Paper Title
Iterative Recommendation System For Learning Material In E-Learning Environment

Web-based learning environments have increased the need for researchers to find alternative ways to access learning materials. In web-based learning the resources are constantly available to all the users, who have different personalized profiles. This paper proposes a dynamic hybrid system to access learning materials or notes in E-learning environment based on the user’s profile. Thus the tutors and students can share, view, study, rate and update material depending on their interests and field of study through this system. The main module is a hybrid algorithm. Hybrid algorithms proposed so far focus on filtering the required data based on specified constraints. They don’t tell whether the recommended data is useful for the user or whether the e-learner learned anything from the recommended learning material or not. Hence this paper focuses on identifying the appropriate learning material and recommends the learning content iteratively based on ranking priority of the learning material and also improving the learning skills of the user.