A Hybrid Recommender System to Support Personalization in E Learning System
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Abstract
Believing the fact that modern means of learning systems can act as catalyst to elevate the quality of education. Hence, the e-learning system guarantee not only the delivery of learning objects but also maintains a high standard with the desired learning output. Since e-learning system is focusing on an approach which is learner centric still the major problem with the current elearning system is the approach of one-size-fits-all that does not allow catering the individual learner interests and requirements. As a result, personalization of content, courses and other educational objects has become an essential issue in e-learning system as the basic users of the system are the learners with an almost different style of learning, background, capabilities, interests and the personality.
newlineMost of the times learners would come across a condition where it is difficult to choose the courses to learn and to decide more appropriate ones for
newlineself interest. The set-up of having numerous choices in course selection is
newlineperhaps a good thing but for a student it is hard and time consuming to stride
newlinethrough each of the courses and it s associated the information. The knowledge in the domain of computer science is huge and also disseminated that makes it
newlinedifficult for humans to expertise it, and as far as stability and quality is concerned,the pedagogical context of the domain is not clear. Even if institutes will employ counsellors, but the majority of the learners will not be pleased by the echelon of knowledge the possessed by the counsellors. In such conditions, Recommendation System (RS) is the only way out that can help a learner to choose suitable courses by recognising the learner s domain of interest and then
newlineby searching the appropriate courses to make them available for a learner. Based
newlineon the concept of personalization and to support the activities that are learnercentric
newlinea hybrid recommender system is proposed to maximize the learning experience of a learner because the course selection will have a direct