A neural network approach for students' performance prediction
- 13 March 2017
- proceedings article
- Published by Association for Computing Machinery (ACM)
- p. 598-599
- https://doi.org/10.1145/3027385.3029479
Abstract
In this paper, we propose a method for predicting final grades of students by a Recurrent Neural Network (RNN) from the log data stored in the educational systems. We applied this method to the log data from 108 students and examined the accuracy of prediction. From the experimental results, comparing with multiple regression analysis, it is confirmed that an RNN is effective to early prediction of final grades.Keywords
Funding Information
- National Institute of Information and Communications Technology (NICT), Japan (16H06304)
This publication has 1 reference indexed in Scilit:
- Identifying significant indicators using LMS data to predict course achievement in online learningThe Internet and Higher Education, 2016