The Genetic Algorithms (GA) in Web-based Learning Systems

S. Sargsyan, A. Hovakimyan, and S. Barkhudaryan (Armenia)

Keywords

Genetic Algorithm, Fitnessfunction, knowledge adaptable scenarios, teaching resources, learning sequences, effective teaching

Abstract

In Web-based learning systems the problems of an optimum teaching process management are important (particularly, getting knowledge of demanded level in possibly short period of time). Learning scenarios that are adequate to the user's knowledge can manage the teaching process in the current teaching phase. In this article an approach for constructing one kind of online learning systems is considered. One function of that system is the organization of teaching and testing on some course. Teaching scenario is based on characteristics of teaching material and is adapted on user's knowledge by the given course ("user-adaptable course"). Genetic Algorithm is used to search those scenarios from the set of all possible. Another function of learning system is to give to user a chance to get the desired knowledge by teaching subject from different resources in possibly short period of time. Via the quality and quantity characteristics of the teaching resources, Genetic Algorithm creates the appropriate sequence of the teaching resources. These resources may be used to get preliminary knowledge for "user-adaptable course". The construction of adaptive online teaching system is realized while developing the TeachArm system at the Department of Algorithmic Languages of YSU.

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