This study focused on the generation of the licensure examination performance models
implementing PART and JRip classifiers. Specifically, it identified the attributes that are …

This study focused on two main points: the generation of licensure examination performance
prediction models; and the development of a Decision Support System. In this study, data …

Educational Data Mining can help stakeholders give appropriate decisions to improve
educational experiences. New knowledge or models are realized when data mining …

The students' progression and attainment gap are considered as key performance indicators
of many universities worldwide. Therefore, universities invest significantly in resources to …

Objectives: Data mining techniques are implemented in many organizations as a standard
procedure for analyzing the large volume of available data, extracting useful information and …

Most students have a problem to keep track on their learning performance. Some lecturers
with high teaching hours and burden of administration jobs may have difficulty to identify …

Purpose The purpose of this paper is to present an empirical study on the effect of two
synthetic attributes to popular classification algorithms on data originating from student …

Objectives: Universities accumulate huge amount of student's data in electronic form. Based
on the information stored in the database filtering a data on certain criteria becomes difficult …

Predicting students' academic performance is of paramount importance to educational
institutions. If students' academic performance is predicted course-wise, semester-wise and …

Education is a key factor for achieving a long-term economic progress. Although the
educational level of punjab has been improved in the last decades. But results can be more …