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WHAT HAPPENS WHEN CREATIVITY IS EXHAUSTED? DESIGN TOOLS AS AN AID FOR IDEATION Colin M. Gray 1 , Colleen M. Seifert 2 , Seda Yilmaz 1 , Shanna R. Daly 2 , & Richard Gonzalez 2 1 Iowa State University; 2 University of Michigan

What Happens when Creativity is Exhausted? Design Tools as an Aid for Ideation

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WHAT HAPPENS WHEN CREATIVITY IS EXHAUSTED?DESIGN TOOLS AS AN AID FOR IDEATION

Colin M. Gray1, Colleen M. Seifert2, Seda Yilmaz1, Shanna R. Daly2, & Richard Gonzalez2

1Iowa State University; 2University of Michigan

HOW DO WE CREATE NOVEL & CREATIVE CONCEPTS?

Photo courtesy of Rennet Stowehttps://www.flickr.com/photos/tomsaint/2987926396

AND HOW DO WE KNOW WHEN WE NEED HELP?

INSTRUMENTAL JUDGMENTan understanding and value for design tools,

methods, and strategies (Cross, 2011; Nelson & Stolterman, 2012;

Stolterman, 2008)

INSTRUMENTAL JUDGMENT

TOOLS, METHODS, & STRATEGIES

Reframing design problems

(Akin & Akin, 1996; Smith & Linsey, 2011)

Imposing constraints (Biskjaer & Halskov, 2014;

Finke et al., 1992)

Visual or analogical supports

(Cheng, Mugge, & Schoormans, 2014; Viswanathan & Linsey,

2012, 2013)

JUDGMENTS THAT RELATE TO USE OF

THESE TOOLS?

THE CHALLENGEA focus on cognitive tools has generally neglected

how students are intended to develop their abilities with these tools…

AND

Beginning designers need to develop sensibilities surrounding their use of tools in the design process.

(Self et al., 2014; Stolterman et al., 2008)

What happens when students use a cognitive support only after their

own ability to generate concepts is exhausted, and what implications does this has for the development of pedagogical experiences that

encourage idea fluency?

DESIGN HEURISTICS

• Provides prompts to help designers generate alternatives that vary in nature, discouraging fixation and encouraging divergent patterns of thinking (Yilmaz, Daly, Seifert, & Gonzalez, 2011; Yilmaz, Seifert, & Gonzalez, 2010)

• Derived from empirical evidence of industrial and engineering designs (Daly et al., 2012; Yilmaz, Christian, Daly, Seifert, & Gonzalez, 2012; Yilmaz & Seifert, 2010)

• Validated through a range of product analysis, case studies, and protocol analyses, in both educational and professional contexts (e.g., Yilmaz & Seifert, 2009; Yilmaz et al., 2011; Yilmaz et al., 2010; Yilmaz et al., 2013; Yilmaz, Daly, Christian, Seifert, & Gonzalez, 2014)

DESIGN HEURISTICS

PARTICIPANTS

• Sophomore undergraduate industrial design class at a large Midwestern university

• 34 students (12 females and 22 males), aged 19 to 22

IDEATION SESSION

Please design a seating unit. Generate as many solutions as you can.

BRAINSTORMING

30 MINUTES

DESIGN HEURISTICS

30 MINUTES

LEARN

10 MINUTES

“”

ANALYSIS

• Consensual Assessment Technique with two raters, blind to condition (Amabile, 1982)

• Rated on four concept characteristics, using a 7-point scale• Linear mixed model of scores from both raters• Intra-class correlation (ICC) to test for rater consistency and

agreement

HOW MUCH CAN A COGNITIVE SUPPORT TOOL EXPAND IDEA

GENERATION AFTER EXHAUSTION?

BRAINSTORMING

6.06 CONCEPTS (sd=1.43)

205 CONCEPTS

DESIGN HEURISTICS

2.76 CONCEPTS (sd=0.96)

93 CONCEPTS

CONCEPT CHARACTERISTICS (adapted from Dean, Hender, Rodgers, & Santanen, 2006)

NOVELTYThe degree to which an idea is original and modifies a paradigmWORKABILITY/FEASIBILITY The degree to which an idea can be easily implemented and does not violate constraintsRELEVANCEAn idea is relevant if it applies to the stated problem and will be effective at solving the problemSPECIFICITY The degree to which an idea is specific (i.e., worked out in detail)

ARE THERE CHARACTERISTIC DIFFERENCES BETWEEN CONCEPTS BY METHOD?

 

Average Ranking Working On Own

(SD)   

Average Ranking With

Design Heuristics

(SD)   

Z p

ICC agreement ICC consistency

      No DH DH No DH DH

Novelty3.841

(1.1549)4.280

(1.0695) -2.513 0.014 0.79 0.71 0.82 0.71

Specificity3.220

(1.3007)3.855

(1.3744) -5.276 0.000 0.86 0.87 0.86 0.87

Relevance3.900

(1.3297)4.188

(1.1466) -2.588 0.011 0.77 0.69 0.87 0.72

Feasibility4.561

(1.1589)4.360

(1.1618) 1.312 0.192 0.34 0.46 0.81 0.77

HOW DOES A COGNITIVE SUPPORT TOOL INFLUENCE IDEA GENERATION?

THE AMBIENT CHAIR Chair has a built in “roof” which will

provide over-head lighting

THE POD Solid, partially enclosed chair that allows for 360° movement (chair is

fixed in place)

HOW DOES A COGNITIVE SUPPORT TOOL INFLUENCE IDEA GENERATION?

RUSSIAN DOLL CHAIR 3 chairs in one, 1st layer is comfortable

padding, 2nd is sturdy metal frame + 3rd is a stool. All chairs would be functional

by themselves

THE CAROUSEL Four chairs are attached to a

center coffee table.

#41: LAYER #47: MIRROR OR ARRAY

QUALITY OF CONCEPTS INCREASED

DISCUSSION

Design Heuristics is a cognitive tool to combat creative “exhaustion”

QUANTITY OF CONCEPTS

DECREASEDBUT

DISCUSSION

COGNITIVE SUPPORTS AS JUST-IN-TIME SCAFFOLDING • Supports are related to specific pedagogical contexts, and

cannot be viewed only in abstraction• Knowing when to introduce cognitive tools based on known

instructional barriers (and those yet to be discovered)• Starting the process of self-learning that will be relevant in

future professional work

DISCUSSION

DEVELOPING STUDENTS’ TOOL SENSIBILITY • Building instrumental judgment: not only objective

knowledge of the tool, but how and when to use it• Increasing our understanding of key cognitive and emotive

qualities that may increase receptivity to new cognitive supports

• Heightening the role of cognitive tools/supports in developing a designer’s conceptual repertoire

CONCLUSION &FUTURE WORK

• Triangulation with other data sources to understand individual students’ perception of their developing instrumental judgments

• Clarifying the nature of instrumental judgment, particularly within disciplinary and identity framings

• Learning to capitalize on exhausted creative states is a key area for future instructional development, developing pedagogical experiences that increase students’ design expertise

THANK YOUThis research is funded by the National Science Foundation, Division of Undergraduate Education,

Transforming Undergraduate Education in Science, Technology, Engineering and Mathematics (TUES Type II) Grants # 1323251 and #1322552. Any opinions, findings, and conclusions or

recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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