A model for personalized selection of a learning scenario depending on learning styles

Abstract

This paper deals with one of Technology Enhanced Learning (TEL) problems - the personalized selection of a learning scenario. Personalization is treated here as appropriateness of a learning scenario to preferences of a particular student, mainly, his/her learning style. This paper proposes an extended approach to modeling learning scenario selection based on preferences of a student's learning style. An ant colony optimization algorithm is modified and applied. In order to give a theoretical background the main conceptions of personalization, learning scenario and learning style are briefly presented. The aim of this paper is twofold. First, data mining technique to obtain a student's learning style is presented; second, a model for personalized selection of a learning scenario is proposed.