Teaching and learning activity sequencing system using distributed genetic algorithms

Tatsunori Matsui, Tomotake Ishikawa, Toshio Okamoto

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)449-461
Number of pages13
JournalTransactions of the Japanese Society for Artificial Intelligence
Volume17
Issue number4
DOIs
Publication statusPublished - 2002 Dec 1

Keywords

  • Contents Sequencing
  • Distributed Genetic Algorithm
  • Learning Reference Model
  • Learning Strategy
  • Teaching and Learning Process/Activity

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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