Recommendation of learning resources in social learning environment using data mining

with the growing number of learners in the social learning environments and social networks, and with the ever-growing volume of online content, learners are overwhelmed by the amount of available content. Recommender systems have been an effective strategy to deal with this challenge. In social learning environments, recommendation systems are used much more to locate the most suitable resources for learners, finding the right resources can help learners in their learning process. The proposed approach is based on the similarity calculation between a learner and his/her friends of the same frequent subnetwork by using Learner model. To approve this approach we developed a system that personalized to the requirements of learners.