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  • 标题:Teaching and Learning Activity Sequencing System using Distributed Genetic Algorithms
  • 本地全文:下载
  • 作者:Tatsunori MATSUI ; Tomotake ISHIKAWA ; Toshio OKAMOTO
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2002
  • 卷号:17
  • 期号:4
  • 页码:449-461
  • DOI:10.1527/tjsai.17.449
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:The purpose of this study is development of a supporting system for teacher's design of lesson plan. Especially design of lesson plan which relates to the new subject "Information Study" is supported. In this study, we developed a system which generates teaching and learning activity sequences by interlinking lesson's activities corresponding to the various conditions according to the user's input. Because user's input is multiple information, there will be caused contradiction which the system should solve. This multiobjective optimization problem is resolved by Distributed Genetic Algorithms, in which some fitness functions are defined with reference models on lesson, thinking and teaching style. From results of various experiments, effectivity and validity of the proposed methods and reference models were verified; on the other hand, some future works on reference models and evaluation functions were also pointed out.
  • 关键词:Distributed Genetic Algorithm ; Teaching and Learning Process/Activity ; Learning Strategy ; Contents Sequencing ; Learning Reference Model
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