Learning and interactivity in solving a transformation problem.

Outside the psychologist's laboratory, thinking proceeds on the basis of a great deal of interaction with artefacts that are recruited to augment problem-solving skills. The role of interactivity in problem solving was investigated using a river-crossing problem. In Experiment 1A, participants compl...

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Published in:Memory & Cognition Vol. 43; no. 5; pp. 723 - 736
Main Authors: Guthrie, Lisa, Vallée-Tourangeau, Frédéric, Vallée-Tourangeau, Gaëlle, Howard, Chelsea
Format: Article
Published: Springer Nature Jul2015
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Jul2015
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      pub: Springer Nature
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        10.3758/s13421-015-0504-8
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        au:
          Guthrie, Lisa
          Vallée-Tourangeau, Frédéric
          Vallée-Tourangeau, Gaëlle
          Howard, Chelsea
        affil: Department of Psychology, Kingston University, Kingston upon Thames KT1 2EE UK
      su:
        Analysis of variance
        Cognition
        Learning
        Problem solving
        Undergraduates
        Statistics
        Transfer of training
        Data analysis
        Descriptive statistics
      sug:
        subj:
          Analysis of variance
          Cognition
          Learning
          Problem solving
          Undergraduates
          Statistics
          Transfer of training
          Data analysis
          Descriptive statistics
      keyword:
        Distributed cognition
        Epistemic actions
        Interactivity
        Distributed cognition
        Epistemic actions
        Interactivity
      ab: Outside the psychologist's laboratory, thinking proceeds on the basis of a great deal of interaction with artefacts that are recruited to augment problem-solving skills. The role of interactivity in problem solving was investigated using a river-crossing problem. In Experiment 1A, participants completed the same problem twice, once in a low interactivity condition, and once in a high interactivity condition (with order counterbalanced across participants). Learning, as gauged in terms of latency to completion, was much more pronounced when the high interactivity condition was experienced second. When participants first completed the task in the high interactivity condition, transfer to the low interactivity condition during the second attempt was limited; Experiment 1B replicated this pattern of results. Participants thus showed greater facility to transfer their experience of completing the problem from a low to a high interactivity condition. Experiment 2 was designed to determine the amount of learning in a low and high interactivity condition; in this experiment participants completed the problem twice, but level of interactivity was manipulated between subjects. Learning was evident in both the low and high interactivity groups, but latency per move was significantly faster in the high interactivity group, in both presentations. So-called problem isomorphs instantiated in different task ecologies draw upon different skills and abilities; a distributed cognition analysis may provide a fruitful perspective on learning and transfer.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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