Predictive analytics for E learning system

E Learning courses are much in demand in recent times. The need to study student's performance and predicting their performance is increasing along with it. With the growing popularity of educational technology, various data mining algorithms suitable for predicting student performance have been reviewed. The best algorithm depends on the nature of prediction the faculty wants to make. As the amount of student data is increasing the need to address the complexities of data relation and their processing is a challenge to find the student at risk of failing. This paper covers the Decision Tree Approach for Predictive Analytics of student's performance and its Big Data Implication.