Learning - Implicit vs. Explicit: BBS Call for Commentators

[Stevan Harnad]

Below is the abstract of a forthcoming target article by

        D.R. SHANKS and M.F. ST. JOHN on

        IMPLICIT VS. EXPLICIT LEARNING

that has been accepted for publication in Behavioral and Brain Sciences
(BBS), an international, interdisciplinary journal providing Open Peer
Commentary on important and controversial current research in the
biobehavioral and cognitive sciences.

Commentators must be current BBS Associates or nominated by a current
BBS Associate. To be considered as a commentator for this article, to
suggest other appropriate commentators, or for information about how to
become a BBS Associate, please send email to:

harnad at clarity.princeton.edu  or harnad at pucc.bitnet        or write to:
BBS, 20 Nassau Street, #240, Princeton NJ 08542  [tel: 609-921-7771]

To help us put together a balanced list of commentators, please give
some indication of the aspects of the topic on which you would bring
your areas of expertise to bear if you were selected as a commentator.
An electronic draft of the full text is available for inspection by
anonymous ftp according to the instructions that follow after the abstract.
____________________________________________________________________

        CHARACTERISTICS OF DISSOCIABLE HUMAN LEARNING SYSTEMS

                David R. Shanks
                Department of Psychology
                University College London
                London WC1E 6BT, England
                david.shanks at psychol.ucl.ac.uk

                Mark F. St. John
                Department of Cognitive Science
                University of California at San Diego
                La Jolla, CA 92093
                mstjohn at cogsci.ucsd.edu

        KEYWORDS: learning; memory; consciousness; explicit/implicit
                  processes; rules; instances; unconscious processes

        ABSTRACT: The proposal that there exist independent explicit
        and implicit learning systems is based on two further
        distinctions: (i) learning that takes place with versus without
        concurrent awareness, and (ii) learning that involves the
        encoding of instances (or fragments) versus the induction of
        abstract rules or hypotheses. Implicit learning is assumed to
        involve unconscious rule learning. We examine the implicit
        learning evidence from subliminal learning, conditioning,
        artificial grammar learning, instrumental learning, and
        reaction times in sequence learning. Unconscious learning has
        not been satisfactorily established in any of these areas. The
        assumption that learning in some of these tasks (e.g.,
        artificial grammar learning) is predominantly based on rule
        abstraction is questionable. When subjects cannot report the
        "implicitly learned" rules that govern stimulus selection, this
        is often because their knowledge consists of instances or
        fragments of the training stimuli rather than rules. In contrast
        to the distinction between conscious and unconscious learning,
        the distinction between instance and rule learning is a sound
        and meaningful way of taxonomizing human learning. We discuss
        various computational models of these two forms of learning.

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feel you would bring to bear on what aspect of the article.
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