Genetic Algorithm and the Problem of Getting Knowledge in e-Learning Systems

  • Authors:
  • Anna Hovakimyan;Siranush Sargsyan;Sergey Barkhoudaryan

  • Affiliations:
  • Yerevan State University;Yerevan State University;National Academy of Sciences of RA

  • Venue:
  • ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
  • Year:
  • 2004

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Abstract

In e-learning systems actual problem is getting knowledge of demanded level in possibly short period of time. Besides that the used teaching resources (electronic books, different learning materials) can have different quality and quantity characteristics, such as keywords and key terms, resource complexity, weight of basic terms e. t .c. In the given article an approach for the problem of building such component of e-learning system that give to the user a chance to get the desired set of keywords of teaching course in possibly short period of time is discussed. This approach is based on so-called "teaching scenarios" being constructed by Genetic Algorithm. Via the quality and quantity characteristics of the teaching resources Genetic Algorithm creates the appropriate sequence of the teaching resources from the set of all possible. The considered method is realized and introduced in the TeachArm system developed at the Department of Algorithmic Languages of YSU.