Review of personalized recommendation techniques for learners in e-learning systems

With the rapidly increasing learning materials and learning resources, either offline or online, it is quite difficult to find suitable materials based on learner´s need. Recommender systems help learners find the appropriate learning materials in which they would need to learn. This paper discusses about the personalized recommendation systems in e-learning and compares their recommendation techniques. Two concepts are the main discussion topics in this research. The first one is about the learner´s requirement and the second one in about the personalized recommendation technique. Finally, this study proposes the knowledge based recommendation system as suitable recommendation technique. This recommendation aims to recommend to the learner, some materials based on the learner´s need. By using the semantic relationship between learning materials and the learner´s need, system can select the suitable materials as a recommendation to the learner. To develop the proposed knowledge based recommendation system is the next work for the future.