A model of knowledge activation and insight in problem solving

  • Authors:
  • Matthew A. Cronin

  • Affiliations:
  • Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania

  • Venue:
  • Complexity - Special isssue: Computational modeling in the social sciences
  • Year:
  • 2004

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Abstract

This article presents a model of insight that offers predictions on how and when insights are likely to occur as an individual solves problems. This model is based on a fundamental trade-off between the conscious cognition that underlies how people decide among alternatives and the unconscious cognition that underlies insight. I argue that the attention controls how much thought (i.e., knowledge activation) goes to conscious cognition, and whatever activation is left over will go to finding an insight. I validate this model by replicating the common pattern of insight in problem solving (preparation--impasse--incubation--verification). The model implies that 1) one should be able to increase the frequency of insight by lessening the demand for conscious cognition, 2) impasse is not necessary for insight, and 3) incubation time increases if a person engages in any activity with a high demand on attention. Understanding how insight occurs during problem solving provides practical suggestions to make people and groups more creative and innovative; it also provides avenues for future research on the cognitive dynamics of insight.