive science) and often connected with industry. The aim is to uncover, understand, and leverage early stage engineering design paradigms with a special focus on human-machine/object interactions. Recently he has been published in the Int. Journal of Product Development, Int. Journal of Design Creativity and Innovation, Journal of Engineering Design and Technology, Int. Journal of Design, Int. Journal of Engineering Education, Tech. Forecasting and Social Change, Energy Policy, and Information Knowledge System Management Journal. Ever since a short stint at MIT and time as deputy director at the Center for Design Research and at the d.research program (Hasso-Plattner Design Thinking Research program) at Stanford University, he has made the overarching aim of his research and teaching to always push the boundaries for Norwegian product-development teams, so that they will ideate more radical new concepts, faster.

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Larry Leifer Stanford University, Center for Design Research

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Larry Leifer is a professor of mechanical engineering design and founding director of the Center for Design Research (CDR) at Stanford University, where he has been a member of the faculty since 1976. His teaching laboratory is the graduate course ME310, "Industry Project Based Engineering Design, Innovation, and Development." Research themes include: 1) creating collaborative engineering design environments for distributed product innovation teams; 2) instrumenting that environment for design knowledge capture, indexing, reuse, and performance assessment; and 3) design for sustainable well-being. His top R&D priorities at the moment include the Hasso-Plattner Design Thinking Research Program, d.swiss, and the notion of a pan-disciplinary Ph.D. program in design.

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Abstract

The Impact of Individual Cognitive Differences on Design Decisions while PrototypingBackground: This research addresses a recent call from the National Science Foundation for areinvigorated research agenda to investigate aspects of engineering design associated withcreativity and decision making, including a focus on how individuals make design decisions inthe face of uncertainty and in the early stages of design.Motivation: In responding to this call, our aim is to study the impact of individual cognitivedifferences on decisions made in the context of prototyping, which has been identified as a keyactivity in the early stages of the design process.Research Methods: Our sample included 23 participants (mean age = 23.1 yrs. +/- 4 yrs.), 50%being female. All participants were students currently enrolled in an undergraduate program at asmall, private university. Participants were grouped into engineering students (N=11) and non-engineering students (N=12) based on their declared majors.Participants completed the Kirton Adaption-Innovation Inventory (KAI) and the NEO personalityquestionnaire before participating in a design challenge task. Participants were asked to firstconceptualize and then build 3 different prototypes for a device that would allow them to drop araw egg from different heights without the egg breaking (i.e., the “egg-drop challenge”).Participants were provided with 3 identical sets of materials; each set included 1 plastic bag, 8rubber bands, 8 pipe cleaners, 8 Popsicle sticks, a 4”x8” piece of foam core, a 4”x12” flat foamsheet, and 12” of tape. Participants had 10 minutes to conceptualize and draw their proposedprototypes and 15 minutes to construct their prototypes.To assess the productivity, creativity, and decision making of the participants, we used thefollowing outcome measures:1. Number of prototype concepts drawn2. Number of prototypes built3. Number of prototypes that met the egg-drop challenge (i.e., unbroken egg)4. Dissimilarity between built prototypes5. Deviation (dissimilarity) of built prototypes from idea sketchesFor each participant, a pairwise comparison was performed of all his/her completed prototypes toassess conceptual dissimilarity/similarity among prototypes. Comparisons were conducted bythree independent raters on a 5-point scale (1=highly dissimilar to 5=highly similar). For thefinal analysis, ratings were averaged across participants. Inter-rater reliability was 0.5 (Cohen’skappa). In addition to similarity of completed prototypes, we assessed how much eachparticipant’s built prototypes deviated from their original ideas as sketched/drafted in theprevious step (1=highly dissimilar to 5=highly similar) as an indicator of their decision making(i.e., which ideas did they take forward, which did they reject). Here, novelty of ideas (i.e.,dissimilarity) was defined as any addition that occurred in the built prototype that had notpreviously been drawn. Again, comparisons were conducted by three independent raters(Cohen’s kappa = 0.4).Results: In general, our analyses revealed no significant differences between non-engineeringand engineering students with regard to cognitive style or personality. Mean scores for the KAIwere 97.5 vs. 97.8, respectively, and the two groups did not differ significantly on any of theNEO personality dimensions. The two groups were equally productive (averages of 2.1 vs. 2.2completed prototypes per person, respectively) and did not differ significantly with regard tosuccess rate, although the non-engineering students tended to be slightly more successful thanthe engineering students relative to the general aim of the design challenge (61% vs. 41 % of thecompleted prototypes prevented the egg from breaking, respectively).Our measures of diversity and novelty of ideas revealed a lack of variation in both groups.Deviation from original ideas was found to be low in both non-engineering and engineeringstudents (4.1 vs. 3.9), and similarity between first and second built prototypes was ratedintermediate in both groups (2.7 vs. 2.9). Across groups, the number of completed prototypescorrelated negatively with participants’ KAI scores (r=0.48, p=0.02), suggesting that the moreadaptive participants (in terms of the Adaption-Innovation cognitive style spectrum) were morelikely to achieve the stated goal of 3 prototypes than the more innovative participants. Noassociation was found between KAI score (cognitive style) and measures of diversity or noveltyof ideas.Conclusions and Significance: While the small sample size used in this study limits the strengthof our conclusions, the results are encouraging and suggest further investigation, particularly interms of the relationship between cognitive style and the number of prototypes built. Further datacollection is underway with expanded samples of engineering and non-engineering students.

Jablokow, K., & Spreckelmeyer, K. N., & Hershfield, J., & Hershfield, M., & McEachern, C., & Steinert, M., & Leifer, L. (2014, June), Exploring the Impact of Cognitive Style and Academic Discipline on Design Prototype Variability Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--20478

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