Modelling conceptual change: An interdisciplinary approach

  • Filippo Neri
  • Lorenza Saitta
  • Andrée Tiberghien
Machine Learning 1
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1321)


A computational approach to the simulation of cognitive models of conceptual change in children learning elementary physics is presented. The student's mental model is inferred from a sequence of interviews collected along a period of eleven teaching sessions. Goal of the simulation is to support the cognitive scientist's investigation of learning in humans. The hypothesized cognitive models are based on a theory of conceptual change, derived from psychology results and educational experiences, which accounts for the evolution of the student's knowledge over a learning period. A Machine Learning (ML) system, able to handle domain knowledge (including a causal model of the domain), has been chosen as tool for the simulation of the cognitive models evolution. The system performs knowledge revision and provides causal explanation for its conclusions.

Content areas

cognitive modeling machine learning causality 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Filippo Neri
    • 1
  • Lorenza Saitta
    • 1
  • Andrée Tiberghien
    • 2
  1. 1.Dipartimento di InformaticaUniversità di TorinoTorinoItaly
  2. 2.Ecole Normale Supérieure de LyonEquipe COAST de l'UMR GRIC CNRS - Université Lyon 2Lyon Cedex 07France

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