Reference network: A genetic model for Intelligent Tutoring Systems

  • Nicaud Jean-François
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 608)


Knowledge evolution and curriculum management are generally components that remain external to ITSs. Most ITSs are situated in a more or less explicit theory of learning and teaching, but few implementations incorporate pieces of this theory. In this paper, we review previous works dealing with knowledge evolution and stand reference knowledge state as a basic concept for the domain knowledge of an ITS. We present our current model and ITS for algebraic problem-solving and set up knowledge evolution issues in algebra. We define and describe the reference network, a theoretical domain model allowing to include didactic evolutions and to share the student's tutoring between the ITS and the teacher.


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  1. 1.
    Baron M., Simonnet P.: Génération d'exercices en algèbre. Premières approches dans le cadre du projet APLUSIX. Proceedings of ITS'92, Montréal, Springer Verlag, 1992.Google Scholar
  2. 2.
    Dillenbourg P., Hilaro M., Mendelsohn P., Schneider D.: The MEMOLAB Project. TECFA report 91-5, University of Geneva, 1991.Google Scholar
  3. 3.
    Goldstein I.P.: The Genetic Graph: a Representation for the Evolution of Procedural knowledge. Intelligent Tutoring Systems (Sleeman, Brown eds). Academic Press 1982.Google Scholar
  4. 4.
    Les gold A.: Toward a Theory of Curriculum for Use in Designing Intelligent Instructional Systems. Learning Issues for Intelligent Tutoring Systems (Mandl & Lesgold eds), Springer Verlag, 1988.Google Scholar
  5. 5.
    Nicaud J.F., Saïdi M.: Explanation of algebraic reasoning: the APLUSIX System. Lecture Notes in Artificial Intelligence number 444, Springer-Verlag, 1989.Google Scholar
  6. 6.
    Nicaud J.F., Aubertin C, Nguyen-Xuan A., Saïdi M., Wach P.: APLUSIX: a learning environment for acquiring problem solving abilities. Cognitiva 90, Madrid, 1990.Google Scholar
  7. 7.
    Nicaud J.F.: Reference Network: A Genetic Model for Intelligent Tutoring Systems (long paper). LRI report, University of Paris 11, 1992.Google Scholar
  8. 8.
    Saïdi M.: Evaluation optimisée et planification en résolution d'exercices d'algèbre. Proceedings of 2ème journées EIAO de Cachan, 1991.Google Scholar
  9. 9.
    Vergnaud G.: La théorie des champs conceptuels. Recherche en didactique des mathématiques. Vol 10.2, La Pensée Sauvage, Grenoble 1991.Google Scholar
  10. 10.
    White Y.W., Frederiksen J.R.: Causal Model Progression as a foundation for Intelligent Learning Environments. Artificial Intelligence (42), 1990.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Nicaud Jean-François
    • 1
  1. 1.L.R.I., CNRS URA 410Université de Paris 11Orsay cedexFrance

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