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Selecting Theories in an Ontology-Based ITS Authoring Environment

  • Jacqueline Bourdeau
  • Riichiro Mizoguchi
  • Valéry Psyché
  • Roger Nkambou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3220)

Abstract

This paper introduces the rationale for concrete situations in the authoring process that can exploit a theory-aware Authoring Environment. It illustrates how Ontological Engineering (OE) can be instrumental in representing the declarative knowledge needed, and how an added value in terms of intelligence can be expected for both authoring and for learning environments.

Keywords

Instructional Strategy Authoring Process Declarative Knowledge Intelligent Tutor System Authoring Tool 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Mizoguchi, R., Bourdeau, J.: Using Ontological Engineering to Overcome Common AIED Problems. International Journal of Artificial Intelligence and Education 11, 107–121 (2000), (Special Issue on AIED 2010)Google Scholar
  2. 2.
    Mizoguchi, R., Bourdeau, J.: Theory-Aware Authoring Environment: Ontological Engineering Approach. In: Proc. of the ICCE Workshop on Concepts and Ontologies in Web-based Educational Systems, Technische Universiteit Eindhoven (2002)Google Scholar
  3. 3.
    Mizoguchi, R., Sinitsa, K.: Architectures and Methods for Designing Cost-Effective and Reusable ITSs. In: Lesgold, A.M., Frasson, C., Gauthier, G. (eds.) ITS 1996. LNCS, vol. 1086, Springer, Heidelberg (1996)Google Scholar
  4. 4.
    Chen, W., et al.: Ontological Issues in an Intelligent Authoring Tool. In: ICCE 1998 (1998)Google Scholar
  5. 5.
    Mizoguchi, R., et al.: Construction and Deployment of a Plant Ontology. In: Dieng, R., Corby, O. (eds.) EKAW 2000. LNCS (LNAI), vol. 1937, pp. 113–128. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  6. 6.
    Mizoguchi, R.: Ontology-based systematization of functional knowledge. In: TMCE 2002:Tools and methods of competitive engineering, China (2002)Google Scholar
  7. 7.
    Rubin, D.L., et al.: Representing genetic sequence data for pharmacogenomics: an evolutionary approach using ontological and relational models, vol. 18(1), pp. 207–215 (2002)Google Scholar
  8. 8.
    Bourdeau, J., Mizoguchi, R.: Collaborative Ontological Engineering of Instructional Design Knowledge for an ITS Authoring Environment. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, p. 399. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  9. 9.
    Murray, T.: Authoring intelligent tutoring systems: an analysis of the state of the art. IJAIED 10, 98–129 (1999)Google Scholar
  10. 10.
    Kay, J., Holden, S.: Automatic Extraction fo Ontologies from Teaching Document Metadata. In: ICCE Workshop on Concepts and Ontologies in Web-based Educational Systems, Technische Universiteit Eindhoven (2002)Google Scholar
  11. 11.
    Paquette, G., Rosca, I.: Organic Aggregation of Knowledge Objects in Educational Systems. Canadian Journal of Learning and Technology 28(3), 11–26 (2002)Google Scholar
  12. 12.
    Aroyo, L., Dicheva, D.: Authoring Framework for Concept-based Web Information Systems. In: ICCE Workshop on Concepts and Ontologies in Web-based Educational Systems, Technische Universiteit Eindhoven (2002)Google Scholar
  13. 13.
    Nkambou, R., Frasson, C., Gauthier, G.: Cream-Tools: an authoring environment for knowledge engineering in intelligent tutoring systems. In: B.S.a.A.S., Murray, T. (eds.) Authoring Tools for Advanced Technology Learning Environments: Toward cost-effective adaptative, interactive, and intelligent educational software, Kluwer Academic Publishers, Dordrecht (2002)Google Scholar
  14. 14.
    Reigeluth, C.M. (ed.): Instructional theories in action: lessons illustrating, selected theories and models. LEA (1993)Google Scholar
  15. 15.
    Mizoguchi, R.: A Step Towards Ontological Engineering. In: 12th National Conference on AI of JSAI (1998)Google Scholar
  16. 16.
    Davis, R., Shrobe, H., Szolovits, P.: What Is a Knowledge Representation? AI Magazine (1993)Google Scholar
  17. 17.
    Gruninger, M., Fox, M.S.: Methodology for the Design and Evaluation of Ontologies. In: Workshop on Basic Ontological Issues in Knowledge Sharing, IJCAI 1995, Montreal (1995)Google Scholar
  18. 18.
    Noy, N.F., McGuinness, D.L.: Ontology Development 101: A Guide to Creating Your First Ontology (2000)Google Scholar
  19. 19.
    Kozaki, K., et al.: Development of an environment for building ontologies which is based on a fundamental consideration of relationship and role (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Jacqueline Bourdeau
    • 1
  • Riichiro Mizoguchi
    • 2
  • Valéry Psyché
    • 1
    • 3
  • Roger Nkambou
    • 3
  1. 1.Centre de recherche LICEFTélé-universitéMontréalCanada
  2. 2.ISIROsaka UniversityOsakaJapan
  3. 3.Département d’informatiqueUniversité du Québec à MontréalMontréalCanada

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