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Related Experiment Videos

Analogical transfer, problem similarity, and expertise.

L R Novick1

  • 1University of California, Los Angeles.

Journal of Experimental Psychology. Learning, Memory, and Cognition
|July 1, 1988
PubMed
Summary
This summary is machine-generated.

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Experts show better analogical problem solving by focusing on structural features, while novices are more prone to negative transfer when surface features align. This research clarifies analogical transfer in problem-solving behaviors.

Area of Science:

  • Cognitive Psychology
  • Problem Solving
  • Expertise Studies

Background:

  • Analogical transfer, using past solutions for new problems, is a key cognitive process.
  • Empirical evidence for analogical transfer, especially within short durations, remains challenging to establish.
  • Conflicting findings necessitate a refined framework for understanding analogical problem solving.

Purpose of the Study:

  • To propose a novel framework for conceptualizing analogical problem solving.
  • To reconcile conflicting empirical findings in the literature on analogical transfer.
  • To generate testable predictions regarding expert and novice problem-solving behaviors.

Main Methods:

  • Development of a theoretical framework for analogical problem solving.

Related Experiment Videos

  • Formulation of predictions based on expert vs. novice problem representations.
  • Empirical validation through three experiments using complex arithmetic word problems.

    • Main Results:

    • Experts demonstrated greater spontaneous positive transfer when problems shared structural features.
    • Novices exhibited stronger spontaneous negative transfer when problems shared surface features.
    • Experimental results supported the predictions concerning expert and novice transfer behaviors.

    Conclusions:

    • The proposed framework effectively explains analogical transfer differences between experts and novices.
    • Problem representation (structural vs. surface features) critically influences transfer direction and magnitude.
    • Understanding these differences is crucial for designing effective learning and problem-solving strategies.