doi: 10.18178/ijiet.2017.7.11.977
Adoption of Feature Selection and Classification Techniques in a Decision Support System
Benilda Eleonor V. Comendador
,
Ariel M. Sison ,
Ruji P. Medina
Abstract
This paper presents a decision support system prototype called eCourse Learning Analytics Decision Support System (eCLADSS) using J48 tree classifier and multiple linear regression models. The system identifies students who are falling behind in a course, notifies those at risk of not completing it, then informs the users the predicted grade a student is likely to obtain without intervention. The developed eCLADSS predicts the performance of the Learning Management System (LMS) users which may help the Distance Education (DE) students succeed in the blended learning approach being provided by the DE educators. It is a model-driven decision support system which provides a good platform for prediction model generation.
Keywords
- Learning analytics
- decision support system
- classification techniques
How to Cite
Benilda Eleonor V. Comendador, Ariel M. Sison, and Ruji P. Medina, "Adoption of Feature Selection and Classification Techniques in a Decision Support System," International Journal of Information and Education Technology, vol. 7, no. 11, pp. 809-813, 2017. https://doi.org/10.18178/ijiet.2017.7.11.977
Copyright & License
Copyright © 2017 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).