Clustering Students to Help Evaluate Learning

  • Agathe Merceron
  • Kalina Yacef
Conference paper
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 171)


In this paper we show how clustering techniques can be applied to student answers generated from a web-based tutoring tool. In particular we are interested in extracting clusters of students based on the mistakes they made using the tool, with the aim of obtaining pedagogically relevant information and providing this feedback to the teacher. The data we used comes from the Logic-ITA, a web-based tutoring tool to practice formal proofs currently in use in the School of Information Technologies at the University of Sydney.


Tutoring systems Data Mining Clustering 


  1. [1]
    Abraham D., Crawford L., Lesta L., Merceron A. and Yacef K., The Logic Tutor: A Multimedia Presentation, Interactive Multimedia Electronic Journal of Computer-Enhanced learning, Vol. 3, Nb. 2, Nov. 2001.Google Scholar
  2. [2]
    Benchaffai M., Debord G., Merceron A., and Yacef K., TADA-Ed, a tool to visualize and mine students’ work. Submitted paper. 2004Google Scholar
  3. [3]
    Bisson G., Bronner A., Gordon M.T., Nicaud J.-E, Renaudie D., Analyse statistique de comportements d’eleves en algebre, Proceedings of Environnement Informatiques pour l’Apprentissage Humain, Strasbourg, France, pp.67–78, 2003Google Scholar
  4. [4]
    Han J., and Kamber M., Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, 2001Google Scholar
  5. [5]
    Lesta L. and Yacef K., An Intelligent Teaching-Assistant System for Logic, Proceedings of Intelligent Tutoring Systems, Biarritz, France, Springer-Verlag, June 2002.Google Scholar
  6. [6]
    Merceron A., and Yacef K., A web-based tutoring tool with mining facilities to Improve Teaching and Learning. Proceedings of the 11th International Conference on Artificial Intelligence in Education, IOS Press, Sydney, Australia, pp.201–208 2003Google Scholar
  7. [7]
    Romero, C, Ventura S., de Castro C, Hall W. and Ng M.H., Using Genetic Algorithms for Data Mining in Web-based Educational Hypermedia Systems. In Workshop on Adaptive Systems for Web-based Education, Malaga, Spain, 2002.Google Scholar
  8. [8]
    Tang T.Y., McCalla G., Student Modeling for a Web-based Learning Environment: a Data Mining Approach. Eighteenth national conference on Artificial intelligence, Edmonton, Alberta, Canada, pp.967–968, 2002Google Scholar
  9. [9] Scholar
  10. [10]
    Zaiane, O.R. Web Usage Mining for a Better Web-Based Learning Environment. Proceedings of Conference on Advanced Technology for Education (CATE’01). Banff, Alberta 2001.Google Scholar

Copyright information

© International Federation for Information Processing 2005

Authors and Affiliations

  • Agathe Merceron
    • 1
  • Kalina Yacef
    • 2
  1. 1.Computer Science Department, Engineering SchoolTechnical University Leonard de VinciParis-La DefenseFrance
  2. 2.School of Information TechnologiesUniversity of SydneySydneyAustralia

Personalised recommendations