Explicit learning in Act-R

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    A popular distinction in the learning literature is the distinction between implicit and explicit learning. Although many studies elaborate on the nature of implicit learning, little attention is left for explicit learning. The unintentional aspect of implicit learning corresponds well to the mechanistic view of learning employed in architectures of cognition. But how to account for deliberate, intentional, explicit learning? This chapter argues that explicit learning can be explained by strategies that exploit implicit learning mechanisms. This idea is explored and modelled using the ACT-R theory (Anderson, 1993). An explicit strategy for learning facts in ACT-R's declarative memory is rehearsal, a strategy that uses ACT-R's activation learning mechanisms to gain deliberate control over what is learned. In the same sense, strategies for explicit procedural learning are proposed. Procedural learning in ACT-R involves generalisation of examples. Explicit learning rules can create and manipulate these examples. An example of these explicit rules will be discussed. These rules are general enough to be able to model the learning of three different tasks. Furthermore, the last of these models can explain the difference between adults and children in the discrimination-shift task.

    Originele taal-2English
    TitelMIND MODELLING: A COGNITIVE SCIENCE APPROACH TO REASONING, LEARNING AND DISCOVERY
    RedacteurenU Schmid, J Krems, F Wysotzky
    Plaats van productieD-49525 LENGERICH
    UitgeverijPabst Science Publishers
    Pagina's233 - 252
    Aantal pagina's20
    ISBN van geprinte versie3-933151-25-2
    StatusPublished - 1999
    Evenement1st European Workshop on Cognitive Modelling - , Germany
    Duur: 14-nov.-199616-nov.-1996

    Other

    Other1st European Workshop on Cognitive Modelling
    Land/RegioGermany
    Periode14/11/199616/11/1996

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