Personalized recommendation systems in e-learning

With the expansion of web applications and numerouse developments in communications and knowledge distribution, e-learning – as one of the major applications in this context, has undergone leadning changes and improvements. Nowadays, content development , its shape and format are in less importance of elearning system development issues, but the way of presentation of this content in a manner of personalized and proportional to the learner's learning requirements is one of the most importance problems in e-learning. In the dominant paradigms of education, it is believed that different learners' learning happens through different methods, and every one has his individual information requirements in learning. Considering these differences in the process of learning and training can influence the effectiveness and development of e-learning. Personalized e-learning is a novel approach in e-learning. Applying personalized recommendation techniques in elearning system development can help selection of personalized elearning contents and objects to better meet the requirements of each single learner according to his specific learning needs. In this paper we review rescent advances in personalized elarning content recommendation system development and give suggestions for detectiong learning style of each learner based on the knowledge extraction through the learners' information and introduce an approach to learning style recognistion

Keywords:

personalization , e-learning , personalized recommendation systems , modeling , learning style