Lifting the Veil: Drawing insights about design teams from a cognitively-inspired computational model

McComb, C., Cagan, J., and Kotovsky, K. 2015, Design Studies, vol. 40(C), pp. 119-142. Novel design methodologies are often evaluated through studies involving human designers, but such studies can incur a high personnel cost. It can also be difficult to isolate the...
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Capturing Human Sequence-Learning Abilities in Configuration Design Tasks through Markov Chains

McComb, C., Cagan, J., and Kotovsky, K. 2017, Journal of Mechanical Design, vol. 139(9), pp. 1-12. Designers often search for new solutions by iteratively adapting a current design. By engaging in this search, designers not only improve solution quality but also begin...
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Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test

McComb, C., Cagan, J., and Kotovsky, K. 2017, Journal of Mechanical Design, vol. 139(4), pp. 1-12. The performance of a team with the right characteristics can exceed the mere sum of the constituent members’ individual efforts. However, a team having the wrong...
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Data on the Configuration Design of Internet-Connected Home Cooling Systems by Engineering Students

McComb, C., Cagan, J., and Kotovsky, K. 2017, Data in Brief This experiment was carried out to record the step-by-step actions that humans take in solving a configuration design problem, either in small teams or individually. Specifically, study participants were...
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Research and Practice Group Methodology: A Case Study in Student Success

McComb, C., and Tehrani, F.M 2014, ASEE Pacific-Southwest Conference Experiential learning is a key component in engineering education. In civil engineering, this component is typically delivered through multiple projects. These projects may include term projects for...
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Human system can mean many different things. In this lab, we look at it in three different ways:

Systems of Humans

  • Can we build accurate simulations of problem-solving teams?
  • How can be make organizations more efficient and effective?

Systems for Humans

  • In what way can intelligent tools boost human performance?
  • Can intelligent design tools be developed that mimic expert behavior?

Systems + Humans

  • What are the implications of merging humans and machines as equal partners?
  • What does an intelligent algorithm need to truly contribute?

Our research interests span the entire spectrum of human systems. Some examples of our research include discovering how to effectively manage and organize design teams and multi-team organization, designing computational algorithms that mirror human learning patterns, and developing new methods for rapidly analyzing renewable energy technology. If research like this sounds interesting to you, please take a look at our open positions.