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A Study on E-Learning and Recommendation System
- Source: Recent Advances in Computer Science and Communications, Volume 15, Issue 5, Jun 2022, p. 748 - 764
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- 01 Jun 2022
Abstract
Introduction: Today, technology and internet both are proliferating due to which information access is becoming easier, and is creating new challenges and opportunities in all fields, especially when working in the field of education. For example, the e-learning education system can be 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 plays a significant role. For many researchers, it has become one of the most important subjects, as through the use of elearning, the whole education system would revolutionize. There are many areas of e-learning in which research work is being carried out, such as Mass Communication, Information and Technology (IT), Education and Distance Education. Objectives: To meet the various needs of the learners such as talents, interests and goals an elearning system needs to be designed as a personalized learning system by considering various educational experiences. Many methods such as ontologies, clustering, classification and association rules have been used along with filtering techniques to enhance the personalization and performance of the learner. Methods: This paper presents a detailed review of the literature of previous work that has been conducted in e-learning area, especially in the recommendation system. Current research works on e-learning has been discussed in this work in order to discover the research developments in this discipline. Conclusions: 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 as e-learning plays a vital role in preventing virus spread during COVID-19 pandemic.