Modelling and optimizing the process of learning mathematics

Authors:
Tanja Käser;Alberto Giovanni Busetto;Gian-Marco Baschera;Juliane Kohn;Karin Kucian;Michael von Aster;Markus Gross
Affiliations:
Department of Computer Science, ETH Zurich, Zurich, Switzerland;Department of Computer Science, ETH Zurich, Zurich, Switzerland,Competence Center for Systems Physiology and Metabolic Diseases, Zurich, Switzerland;Department of Computer Science, ETH Zurich, Zurich, Switzerland;Department of Psychology, University of Potsdam, Potsdam, Germany;MR-Center, University Children's Hospital, Zurich, Switzerland;MR-Center, University Children's Hospital, Zurich, Switzerland,Department of Psychology, University of Potsdam, Potsdam, Germany,Department of Child and Adolescent Psychiatry, German Red Cross Hos ...;Department of Computer Science, ETH Zurich, Zurich, Switzerland
Venue:
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
Year:
2012

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Abstract

This paper introduces a computer-based training program for enhancing numerical cognition aimed at children with developmental dyscalculia. Through modelling cognitive processes and controlling the level of their stimulation, the system optimizes the learning process. Domain knowledge is represented with a dynamic Bayesian network on which the mechanism of automatic control operates. Accumulated knowledge is estimated to select informative tasks and to evaluate student actions. This adaptive training environment equally improves success and motivation. Large-scale experimental data quantifies substantial improvement and validates the advantages of the optimized training.