Innovation
  Does innovation come from process or from cognition?
 



Overview

Engineering and scientists uses a complex semi-formal process to develop innovative products that bring value to users. While we know a lot about how people become fixated on past solutions and how the scienctific discovery process and the engineering design process can each be structured to lead scientists and designers to new solutions, much remains to be understood the process of insight and innovation, particularly regarding the cognition that underlies it. We brings the theories and methods of cognitive and social psychology to unpack the complex events of design that occur in the real world.

   

         
 
Recent Results
  • Far analogies increase ideation rates but also lead to exploration of functionally similar rather than functionally dissimilar ideas (i.e., they lead to staying closer rather than moving further away from past ideas)
  • Analogical distance can be decoupled psychologically from commonness of the analogical prime
  • Analogical distance has an inverted U-shape effect on creativity (which can be captured with computational models of distance between examples)
  • The physical design environment appears to shape the kinds of analogies that engineers bring to the design problem. In particular, physical prototypes appear to supress between domain analogies.
  • Within-domain analogies, but not within-discipline or outside-discipline analogies, led to science and work process conflicts.
   
   

 

   
 
The Team
   
       
 
Schunn Lab:Natalie Pareja Roblin
Collaborators: Joel Chan (CMU), Jon Cagan (CMU Engr), Kris Wood (UT Austin, Engr), Ken Kotovsky (CMU Psy), Katherine Fu (CMU Engr), Paul Egan (CMU Engr), Susannah Paletz(CASL), Debra Berstein (TERC), Brian Drayton (TERC), Susan McKenney (Pitt/Twente/OUNL), Jacquey Barber (UC Berkeley), Sara Walkup (UC Berkeley)
   
 


   

 

Engineering video

 

We have instrumented engineering design spaces to capture thousands of hours of video of engineering design work.
 

 
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Current Projects

Integrating Social and Cognitive Processes in Discovery and Innovation. Innovation and discovery involve individuals working successfully together in teams. Prior research has typically studied social teamwork variables in isolation or individual cognition variables in isolation. We have examined a very large quantity of video data collected from a recent highly successful case of science and engineering, the Mars Exploration Rover. From this video record, the project traces the path from the structure of different subgroups (such as having formal roles and diversity of knowledge in the subgroups) to the occurrence of different social processes (such as task conflict, breadth of participation, communication norms, and shared mental models) to the occurrence of different cognitive processes (such as analogy, information search, and evaluation) and finally to outcomes (such as new methods for rover control and new hypotheses regarding the nature of Mars). We are also doing analyses of cogntive and social processes in the large data set of successful and unsuccessful teams in an engineering productive innovation class.

NanoDesign. Engineering is now taking on the design of objects building upon emerging nano-science. This kind of design poses new challenges for designers, as they must manipulate objects at the nanometer-level, but work towards outcomes at the centimeter or larger level (e.g., changing myosin properties to influence heart muscle properties). The work across huge spatial scales is challenging because the properties at the nano-scale do not map directly onto the emergent systems level properties. We are building simulations of particular systems, studying the cognitive processes of various groups who will need to do design work in this area, and developing design environments that leverage the simulations to support the cognitive challenges for various groups.

Design Dimensions. Why do some educational curricula move to scale well while others do not? We are studying critical processes related to dimensions of time, goals, context, and scale. The work involves retrospective studies of four successful cases, participant/observation of ongoing large scale curriculum design cases, and interview studies across larger numbers of science curricula design projects.


Prior Projects

Advanced Analogical Search with Integrated Function and Form: The Verrocchio Project: Much research has shown that a major component of creative ideation is based on the incorporation of analogies in concept generation. The Verrocchio Project seeks to improve our capabilities in concept generation through collaboration between the disciplines of Cognitve Psychology, Computer Science, and Engineering Design to provide new tools for design by analogy. Our approach is based on a representation that associates functional and geometric information. We combine a linguistic search for functional similarity with a multi-level search for geometric similarity to automatically identify and present analogies to the designer. The initial application for the Verrocchio Project is the design of sustainable energy-using devices for developing world applications, a domain that is ripe for innovation. Our initial search space is the USPTO utility patent repository.

Design Tools to Cognitive Processes to Innovation. We have collected data (~30 hrs/team) from semester-long product realization teams (approximately 60 teams across three yrs of data collection) to understand how the artifacts and tools in the design environment shape cognitive processes like analogy and mental simulation to in turn influence the quality of final solutions.

