Advanced Educational Technology: Knowledge Revisited

  • N. Balacheff
Conference paper
Part of the NATO ASI Series book series (volume 145)

Abstract

AET R&D cannot avoid the question of the nature of knowledge which is at the core of both learning and teaching or training. The way this problem can be handled for the purpose of design and implementation of systems supporting human learning, the question of knowledge representations for the purpose of computational models as well as the question of the place of knowledge in person/machine interactions suggest that knowledge should be revisited in the light of the AET research programme. In this chapter I consider this question from the point of view of computational modeling and situated AET.

Keywords

Epistemology artificial intelligence computational transposition knowledge modeling learner modeling human-machine interaction didactical contract intelligent learning environment educational technology 
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Balacheff, N. (1991) Contribution de la didactique et de l’épistémologie aux recherches en EIAO. In: Bellissant C. (ed.) Actes des XIII° Journées francophonessur l’informatique. Grenoble-Genève. 9–38. Grenoble: IMAGGoogle Scholar
  2. Balacheff, N. (1993) La transposition informatique. Note sur un nouveau problem pour la didactique. In: Artigue, M., Gras, R., Laborde, C., Tavignot, P. (eds.) 20 ans de didactique des mathématiques en France. Grenoble: La Pensée SauvageGoogle Scholar
  3. Balacheff, N., Sutherland, R. (1994) Epistemological domain of validity of micro worlds, the case of Logo and Cabri-géomètre. In: Lewis, R., Mendelshon, P. (eds.) Lessons from learning. Proceedings of the IFIP WG3 working group A46, 137–150. Amsterdam: North-Holland/ElsevierGoogle Scholar
  4. Bourdieu, P. (1980) Le sens pratique. Paris: Editions de MinuitGoogle Scholar
  5. Bresenham, J. E. (1988). Anomalies in incremental line rastering. In F40Google Scholar
  6. Brousseau, G. (1972). Processus de mathématisation. In: La Mathématique à l’école élémentaire. 428–442. Paris: Association des Professeurs de Mathématiques de l’Enseignement PublicGoogle Scholar
  7. Brousseau, G. (1986). Fondements et méthodes de la didactique des mathématiques. Recherches en didactique des mathématiques 7(2) 33–116Google Scholar
  8. Chevallard, Y. (1985). La transposition didactique. (Nouvelle édition revue et augmentée, 1991). Grenoble: Editions La Pensée SauvageGoogle Scholar
  9. Clancey, W.J. (1993) Guidon-Manage revisited: A socio-technical system approach. Journal of Artificial Intelligence in Education 4(1) 5–34Google Scholar
  10. Dijkstra, S., Krammer, H.P.M., van Merriënboer, J.J.G. (eds.) (1992) Instructional models in computer-based learning environments. F104MATHGoogle Scholar
  11. Elsom-Cook, M. (1990) Guided discovery tutoring. Chapman, LondonGoogle Scholar
  12. Hoyles, C. (1993) Microworlds/Schoolworlds: The transformation of an innovation. In F121Google Scholar
  13. Laborde, C. (1992) Solving problems in computer based geometry environments: the influence of the features of the software. Zentrablatt für Didactik des Mathematik, 92(4) 128–135MathSciNetGoogle Scholar
  14. Laborde, J.-M. (1986) Proposition d’un Cabri-géomètre, incluant la notion de figures manipulables. Sujet d’année spéciale ENSIMAGGoogle Scholar
  15. Laborde, J.-M. (1993) Intelligent microworlds and learning environments. In F117Google Scholar
  16. Lave, J. (1988) Cognition in practice. Cambridge, UK: Cambridge University PressCrossRefGoogle Scholar
  17. Lesgold, A., Katz, S., Greenberg, L., Hughes, E., Egan, G. (1992) Extensions of intelligent tutoring paradigms to support collaborative learning. In F104Google Scholar
  18. McCalla, G. (1988) Intelligent tutoring systems: Navigating the rocky road to success. InF96Google Scholar
  19. McCalla, G. (1992) The central importance of student modelling to intelligent tutoring. In F91Google Scholar
  20. Miller, J.R. (1988) The role of human-computer interaction in intelligent tutoring systems. In: Poison, M.C., Richardson, J.J. (eds.) Foundations of intelligent tutoring systems, 143–189. Hillsdale, NJ: Lawrence Erlbaum AssociatesGoogle Scholar
  21. Nicaud, J.-F. (1992). A general model of algebraic problem solving for the design of interactive learning environments. In F89Google Scholar
  22. Ohlsson, S. (1988) Towards intelligent tutoring systems that teach knowledge rather than skills: Five research questions. In F96Google Scholar
  23. Popper, K. (1979) Objective knowledge. Oxford, UK: Oxford University PressGoogle Scholar
  24. Self, J. (1990) Theoretical foundations for intelligent tutoring systems. Journal of Artificial Intelligence in Education 1(4) 3–14Google Scholar
  25. Self, J. (1992) Computational mathetics: The missing link in intelligent tutoring systems research? In F91Google Scholar
  26. Sleeman, D.H. (1982). Inferring (mal) rules from pupils’ protocols. Proceedings of the European Conference on Artificial Intelligence 160–164. Paris: université d’OrsayGoogle Scholar
  27. Smith, R. B. (1988) A prototype futuristic technology for distance education. In F96Google Scholar
  28. Teodoro, E.D. (1992) Direct manipulation on physical models in computerized exploratory laboratory. In F84Google Scholar
  29. Tiberghien, A. (1992) Analysis of interfaces from the points of view of epistemology and didactics. In F86Google Scholar
  30. Verdejo, F.M. (1992) A framework for instructional planning and discourse modeling in intelligent tutorial systems. In F91Google Scholar
  31. Vergnaud, G. (1992) Conceptual fields, problem-solving and intelligent computer tools. In F84Google Scholar
  32. Vivet, M. (1992) Uses of ITS, which role for the teacher? In F91Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • N. Balacheff
    • 1
  1. 1.DidaTech, Laboratoire LSD2IMAG-CNRS & Université Joseph FourierGrenoble Cedex 9France

Personalised recommendations