On the Architecture of Intelligent Tutoring Systems and Its Application to a Neural Networks Course

  • J. F. Vega-Riveros
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 36)


This chapter presents the architecture of an Intelligent Tutoring System for a Neural Networks course that consists of four basic modules. The subject knowledge-base stores an object-oriented representation of the theme knowledge. The student modeling module traces the user interaction with the system and assess goal accomplishment and motivation-towards-achievement. The instructional strategy module in this implementation consists of a knowledge navigation tool based on a concept-space metaphor and an automatic multiple choice question generator. The user interface, based on the concept-space metaphor, provides the means for the student to access hypermedia information that includes theory and examples, the question generator and the neural networks simulators. The description of the architecture is followed by a presentation and analysis of a learning model based on which a new Intelligent Tutoring System architecture using collaborating agents is proposed.


Intelligent Tutoring System Student Modeling Instructional Model Membership Relation Neural Network Simulator 
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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  1. [1]
    Martin, J.J. and Odell, J. (1992), Principles of Object-Oriented Analysis and Design,Prentice Hall.Google Scholar
  2. [2]
    Ikeda, M. (1993), “Non-monotonic inference: a formalization of student modeling,” Proc. Of the 13th Intl. Joint Conference on Artificial Intelligence, Vol. 1, pp. 467–473.Google Scholar
  3. [3]
    Fernandez-Ossa, M. del P. (1997), Modelamiento de Estudiantes para aplicación en un Sistema Tutorial Inteligente, Undergraduate final project. Javeriana University, Santafé de Bogota, DC, Colombia.Google Scholar
  4. [4]
    Verdejo, M.F. (1994), “Building a student model for an intelligent tutoring system. Student modeling: the key to individualized knowledge-based instruction,” Proc. of the NATO Advance Research Workshop, pp. 127–146.Google Scholar
  5. [5]
    Ausubel, D., Novak, J.D. and Hanesian, H. (1989), Psicologia Educativa, Ed. Trillas, Mexico.Google Scholar
  6. [6]
    Novak, J.D. and Gowing, D.B. (1988), Aprendiendo a Aprender. Ed. Martínez-Roca, Barcelona, Spain.Google Scholar
  7. [7]
    Vega-Riveros, J.F., Marciales-Vivas, G.P. and Martínez-Melo, M. (1998), “Concept maps in engineering education: a case study,” UICEE Global J. on Engineering Education, Vol. 2, No. 1, pp. 2127.Google Scholar
  8. [8]
    Kolb, D.A. (1984), Experimental Learning: Experience on the Source of Learning and Development, Prentice Hall, Englewood Cliffs, NJ.Google Scholar
  9. [9]
    Acero-Barrera, L.E. and Sanchez-Angel, H. (1997), Investigación de Modelo de Conocimiento para la Generación de Preguntas, Undergraduate final project, Javeriana University, Santafé de Bogota, DC, Colombia.Google Scholar
  10. [10]
    Vega-Riveros, J.F., Borda-Medina, R.A. and Marciales-Vivas, G.P. (1995), Sistema Experto para Instrucción Asistida por Computador en un Area de la Obstetricia, Final technical report to Colciencias, Javeriana University, Santafé de Bogota, DC, Colombia.Google Scholar
  11. [11]
    Wertsch, J.W. (1988), Vigotski y la Formación Social de la Mente, Ed. Paidos, Barcelona, Spain.Google Scholar
  12. [12]
    Gimeno, J. (1996), Comprender y Transformar la Ensenanza, Ed. Morata, Madrid, Spain.Google Scholar
  13. [13]
    Bandura, A. (1987), Pensamiento y Acción: Fundamentos Sociales, Ed. Martínez-Roca, Barcelona, Spain.Google Scholar
  14. [14]
    Bruner, J. (1978), Acción, Pensamiento y Lenguaje, Ed. Alianza, Madrid, Spain.Google Scholar
  15. [15]
    Acosta-Vàsquez, C.P. (1998), Sistema Tutor en Lecto-Escritura, Undergraduate Final Project, Javeriana University, Santafé de Bogota, DC, Colombia.Google Scholar
  16. [16]
    Condemarin, M., Chadwick, M. and Milicic, N. (1981), Madurez Escolar, Ed. Andrés Bello, U.K.Google Scholar
  17. [17]
    Minar, N.M., Kramer, K.H. and Maes, P. (1998), “Cooperating Mobile Agents for Mapping Networks,” Proc. of the 1 t Hungarian National Conference on Agent Based Computing, John von Neumann Computer Society, Budapest, Hungary.Google Scholar
  18. [18]
    Daily, M., Payton, D., Clifton, T., Weghorst, S. and Loftin, B. (1997), Human Computer Symbiotes; Cyberspace Entities for Active and Indirect Collaboration,Hughes Research Laboratories, Project summary, E359_0.html.
  19. [19]
    Albornoz-Reina, R. and Casas, L.A. (1998), Ambiente Hipermedial Unificado para Aulas Virtuales, Undergraduate final project, Javeriana University, Santafé de Bogota, DC, Colombia.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • J. F. Vega-Riveros
    • 1
  1. 1.Department of Electronic EngineeringJaveriana UniversitySantafé de BogotáColombia

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