 

   
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Publications
   
 
  • Chan, J., Dow, S. P., & Schunn, C. D. (In press). Do the best design ideas (really) come from conceptually distant sources of inspiration? Design Studies.
  • Chan, J., & Schunn, C. D. (In press). The impact of analogies on creative concept generation: Lessons from an in vivo study in engineering design. Cognitive Science. pdf
  • Fu, K., Chan, J., Schunn, C. D., & Cagan, J. (2013). Expert representation of design repository space: A comparison to and validation of algorithmic output. Design Studies, 34(6), 729-762. pdf
  • Fu, K., Chan, J., Cagan, J., Kotovsky, K., Schunn, C., & Wood, K. (2013). The meaning of “near” and “far”: The impact of structuring design databases and the effect of distance of analogy on design output. Journal of Mechanical Design, 135(2), 021007. pdf
  • Egan, P. F., Cagan, J. C., Schunn, C. D., & LeDuc, P. R. (2013). Design of complex biologically-based nanoscale systems using multi-agent simulations and structure-behavior-function representations. Journal of Mechanical Design, 135(6), 061005. pdf
  • Paletz, S. B. F., Kim, K., Schunn, C. D., Tollinger, I., & Vera, A. (2013). The development of adaptive expertise, routine expertise, and novelty in a large research team. Applied Cognitive Psychology, 27(4), 415–428. pdf
  • Paletz, S. B. F., Schunn, C. D., & Kim, K. (2013).The interplay of conflict and analogy in multidisciplinary teams. Cognition, 126(1), 1-19. pdf
  • Chan, J., Paletz, S., & Schunn, C. D. (2012). Analogy as a strategy for supporting complex problem solving under uncertainty. Memory & Cognition, 40, 1352-1365. pdf
  • Paletz, S. B. F., Schunn, C. D., & Kim, K. (2011). Intragroup conflict under the microscope: micro-conflicts in naturalistic team discussions. Negotiation and Conflict Management Research, 4, 314-351. pdf
  • Paletz, S. B. F., & Schunn, C. D. (2011). Assessing group level participation in fluid teams: Testing a new metric. Behavior Research Methods. pdf
  • Jang, J., & Schunn, C. D. (2012). Physical design tools support and hinder innovative engineering design. Journal of Mechanical Design. pdf
  • Chan, J., Fu, K., Schunn, C. D., Cagan, J., Wood, K., & Kotovsky, K. (2011). On the benefits and pitfalls of analogies for innovative design: Ideation performance based on analogical distance, commonness, and modality of examples. Journal of Mechanical Design, 133, 081004-1-11. pdf
  • Schunn, C. D. (2010). From uncertainly exact to certainly vague: Epistemic uncertainty and approximation in science and engineering problem solving. In B. Ross (Ed.), Psychology of Learning and Motivation (Vol. 53). pdf
  • Linsey, J., Tseng, I., Fu, K., Cagan, J., Wood, K., & Schunn, C. D. (2010). A study of design fixation, its mitigation and perception in engineering design faculty. Journal of Mechanical Design, 132. pdf
  • Paletz, S. B. F., & Schunn, C. D. (2010). A social-cognitive framework of multidisciplinary team innovation. Topics in Cognitive Science, 2, 73-95. pdf
  • Christensen, B. T., & Schunn, C. D. (2009). The role and impact of mental simulation in design. Applied Cognitive Psychology, 23, 327-344. pdf
  • Christensen, B. T., & Schunn, C. D. (2009). Setting a limit to randomness [or: ‘Putting blinkers on a blind man’]: Providing cognitive support for creative processes with environmental cues. In K. Wood & A. Markman (Eds.), Tools for Innovation. pdf
  • Titus, N., Schunn, C. D., Walhall, C., Chiu, G., & Ramani, K. (2008). What design processes predict better design outcomes? The case of robotics design teams. Proceedings of the Tools and Methods of Competitive Engineering Conference, Izmir, Turkey, (April, 2009). pdf
  • Schunn, C. D., Lovell, M. R., Wang, Y., and Yang, A. (2008). Measuring Innovative Apples & Oranges: Towards More Robust and Efficient Measures of Product Innovation. Paper presented at the Studying Design Creativity conference. Aix-en-Provence, France, (March, 2008).
  • Christensen, B. T., & Schunn, C. D. (2007). The relationship of analogical distance to analogical function and pre-inventive structure: The case of engineering design. Memory & Cognition, 35(1), 29-38. pdf
  • Mehalik, M. M., & Schunn, C. D. (2006). What constitutes good design? A review of empirical studies of the design process. International Journal of Engineering Education, 22(3), 519-532. pdf
  • Christensen, B. T., & Schunn, C. D. (2005). Spontaneous access and analogical incubation effects. Creativity Research Journal, 17(2), 207-220. pdf
  • Lovett, M. C., & Schunn, C. D. (1999). Task representations, strategy variability and base-rate neglect. Journal of Experimental Psychology: General, 128, 107-130. pdf