International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 181 - Number 6 |
Year of Publication: 2018 |
Authors: Arindam Mondal, Joydeep Mukherjee |
10.5120/ijca2018917352 |
Arindam Mondal, Joydeep Mukherjee . An Approach to Predict a Student’s Academic Performance using Recurrent Neural Network (RNN). International Journal of Computer Applications. 181, 6 ( Jul 2018), 1-5. DOI=10.5120/ijca2018917352
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.