MOOCs Recommender System: A Recommender System for the Massive Open Online Courses

Abstract

Nowadays, technology is affecting every aspect of our society in different manner. However, the technology impact is more tangible in the field of education. Technological advances are transforming the way education is being delivered. Courses are not limited for those who are attending university or school classes. The proliferation of Web Technologies and the exploration of the possibilities of Technology Enhance Learning (TEL) led to the development of many learning solutions and recently to Massive Open Online Courses (MOOCs). MOOCs are capable of providing several ten thousands of learners with access to courses over the web. Recently, there are many MOOCs providers/platforms with different features and characteristics. Online learners are exposed to various challenges with this excess of those MOOCs providers. This paper presents a system that is built in the top of MOOCs providers to act as a single point of access to those providers. This system is twofold: first, it will improve the learning process for any online learner in a way that satisfies the learner needs when searching for suitable courses among different providers; It will help users not to be lost in the overwhelming offers of MOOCs. Second, it will recommend courses related to the previous experiences of its users.