Course Recommendations In Moocs : Techniques And Evaluation

In the recent years, there has been a massive growth in the amount of online technical information available to the users on internet, in the form of open-access publications, tutorials, and a variety of other open source material. The usage of Massive Open Online Courses (MOOCs) like Coursera, Udacity, etc. is increasing rapidly. These MOOCs offer a huge variety of courses containing a lot of information. This overload of information means that, MOOC users spend a lot of time surfing through the internet to find the course that suits them best. Recommendation technology, thus, plays an important role in assisting the users to find their favorite content from the bulk of content available. This paper is a comparative study of the different techniques used to build recommendation systems. The paper discusses various approaches for recommendation of courses to new and existing users on MOOC platforms. Different evaluation techniques are also discussed.