The ensemble approach such as boosting is based on heuristic system to develop
prediction paradigms. The ensemble learning techniques are typically more accurate than …

Educational data mining has received considerable attention in the last few years. Many
data mining techniques are proposed to extract the hidden knowledge from educational …

A plethora of research has been done in the past focusing on predicting student's
performance in order to support their development. Many institutions are focused on …

Automatic Student performance prediction is a crucial job due to the large volume of data in
educational databases. This job is being addressed by educational data mining (EDM) …

In the past few years, educational data mining (EDM) has attracted the attention of
researchers to enhance the quality of education. Predicting student academic performance …

Student performance prediction is extremely important in today's educational system.
Predicting student achievement in advance can assist students and teachers in keeping …

Purpose The purpose of this paper is to empirically investigate and compare the use of
multiple data sources, different classifiers and ensembles of classifiers technique in …

The development of intelligent technologies gains popularity in the education field. The
rapid growth of educational data indicates traditional processing methods may have …

Predicting students' performance has emerged as an attractive task among researchers.
They use supervised and unsupervised educational data mining (EDM) techniques to build …

The main objective of this study is to apply data mining techniques to predict and analyze
students' academic performance based on their academic record and forum participation …