Towards Recommending Courses in a Learner-Centered System based on Trend, Faculty and Student Course Preferences

Abstract

Recommendation systems have become essential today in different areas of life, they help learners to find content in large sets. Also, the recommendation engines can display the elements that users may not have thought of searching on their own and users get never-expected results. People today use search engines to look for products, tomorrow they will just explore the proposals submitted. This system aims to enhance student`s skills and provide them with training courses to raise their opportunities for good careers. Students assessments are traditional methods to predict student`s performance such as failing or passing or forecasting successful completion of the course, in this continuation, predicting the classification of degree or achievement. This paper discusses the course of their interests and proposes course selection assistance through a recommendation system that may help students make the right choices through experienced support.