Modeling of the students scenario on a learning course

Yuji Shinoda*, Kenji Yoshida, Hirotaka Nakayama

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Adjusting the content to each student is a major issue in e-Learning. From this viewpoint, a learning course as a series of content also must be adjusted according to the performance of the students. We propose a method that combines clustering and decision tree learning for constructing scenarios of the students' actions. The global statuses of the students are reflected to the clusters, and the local and sequential actions of the students are reflected to the decision trees. The results of e-Learning tests gathered from Japanese junior high school students was processed by our proposed method. We graded the clusters by adaptation to the trees, and selected a set of clusters as a scenario for the students. These scenarios have a possibility of aiding the adjustment, and revision of learning courses.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
PublisherSpringer Verlag
Pages573-579
Number of pages7
EditionPART 1
ISBN (Print)3540855629, 9783540855620
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb, Croatia
Duration: 2008 Sept 32008 Sept 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5177 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
Country/TerritoryCroatia
CityZagreb
Period08/9/308/9/5

Keywords

  • Clustering
  • Decision Tree
  • E-learning
  • K-means
  • User model

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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