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Classification Networks: A Knowledge Representation Scheme for Curriculum Prescription

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Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Intelligent Tutoring Systems. Pages 447-451.

Abstract

This paper presents a classification scheme that articulates the categorisation of subject matter. Two basic classificatory devices are inb'Oduced: (a) a feature representing the resulting category characterised by a property that the feature denotes, (b) a dimension representing a perspective that partitions the Universe of Discourse (UoD) or a category. A classification based on a dimension can be further classified into the categories it has formed. Dimensions can be juxtaposed to form a classification based on multiple perspectives. The classificatory devices of features and dimensions, which form a classification network, support a wide range of subject organisation types, viz. (a) conceptual organisation, (b) procedural organisation and (c) theoretical organisation. The purpose of the approach is to support the clarity, simplicity and maintainability of large scale general ITS development. Some simple course organisation examples using classification networks are also presented.

Kwok-Keung Yum, and Thomas J. Richards. 1993. Classification Networks: A Knowledge Representation Scheme for Curriculum Prescription. In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93. IJCAI, 447–451. https://ijcai.org/proceedings/1993/63
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