Conceptual clustering: a new approach to student modeling in Intelligent Tutoring Systems

  • Yunia Reyes-González University of Information Science
  • Natalia Martínez-Sánchez University of Information Science
  • Adolfo Díaz-Sardiñas University of Information Science
  • Marisol de la Caridad Patterson-Peña University of Information Science
Keywords: Student modeling, Intelligent tutoring systems, Logical combinatorial pattern recognition, Artificial intelligence


Student modeling is a central problem in Intelligent Tutoring Systems design and development. In this way, the characteristic that distinguishes this type of system is the ability to determine as accurately and quickly as possible the student’s cognitive and affective-motivational state in order to personalize the educational process. Therefore, the fundamental problem is to select data structure to represent all relative information to student and to choose the procedure to make the diagnosis. This paper describes a model for knowledge engineering inherent to all intelligent tutoring system, using the LC-Conceptual clustering algorithm, from logical combinatorial pattern recognition. This algorithm builds the objects clusters based on their similarity, using a grouping criterion, and it also builds the property (or concept) that meets each group of objects.

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Author Biographies

Yunia Reyes-González, University of Information Science

MSc. and Assistant Professor of the Programming Department, Vice Dean of Research and Postgraduate Studies.

Natalia Martínez-Sánchez, University of Information Science

PhD. In Technical Sciences and Professor. Programming Department.

Adolfo Díaz-Sardiñas, University of Information Science

PhD. in Pedagogical Sciences and Professor, Programming Department.

Marisol de la Caridad Patterson-Peña, University of Information Science

Master in English Language Studies and Assistant Professor at the Language Center.



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How to Cite
Reyes-González Y., Martínez-Sánchez N., Díaz-Sardiñas A., & Patterson-Peña M. de la C. (2018). Conceptual clustering: a new approach to student modeling in Intelligent Tutoring Systems. Revista Facultad De Ingeniería Universidad De Antioquia, (87), 70-76.