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Connectionist Modelling and Education

Connectionist Modelling and Education Connectionist modelling and education Colin W. Evers The University ofHong Kong Introduction The main aim of this paper is to describe and explain some recent work on arti­ ficial neural networks (ANNs) that should be of interest to researchers in edu­ cational studies. These networks are also known more generally in the literature as connectionist systems. Although models of cognition would be of obvious rel­ evance to those seeking to understand teaching and learning, a subsidiary aim of the paper will be to show that ANNs are relevant to the study of a wider range of educational phenomena. The plan of the discussion is as follows. First, the development of ANN models is located within the context of the rise of what might usefully be called the 'new cognitive science'. Then a taxonomy of the main models is provided, together with a fairly detailed account of the workings of one particular type. Three quite diverse applications are then discussed and their implications for edu­ cation canvassed. Finally the significance of ANN models for representing both static and dynamical aspects of knowledge is touched upon. Since applications involve computer simulations, there will also be mention of a number of helpful http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Australian Journal of Education SAGE

Connectionist Modelling and Education

Evers, Colin W.
Australian Journal of Education , Volume 44 (3): 17 – Nov 1, 2000
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References (13)

Publisher
SAGE
Copyright
© 2000 Australian Council for Educational Research
ISSN
0004-9441
eISSN
2050-5884
DOI
10.1177/000494410004400302
Publisher site
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Abstract

Connectionist modelling and education Colin W. Evers The University ofHong Kong Introduction The main aim of this paper is to describe and explain some recent work on arti­ ficial neural networks (ANNs) that should be of interest to researchers in edu­ cational studies. These networks are also known more generally in the literature as connectionist systems. Although models of cognition would be of obvious rel­ evance to those seeking to understand teaching and learning, a subsidiary aim of the paper will be to show that ANNs are relevant to the study of a wider range of educational phenomena. The plan of the discussion is as follows. First, the development of ANN models is located within the context of the rise of what might usefully be called the 'new cognitive science'. Then a taxonomy of the main models is provided, together with a fairly detailed account of the workings of one particular type. Three quite diverse applications are then discussed and their implications for edu­ cation canvassed. Finally the significance of ANN models for representing both static and dynamical aspects of knowledge is touched upon. Since applications involve computer simulations, there will also be mention of a number of helpful

Journal

Australian Journal of Education – SAGE

Published: Nov 1, 2000

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