Automatic extraction of knowledge from student essays Online publication date: Wed, 07-Dec-2005
by Maria Vargas-Vera, Emanuela Moreale
International Journal of Knowledge and Learning (IJKL), Vol. 1, No. 4, 2005
Abstract: This paper presents a characterisation of argumentation in student essays and analyses patterns for extracting knowledge from them. Having analysed their complexity in light of the kinds of logic that may be used in an automatic argumentation extraction system, the main characteristic of these patterns appears to be the polymorphism of the pattern variables. Therefore, systems that learn patterns automatically ought to be able to generate many-sorted logic formulae, so that polymorphic types may be associated to the extraction slots (or – equivalently – to a logic formulae). An analysis of existing (pattern learning) systems was carried out to gauge the possibility of using them within our framework. However, we concluded that none of the existing systems can handle our requirements. Finally, we present our vision of an agent-based student portal as the front-end of a system that can locate argumentation links in a student essay and integrates with related educational services.
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