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On Small Data Sets Revealing Big Differences

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Advances in Artificial Intelligence (SETN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3955))

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Abstract

We use decision trees and genetic algorithms to analyze the academic performance of students throughout an academic year at a distance learning university. Based on the accuracy of the generated rules, and on cross-examinations of various groups of the same student population, we surprisingly observe that students’ performance is clustered around tutors.

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References

  1. Kotsiantis, S., Pierrakeas, C., Pintelas, P.: Predicting students’ performance in distance learning using Machine Learning techniques. Applied Artificial Intelligence 18(5), 411–426 (2004)

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  2. Witten, I., Frank, E.: Data mining: practical machine learning tools and techniques with Java implementations. Morgan Kaufmann, San Mateo, CA (2000)

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  3. Kalles, D., Pierrakeas, C.: Analyzing student performance in distance learning with genetic algorithms and decision trees. Applied Artificial Intelligence (accepted for publication, 2006)

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  4. Papagelis, A., Kalles, D.: Breeding decision trees using evolutionary techniques. In: Proceedings of the International Conference on Machine Learning, Williamstown, Massachusetts (2001)

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Author information

Authors and Affiliations

  1. Hellenic Open University, Patras, Greece

    Thanasis Hadzilacos, Dimitris Kalles, Christos Pierrakeas & Michalis Xenos

  2. Computer Technology Institute, Patras, Greece

    Thanasis Hadzilacos

Authors
  1. Thanasis Hadzilacos
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  2. Dimitris Kalles
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  3. Christos Pierrakeas
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  4. Michalis Xenos
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Editor information

Editors and Affiliations

  1. Computer Science Department of University of Crete, Greece

    Grigoris Antoniou

  2. Institute of Computer Science, Foundation for Research & Technology – Hellas (FORTH), Vassilika Vouton, P.O. Box 1385, 71110, Heraklion, Greece

    George Potamias

  3. Institute of Informatics and Telecommunications, NCSR "Demokritos", 15310 A., Paraskevi Attikis, Greece

    Costas Spyropoulos

  4. Institute of Computer Science, FO.R.T.H., Vassilika Vouton, P.O. Box 1385, GR 71110, Heraklion, Greece

    Dimitris Plexousakis

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© 2006 Springer-Verlag Berlin Heidelberg

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Hadzilacos, T., Kalles, D., Pierrakeas, C., Xenos, M. (2006). On Small Data Sets Revealing Big Differences. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_57

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  • DOI: https://doi.org/10.1007/11752912_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34117-8

  • Online ISBN: 978-3-540-34118-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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