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Modelling the knowledge and reasoning of users in a knowledge-based authoring tool

Authors: Maria Virvou;

Modelling the knowledge and reasoning of users in a knowledge-based authoring tool

Abstract

This paper describes the domain-independent user modelling capabilities of a knowledge-based authoring tool. User modelling is primarily based on a cognitive theory that models human reasoning and is called Human Plausible Reasoning'. Moreover the cognitive theory is combined with the overlay modelling technique that aims to model students' knowledge as a subset of the domain knowledge. This method is used in the authoring tool to help the instructors create Intelligent Tutoring Systems (ITS) that may model both the learners' level of factual knowledge on a particular domain and their reasoning abilities within this domain. The resulting ITSs aim to allow the learners justify their answers to questions related to the domain taught. In this way, the system may assess the students' knowledge by taking into account the reasoning that the students have used. On the other hand, the students have the opportunity to consolidate what they have learned by elaborating on their knowledge. At the user interface level, students are able to work on questions in one of two different modes: the tutor mode and the co-learner mode.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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