A Collaborative Learning Design Environment to Integrate Practice and Learning Based on Collaborative Space Ontology and Patterns

  • Masataka Takeuchi
  • Yusuke Hayashi
  • Mitsuru Ikeda
  • Riichiro Mizoguchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4053)


The integration of practice and learning is a key to cultivation of organizational capability for creating or inheriting intellect. In this paper, firstly we address the critical research issues for collaborative space design to integrate practice and learning. Following the discussion, we have built an ontology which specifies the structure of the collaborative learning, described patterns of a collaborative space by reference to the learning theories and developed an intelligent function to support a collaborative space design on ontology-based KM environment, Kfarm, as a foundation for supporting collaborative space design.


Organizational Member Abstract Design Computer Support Collaborative Learn Practical Goal Collaborative Space 
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  1. 1.
    Davenport, T., Prusaki, L.: Working Knowledge. Harvard Business School Press, Boston (1998)Google Scholar
  2. 2.
    Wenger, E., McDermott, R., Snyder, M.W.: Cultivating Communities of Practice. Harvard Business School Press, Boston (2002)Google Scholar
  3. 3.
    Nonaka, I., Toyama, R., Konno, N.: Seci, ba, leadership: a unified model of dynamic knowledge creation. Long Range Planning 4-5/1, 1–31 (2000)Google Scholar
  4. 4.
    Hayashi, Y., Tsumoto, H., Ikeda, M., Mizoguchi, R.: Kfarm: An ontology-aware support environment for learning-oriented knowledge management. The Journal of Information and Systems in Education 1(1), 80–89 (2003)Google Scholar
  5. 5.
    Mizoguchi, R., Bourdeau, J.: Using ontological engineering to overcome ai-ed problems. Int. J. of Artificial Intelligence in Education 11(2), 107–121 (2000)Google Scholar
  6. 6.
    Ikeda, M., Seta, K., Mizoguchi, R.: Task ontology makes it easier to use authoring tools. In: Proc. of IJCAI 1997, Nagoya, Japan, pp. 342–347 (1997)Google Scholar
  7. 7.
    Hayashi, Y., Tsumoto, H., Ikeda, M., Mizoguchi, R.: An Intellectual Genealogy Graph Affording a Fine Prospect of Organizational Learning. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 10–20. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  8. 8.
    Inaba, A., Supnithi, T., Ikeda, M., Mizoguchi, R., Toyoda, J.: How Can We Form Effective Collaborative Learning Groups? In: Gauthier, G., VanLehn, K., Frasson, C. (eds.) ITS 2000. LNCS, vol. 1839, pp. 282–291. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  9. 9.
    Kozaki, K., Kitamura, Y., Ikeda, M., Mizoguchi, R.: Hozo: An environment for building/Using ontologies based on a fundamental consideration of "Role" and "Relationship". In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS, vol. 2473, pp. 213–218. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  10. 10.
    Coplien, J.O.: A development process generative pattern language. In: Coplien, J.O., Schmidt, D. (eds.) Pattern Languages of Program Design, pp. 183–237. Addison-Wesley, Reading (1995)Google Scholar
  11. 11.
    Vygotsky, L.S.: The problem of cultural development of the child. II. Journal of Genetic Psychology 36, 414–434 (1929)Google Scholar
  12. 12.
    Vygotsky, L.S.: Mind in Society: The development of higher psychological processes. Harvard University Press, Cambridge (1930) (re-published 1978)Google Scholar
  13. 13.
    Collins, A.: Cognitive apprenticeship and instructional technology. In: Idol, L., Jones, B.F. (eds.) Educational values and cognitive instruction: Implications for reform, pp. 121–138. Lawrence Erlbaum Associates, Hillsdale (1991)Google Scholar
  14. 14.
    Bandura, A.: Social Learning Theory. General Learning Press (1971)Google Scholar
  15. 15.
    Papert, S.: Mindstorms: Children, Computers, and Powerful Ideas. Harvester Wheatsheaf (1980)Google Scholar
  16. 16.
    Lave, J.: Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge University Press, Cambridge (1988)CrossRefGoogle Scholar
  17. 17.
    Lave, J., Wenger, E.: Situated Learning: Legitimate peripheral participation. Cambridge University Press, Cambridge (1991)Google Scholar
  18. 18.
    Resnick, L.B.: Shared cognition: Thinking as social practice. In: Resnick, L., Levine, J., Teasley, S. (eds.) Perspectives on Socially Shared Cognition, Hyattsville, MD, pp. 1–22. American Psychological Association (1991)Google Scholar
  19. 19.
    Salomon, G.: What does the design of effective cscl require and how do we study its effects? In: Proc. of 2nd ACM Conference on Computer Supported Collaborative Learning, vol. 21(3). ACM Press, New York (1992)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Masataka Takeuchi
    • 1
  • Yusuke Hayashi
    • 1
  • Mitsuru Ikeda
    • 2
  • Riichiro Mizoguchi
    • 1
  1. 1.The Institute of Scientific and Industrial ResearchOsaka University 
  2. 2.Japan Advanced Institute of Science and Technology 

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