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• [P256] Personalized Curriculum Composition by Learner Profile Driven Data Mining
  Author(s): Rainer Knauf, Yoshitaka Sakurai, Setsuo Tsuruta, Kouhei Takada, Shinichi Dohi
  
  

  Abstract
  The paper is focused on modeling, processing, evaluating and refining processes with humans involved like (not only, but also e-) learning. A formerly developed concept called storyboarding has been applied at Tokyo Denki University (TDU) to model the various ways to study at this university. Along with this storyboard, we developed a Data Mining Technology to estimate success chances of curricula. Here, we introduce a learner profiling concept that represents the students' individual properties, talents and preferences personalized data mining.

  
   

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