Metadata and Ontologies in Learning Resources Design

  • Christian Vidal C.
  • Alejandra Segura Navarrete
  • Víctor Menéndez D.
  • Alfredo Zapata Gonzalez
  • Manuel Prieto M.
Part of the Communications in Computer and Information Science book series (CCIS, volume 111)

Abstract

Resource design and development requires knowledge about educational goals, instructional context and information about learner’s characteristics among other. An important information source about this knowledge are metadata. However, metadata by themselves do not foresee all necessary information related to resource design. Here we argue the need to use different data and knowledge models to improve understanding the complex processes related to e-learning resources and their management. This paper presents the use of semantic web technologies, as ontologies, supporting the search and selection of resources used in design. Classification is done, based on instructional criteria derived from a knowledge acquisition process, using information provided by IEEE-LOM metadata standard. The knowledge obtained is represented in an ontology using OWL and SWRL. In this work we give evidence of the implementation of a Learning Object Classifier based on ontology. We demonstrate that the use of ontologies can support the design activities in e-learning.

Keywords

Ontology Instructional Design knowledge acquisition web semantic 

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References

  1. 1.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 28–37 (2001)CrossRefGoogle Scholar
  2. 2.
    Horrocks, I., Patel-Schneider, P., McGuinness, D., Welty, C.: OWL: a Description Logic Based Ontology Language for the Semantic Web. In: Baader, F., et al. (eds.) The Description Logic Handbook: Theory, Implementation, and Applications, 2nd edn., ch. 14. Cambridge University Press, Cambridge (2007)Google Scholar
  3. 3.
    OWL Web Ontology Language- Overview (2010), http://www.w3.org/TR/owl-features/
  4. 4.
    Hernández, H., Saiz, M.: Ontologías mixtas para la representación conceptual de objetos de aprendizaje. Procesamiento del Lenguaje Natural N. 38 (abr. 2007), pp. 99–106 (2007)Google Scholar
  5. 5.
    Marengo, A., Albanese, D., Convertini, N., Marengo, V., Scalera, M., Serra, A.: Ontological support for the creation of learning objects. In: 28th International Conference on Information Technology Interfaces IEEE, pp. 361–366 (2006)Google Scholar
  6. 6.
    Zouaq, A., Nkambou, R., Frasson, C.: An Integrated Approach for Automatic Aggregation of Learning Knowledge Objects. Interdisciplinary Journal of Knowledge and Learning Objects (IJKLO) (3), 135–162 (2007)Google Scholar
  7. 7.
    Reigeluth, C.M.: What Is Instructional-Design Theory and How Is It Changing? In: Reigeluth, C.M. (ed.) Instructional-Design Theories and Models. A New Paradigm of Instructional Theory, vol. II. Lawrence Erlbaum Associates, Mahwah (1999)Google Scholar
  8. 8.
    Sicilia, M.A.: On the general structure of ontologies of instructional models. In: SPDECE 2007: Proceedings of the IV Simposio Pluridisciplinar sobre Diseño, Evaluación y Desarrollo de Contenidos Educativos Reutilizables, Bilbao, Spain (2007)Google Scholar
  9. 9.
    Hayashi, Y., Bourdeau, J., Mizoguchi, R.: Ontological Support for a Theory-Eclectic Approach to Instructional and Learning Design. In: Nejdl, W., Tochtermann, K. (eds.) EC-TEL 2006. LNCS, vol. 4227, pp. 155–169. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Willey, D.: Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. In: Wiley, D.A., et al, eds. (2007), http://www.reusability.org/read/chapters/wiley.doc
  11. 11.
    Draft Standard for Learning Object Metadata. IEEE P1484.12.1, IEEE Learning Technology Standards Committee (2002), http://ltsc.ieee.org/wg12/files/LOM_1484_12_1_v1_Final_Draft.pdf
  12. 12.
    Romero, C., Ventura, S.: Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications 33(1), 135–146 (2007)CrossRefGoogle Scholar
  13. 13.
    Romero, C., Ventura, S., Garcia, E.: Data mining in course management systems: Moodle case study and tutorial. Computers & Education 51(1), 368–384 (2008)CrossRefGoogle Scholar
  14. 14.
    Prieto, M., Menéndez, V., Segura, A., Vidal, C.: A Recommender System Architecture for Instructional Engineering. In: Lytras, M.D., et al. (eds.) WSKS 2008. LNCS (LNAI), vol. 5288, pp. 314–321. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Segura, A., Vidal, C., Menéndez, V., Zapata, A., Prieto, M.: Exploring Characterizations of Learning Object Repositories Using Data Mining Techniques. In: MTSR 2009: Proceedings Metadata and Semantic Research Third International Conference, pp. 215–225. Springer, Heidelberg (2009)Google Scholar
  16. 16.
    Vidal, C., Prieto, M.: Una Ontología de apoyo a actividades de Diseño Instruccional. In: Prieto, M., Sanchez-Alonso, S., et al. (ed.) Recursos Digitales para el Aprendizaje, Editorial Universidad Autónoma de Yucatán (2009) ISBN 9876077573173Google Scholar
  17. 17.
    Protegé. Ontology Tool (2010), http://protege.stanford.edu/
  18. 18.
    O’Connor, M., Knublauch, H., Samson, T., Grosof, B., Dean, M., Grosso, W., Musen, M.: Supporting Rule System Interoperability on the Semantic Web with SWRL. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 974–986. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  19. 19.
    Felder, R., Silverman, L.: Learning and Teaching Styles in Engineering Education. Engineering Education 78(7), 674–681 (1988)Google Scholar
  20. 20.
    Duval, E., Forte, E., Cardinaels, K., Verhoeven, B., Van Durm, R., Hendrikx, K., Wentland Forte, M., Ebel, N., Macowicz, M., Warkentyne, K., Haenni, F.: The Ariadne knowledge pool system. Communications of the ACM 44(4), 72–78 (2001)CrossRefGoogle Scholar
  21. 21.
    Stefaner, M., Vecchia, E.D., Condotta, M., Wolpers, M., Spech, M.T., Apelt, S., Duval, E.: MACE - Enriching architectural learning objects for experience multiplication. In: Duval, E., Klamma, R., Wolpers, M. (eds.) EC-TEL 2007. LNCS, vol. 4753, pp. 322–336. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Christian Vidal C.
    • 1
  • Alejandra Segura Navarrete
    • 1
  • Víctor Menéndez D.
    • 2
  • Alfredo Zapata Gonzalez
    • 2
  • Manuel Prieto M.
    • 3
  1. 1.Universidad del Bio-BioConcepciónChile
  2. 2.Univ. Autónoma de YucatánMérida, YucMexico
  3. 3.Univ. de Castilla-La ManchaCiudad RealSpain

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