June 15, 2014
June 15, 2014
June 18, 2014
Design in Engineering Education
24.587.1 - 24.587.13
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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