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Automatic Leveling System for E-Learning Examination Pool Using Entropy-Based Decision Tree

  • Shu-Chen Cheng
  • Yueh-Min Huang
  • Juei-Nan Chen
  • Yen-Ting Lin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3583)

Abstract

In this paper, we propose an automatic leveling system for e-learning examination pool using the algorithm of the decision tree. The automatic leveling system is built to automatically level each question in the examination pool according its difficulty. Thus, an e-learning system can choose questions that are suitable for each learner according to individual background. Not all attributes are relevant to the classification, in other words, the decision tree tells the importance of each attribute.

Keywords

Decision Tree Information Gain Assessment Item Decision Tree Induction Peer Assessment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Shu-Chen Cheng
    • 1
  • Yueh-Min Huang
    • 2
  • Juei-Nan Chen
    • 2
  • Yen-Ting Lin
    • 1
  1. 1.Department of Computer Science and Information EngineeringSouthern Taiwan University of TechnologyTainanTaiwan
  2. 2.Department of Engineering ScienceNational Cheng Kung UniversityTainanTaiwan

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