An Approach to Predict a Student’s Academic Performance using Recurrent Neural Network (RNN)

Abstract

Educational Data Mining able to gain a handsome amount of attention of the researcher of educational technology in recent times. In this paper, Recurrent Neural Network (RNN) is used to predict a student's final result. RNN is a variant of neural network that can handle time series data. The final term class is predicted using the first and second term class along with fifteen others features of a student. This analysis help the teacher to identify the students, who are 'at risk' and based on that he can offer proper remedy to them. In this paper, a comparison based study is also made with Artificial Neural Network and Deep Neural Network with the proposed Recurrent Neural Network.