Knowledge-Based Systems: A Tool for Distance Education

  • Pedro Salcedo L.
  • M. Angélica Pinninghoff J.
  • Ricardo Contreras A.
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5601)

Abstract

This work describes how, starting from the PhD thesis A Knowledge-Based System for Distance Education, under the supervision of Professor José Mira Mira, different ideas have evolved opening new research directions. This thesis has emphasized the usefulness of artificial intelligence (AI) techniques in developing systems to support distance education. In particular, the work concerning the modelling of tasks and methods at knowledge level, and in the use of hybrid procedures (symbolic and connectionist) to solve those tasks that recurrently appear when designing systems to support teaching-learning processes.

Keywords

Prediction Academic Performance Neural Networks 

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References

  1. 1.
    Alonso, A., Guijarro, B.: Ingeniería del Conocimiento. Aspectos Metodológicos. Pearson Prentice Hall, London (2004)Google Scholar
  2. 2.
    Kolb, D.: The Learning Style Inventory. Technical Manual. McBer, Boston (1976)Google Scholar
  3. 3.
    Kolb, D.: Learning Style and Disciplinary Differences. In: Chickering, A.W. (ed.) The Modern American College. Jossey-Bass, San Francisco (1981)Google Scholar
  4. 4.
    Pinninghoff, M.A., Salcedo, P., Contreras, R.: Neural Networks to Predict Schooling Failure/Success. LNCS. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  5. 5.
    Salcedo, P., Pinninghoff, M.A., Contreras, R.: MISTRAL: A Knowledge-Based System for Distance Education that Incorporates Neural Networks for Teaching Decisions. In: Mira, J., Álvarez, J.R. (eds.) IWANN 2003. LNCS, vol. 2687, pp. 726–733. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  6. 6.
    Salcedo, P., Pinninghoff, M.A., Contreras, R.: Computerized Adaptive Tests and Item Response Theory on a Distance Education Platform. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3562, pp. 613–621. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    Schreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N., Van de Velde, W., Wielinga, B.: Knowledge Engineering and Management: The CommonKADS Methodology. MIT Press, Cambridge (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Pedro Salcedo L.
    • 1
  • M. Angélica Pinninghoff J.
    • 2
  • Ricardo Contreras A.
    • 2
  1. 1.Faculty of EducationChile
  2. 2.Faculty of EngineeringUniversity of ConcepciónChile

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