A Study on E-Learning and Recommendation System

Abstract

Introduction: Today’s technology and the internet are proliferating due to which information access is becoming easier for many people, and creating new challenges and opportunities in all fields, especially when working with education. For example, the e-learning education system can personalized in order to acquire knowledge level and learner’s requirements in a learning process. The learning experience, as per the individual learner’s goals, should be adopted. Background: In the current educational environment, e-learning is playing a significant role. For many researchers, it has become one of the most important subjects, as using e-learning whole education system would revolutionize. There are many areas of e-learning in which research work is going on, such as Mass Communication, Information and Technology (IT), Education and Distance Education. Objective: To meet the various needs of the learners such as talents, interests, goals and needs, an e-learning system has to design a personalized learning system by considering various educational experiences. Many methods such as ontologies, clustering, classification and association rules have used along with filtering techniques to enhance the personalization and performance of the learner. Methods: This paper presents a detailed review of literature of previous work that has done in e-learning area especially on recommendation system. Current research works on e-learning to discover the research developments in this discipline have discussed in this work. Conclusion: One of the vital functions of the current e-learning system is creating a personalized resource recommendation system. In this paper, we reviewed some crucial papers on both e-learning and recommendation systems. Future research work of this paper would be designing efficient and precise e-learning and recommendation system to deal with the problem of substantial personalized information resources and further e-Learning plays vital role in preventing virus spread during COVID-19 pandemic.