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Transformational and derivational strategies in analogical problem solving.

Sven-Eric Schelhorn1, Jacqueline Griego, Ute Schmid

  • 1Institute of Cognitive Science, University of Osnabrueck, Osnabrueck, Germany. sven-eric.schelhorn@uos.de

Cognitive Processing
|January 20, 2007
PubMed
Summary

Human problem solvers use two main analogical strategies: transformational analogy and derivational analogy. The choice between these strategies depends on how easily problem elements can be mapped between source and target problems.

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Area of Science:

  • Cognitive Psychology
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Analogical problem solving is often viewed as transferring solutions based on structural mapping.
  • Derivational analogy offers an alternative: replaying past problem-solving episodes to guide current solutions.

Purpose of the Study:

  • To empirically investigate transformational and derivational analogy as distinct human problem-solving strategies.
  • To identify the factors influencing the choice between transformational and derivational analogy.

Main Methods:

  • An empirical study using path-finding problems.
  • Analysis of how participants solved problems under varying mapping constraints.

Main Results:

  • Both transformational and derivational analogy are viable strategies for human problem solvers.
  • The availability of constraints facilitating object-to-object mapping influences strategy selection.

Conclusions:

  • When mapping is easy, transformational analogy is favored.
  • When mapping is difficult, derivational analogy is more likely to be employed.