LINGUIST List 12.1597

Mon Jun 18 2001

Confs: Interaction of Explicit & Implicit Learning

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  1. rsun, Interaction of Explicit & Implicit Learning: Symposium/ CogSci'2001

Message 1: Interaction of Explicit & Implicit Learning: Symposium/ CogSci'2001

Date: Sun, 17 Jun 2001 12:40:55 -0500
From: rsun <rsuncecs.missouri.edu>
Subject: Interaction of Explicit & Implicit Learning: Symposium/ CogSci'2001


 THE INTERACTION OF EXPLICIT AND IMPLICIT LEARNING

 A Symposium at CogSci'2001 (August 1-4, 2001), Edinburgh, Scotland

===============================================================
 Titles of the Talks:

Axel Cleeremans: ``Behavioral, neural, and computational correlates of
implicit and explicit learning"

Zoltan Dienes: ``The effect of prior knowledge on implicit learning"

Bob Mathews: ``Finding the optimal mix of implicit and explicit learning"

Ron Sun: ``The synergy of the implciit and the explicit"


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 The symposium will be held on August 4th, 2001, 2:30 - 4:10 pm.

 See http://www.hcrc.ed.ac.uk/cogsci2001/programme.html for futher
 details of the 23rd Cognitive Science Conference, Edinburgh, Scotland.

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Background:
The role of implicit learning in skill acquisition and the distinction
between implicit and explicit learning have been widely recognized in
recent years (see, e.g., Reber 1989, Stanley et al 1989, Willingham et
al 1989, Anderson 1993), Although implicit learning has been actively
investigated, the complex and multifaceted interaction between the
implicit and the explicit and the importance of this interaction have
not been universally recognized; to a large extent, such interaction
has been downplayed or ignored, with only a few notable exceptions.
Research has been focused on showing the LACK of explicit learning
in various learning settings (see especially Lewicki et al 1987) and on
the controversies stemming from such claims.

Despite the lack of studies of interaction, it has been gaining
recognition that it is difficult, if not impossible, to find a situation
in which only one type of learning is engaged (Reber 1989, Seger 1994,
but see Lewicki et al 1987). Our review of existing data has indicated
that, while one can manipulate conditions to emphasize one or the other
type, in most situations, both types of learning are involved, with
varying amounts of contributions from each (see, e.g., Sun et al 2000;
see also Stanley et al 1989, Willingham et al 1989).

Likewise, in the development of cognitive architectures (e.g., Rosenbloom
et al 1993, Anderson 1993), the distinction between procedural and
declarative knowledge has been proposed for a long time, and advocated
or adopted by many in the field (see especially Anderson 1993).
The distinction maps roughly onto the distinction between the explicit and
implicit knowledge, because procedural knowledge is generally inaccessible
while declarative knowledge is generally accessible and thus explicit.
However, in work on cognitive architectures, focus has been almost
exclusively on ``top-down" models (that is, learning first explicit
knowledge and then implicit knowledge on the basis of the former),
the bottom-up direction (that is, learning first implicit knowledge
and then explicit knowledge, or learning both in parallel) has been
largely ignored, paralleling and reflecting the related neglect of
%the complex and multifaceted the interaction of explicit and implicit
processes in the skill learning literature. However, there are a few
scattered pieces of work that did demonstrate the parallel development of
the two types of knowledge or the extraction of explicit knowledge from
implicit knowledge (e.g, Willingham et al 1989, Stanley et al 1989,
Sun et al 2000), contrary to usual top-down approaches in developing
cognitive architectures.

Many issues arise with regard to the interaction between implicit and
explicit processes, which we need to look into if we want to better
understand this interaction:

 How can we best capture implicit processes computationally? How can we
 best capture explicit processes computationally?

 How do the two types of knowledge develop along side each other and
 influence each other's development?

 Is bottom-up learning (or parallel learning) possible, besides top-down
 learning? How can they (bottom-up learning, top-down learning, and
 parallel learning) be realized computationally?

 How do the two types of acquired knowledge interact during skilled
 performance? What is the impact of that interaction on performance?
 How do we capture such impact computationally?


===========================================================================
Prof. Ron Sun http://www.cecs.missouri.edu/~rsun
CECS Department phone: (573) 884-7662
University of Missouri-Columbia fax: (573) 882 8318 
201 Engineering Building West
Columbia, MO 65211-2060 email: rsuncecs.missouri.edu 

http://www.cecs.missouri.edu/~rsun
http://www.cecs.missouri.edu/~rsun/journal.html
http://www.elsevier.com/locate/cogsys
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