Increasing the Profitability of Students in MOOCs using Recommendation Systems

Abstract

Massive open online courses MOOCs have earned much attention since the beginning in 2011 and students who signed up for at least one course has crossed 35 million in 2015. Yet, there has been a lack of research conducted to study the design of learning materials and tasks of MOOCs. Moreover, there are limited researches that focus on implementing recommendation systems in MOOCs to predict what students want more aiming to increase their profitability. In this paper, the authors present the algorithm they are creating. The main purpose of this algorithm is to create automatic mechanisms as the recommendation system to give such assistance and personalized guidance to students.