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Combining intelligent methods for learner modelling in exploratory learning environments

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Most of the existing learning environments work in well-structured domains by making use of or combining AI techniques in order to create and update a learner model, provide individual and/or collaboration support and perform learner diagnosis. In this paper we present an approach that exploits the synergy of case-base reasoning and soft-computing for learner modelling in an ill-structured domain for exploratory learning. We present the architecture of the learner model, the knowledge formulation in terms of cases and illustrate its application in an exploratory learning environment for mathematical generalisation.
Original languageEnglish
Title of host publicationProceedings of the 1st International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2008), in conjunction with the 18th European Conference on Artificial Intelligence (ECAI-08)
EditorsI. Hatzilygeroudis, C. Koutsojannis, V. Palade
PublisherCEUR Workshop Proceedings
Pages13-18
Number of pages6
Edition375
Publication statusPublished - 21 Jul 2008
Event1st International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2008) in conjunction with the 18th European Conference on Artificial Intelligence (ECAI-08) - Patras, Greece
Duration: 21 Jul 2008 → 22 Jul 2008

Publication series

NameCEUR-WS
PublisherCEUR-WS
Number375

Workshop

Workshop1st International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2008) in conjunction with the 18th European Conference on Artificial Intelligence (ECAI-08)
CountryGreece
Period21/07/08 → 22/07/08

Documents

  • CIMA2008.pdf

    Accepted author manuscript (Post-print), 321 KB, PDF document

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