An Intelligent System for Modeling and Supporting Academic Educational Processes

  • Setsuo Tsuruta
  • Rainer Knauf
  • Shinichi Dohi
  • Takashi Kawabe
  • Yoshitaka Sakurai

Abstract

University has a complicated system of course offerings, registration rules, and prerequisite courses, which should be matched to students’ dynamic learning needs, and desires. We address this problem by developing an Educational-Learning System called “Dynamic Storyboarding System”. Besides modeling learning processes, this system aims at evaluating and refining university curricula to reach an optimum of learning success in terms of best possible ac-cumulative grade point average (GPA). This is performed by applying Educational Data Mining (EDM) to former students curricula and their degree of success (GPA) and thus, uncovering golden didactic knowledge for successful education. It consists of mining a decision tree (DT) and applying it to curricula planned by current students. Students receive an estimation of the GPA they are likely to receive along with a recommendation to supplement a partial path to reach optimal success. Our approach includes individual learner profiles. The profiling concept initially uses the per-university educational history and is dynamically extended by the students’ university study results. The profiles are used by applying the EDM technology to students with profiles of a high similarity to the student under consideration. A feasibility study showed the usefulness of the system. The effect has been validated by cross-validation with about 200 students’ records. The mean of the difference between the original grade point average (GPA) and the estimated one was 0.43 with a standard deviation of 0.30.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Amasyali, M.F., Ersoy, O.: Cline: New multivariate decision tree construction heuristics. In: Proceedings of CIMA (2005)Google Scholar
  2. Boeck, R.: Ein data mining verfahren zur pfadbewertung in storyboards. (German) Diploma thesis, Ilmenau University of Technology (2007)Google Scholar
  3. Cha, S., Tappert, C.: A genetic algorithm for constructing compact binary decision trees. Journal of Pattern Recognition Research 1, 1–13 (2009)Google Scholar
  4. Dohi, S., Nakamura, S.: The development of the dynamic syllabus for school of information environment. In: Proceedings of ITHET, pp. 505–510 (2003)Google Scholar
  5. Felder, R.M., Silverman, L.K.: Learning and teaching styles in engineering education. Engineering Education 78(7), 674–681 (1988)Google Scholar
  6. Gardner, H.: Frames of Mind: The Theory of Multiple Intelligences. Basic Books (1993)Google Scholar
  7. Knauf, R., Sakurai, Y., Takada, T., Dohi, S.: Personalized Curriculum Composition by Learner Profile Driven Data Mining. In: Proc. of the 2009 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2009), San Antonio, TX, USA, pp. 2137–2142 (2009) ISBN 978-1-4244- 2794-9Google Scholar
  8. Knauf, R., Sakurai, Y., Tsuruta, S., Jantke, K.P.: Modeling Didactic Knowledge by Storyboarding. Journal of Educational Computing Research 42(4), 355–383 (2010)CrossRefGoogle Scholar
  9. Lacave, C., Luque, M., Díez, F.J.: Explanation of Bayesian networks and influence dia-grams in Elvira. IEEE Transactions on Systems, Man and Cybernetics, part B: Cybernetics 37, 952–965 (2007)CrossRefGoogle Scholar
  10. Rexer, K., Allen, H., Gearan, P.: Data miner survey. In: Proceedings of PAW (2010)Google Scholar
  11. Puterman, M.L.: Markov decision processes: Discrete stochastic dynamic programming. Wiley, New York (1995)Google Scholar
  12. Sakurai, Y., Dohi, S., Tsuruta, S., Knauf, R.: Modeling academic education processes by dynamic storyboarding. Journal of Educational Technology & Society 12, 307–333 (2009)Google Scholar
  13. Weihong, W., Wei, R., Qu, L.: Fuzzy decision tree construction with gene expression programming. In: Proceedings of ISKE, pp. 244–248 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Setsuo Tsuruta
    • 1
  • Rainer Knauf
    • 2
  • Shinichi Dohi
    • 1
  • Takashi Kawabe
    • 1
  • Yoshitaka Sakurai
    • 1
  1. 1.School of Information EnvironmentTokyo Denki UniversityInzaiJapan
  2. 2.Faculty of Computer Science and AutomationUniversity of IlmenauIlmenauGermany

Personalised recommendations