Ensemble Learning is an algorithm that searches for the best prediction result based on
several classifier solutions which are come from different algorithms. Ensemble learning has …

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 …

In every educational institution, predicting pupils' performance is a vital responsibility. Due to
this, a variety of data mining techniques, such as clustering, classification, and regression …

Recommender algorithms are widely used in e-commercial platforms to recommend users
suitable items according to users' preferences. In recent years, an increasing amount of …

Predicting student performance (PSP), one of the task in Student Modeling, has been taken
into account by educational data mining community recently. Previous works show that good …

This paper focuses on presenting the benefits of a stacking technique, an ensemble method,
for academic achievement prediction. The data for this study consisted of students' grades in …

Graduates' employability becomes one of the performance indicators for higher educational
institutions (HEIs) because the number of graduates produced every year from higher …

Students' performance is an important factor for the evaluation of teaching quality in
colleges. The prediction and analysis of students' performance can guide students' learning …

At the beginning of a new semester, due to the limited understanding of the new courses, it
is difficult for students to make predictive choices about the courses of the current semester …

A University admission process is a complex process that needs a tremendous amount of
time and labor to allocate course (s) to the prospective applicants. The study aimed at …