Survey on Predicting Educational Trends by Analyzing the Academic Performance of the Students

Abstract

Driving decisions using data is being followed in most of the business units. Industries and Institutions use complex computational techniques to improve and identify their growth trend by using Business Intelligence techniques. Adoption of data mining in educational system(s) is fairly new, data mining techniques can detect patterns from the educational system data which might be continuous or discrete and drive a prediction rule to identify the academic performance of students. Our study is focused on exploring various factors affecting educational performance of undergraduate students based on the data from their course activities. The survey explores various data mining techniques applied on educational data and advocates to integrate the learning management system with the data pattern models identified.