Investigating the influence of designers' cognitive characteristics and interaction behaviors in design concept generation

Kathryn W. Jablokow, Neeraj Sonalkar, Jonathan Edelman, Ade Mabogunje, Larry Leifer

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


This paper investigates relationships among the cognitive characteristics, interaction behaviors, and ideation outcomes of 14 engineering design teams engaged in concept generation. Cognitive characteristics were measured using the Kirton Adaption-Innovation Inventory (KAI), which assesses an individual's cognitive preference for structure in generating and working with ideas in problem solving. Team interactions were assessed using the Interaction Dynamics Notation (IDN), which allows interaction behaviors to be quantitatively analyzed, while team outcomes were measured in terms of ideation utterances (ideas and unique ideas). Our analyses revealed that cognitive style (KAI) did not correlate significantly with interaction response behaviors (IDN) or with the quantity of ideas/unique ideas produced. However, the cognitive style diversity of the teams did influence the number of topics they discussed, as well as the interconnectedness of those topics. In addition, several specific interaction responses were associated with the occurrence of ideas/unique ideas, although the sequences associated with those responses varied widely; the more adaptive teams also had greater position specificity in these sequences than the more innovative teams. Our findings highlight the importance of forming cognitively diverse design teams and suggest that specific interaction behaviors should be encouraged or taught as a means to increase the occurrence of ideas and/or unique ideas during team concept generation.

Original languageEnglish (US)
Article number091101
JournalJournal of Mechanical Design
Issue number9
StatePublished - Sep 1 2019

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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