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An Auto-Recommender Based Intelligent E-Learning System


Abdallah Gomah, Samir Abdel Rahman, Amr Badr, Ibrahim Farag


Vol. 11  No. 1  pp. 67-70


Internet has been universally recognized as a medium for network-enabled transfer of information and knowledge in various areas. Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning. Nevertheless, learning systems do not generally adapt to learners profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge background. In this paper, we propose architecture for intelligent E-Learning system architecture which helps learners taking advantage of the web massive contents through the use of an automated assistant (a recommender system). The proposed recommender system is based on a novel feature reduction technique with the goal of being able to adapt according to the learners interest in the general domain without being specific to a single domain.


Auto Recommender, E-Learning, Artificial Intelligence and Tutoring Systems