Predicting Academic Performance of Students in UAE Using Data Mining Techniques
Authors:
- 1 June 2018
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 179-183
Abstract
In this paper, we implemented an approach to predict final exam scores from early course assessments of the students during the semester. We used a linear regression model to check which part of the evaluation of the course assessment affects final exam score the most. In addition, we explained the origins of data mining and data mining in education. After preprocessing and preparing data for the task in hand, we implemented the linear regression model. The results of our work show that quizzes are most accurate predictors of final exam scores compared to other kinds of assessments.Keywords
This publication has 4 references indexed in Scilit:
- Modeling and Predicting Students’ Academic Performance Using Data Mining TechniquesInternational Journal of Modern Education and Computer Science, 2016
- Analysis of Data Mining Techniques for Constructing a Predictive Model for Academic PerformanceIEEE Latin America Transactions, 2016
- A Review on Predicting Student's Performance Using Data Mining TechniquesProcedia Computer Science, 2015
- Data mining in course management systems: Moodle case study and tutorialComputers & Education, 2008