Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …

Anomalies in education affect the personal careers of students and universities' retention
rates. Understanding the laws behind educational anomalies promotes the development of …

In the realm of Educational Data Mining (EDM), the predictive analysis of student
performance has emerged as a pivotal area of interest, particularly within computer science …

In universities, student dropout is a major concern that reflects the university's quality. Some
characteristics cause students to drop out of university. A high dropout rate of students …

The hard times of COVID 19 have shown mankind some harsh reality. Numerous sectors
including education have been terribly victimized by the grasp of the pandemic. Schools …

Neural networks are becoming increasingly widely used in various fields, especially for
academic risk forecasts. Academic risk prediction is a hot topic in the field of big data in …

When a student does not pass the requirements to graduate from a vocational college, the
drop out (DO) system is usually utilized. The Naive Bayes technique make it simple to learn …

School dropout is a problem faced by educational systems worldwide across various levels
of education and institutions. In this regard, several strategies are studied and tested to …

Educational Data Mining (EDM) plays a vital role in discovering meaningful relationships
from educational data. In recent years, the application of EDM has become an active …

A significant concern in universities is student dropout, which reflects the institution's quality
and affects its reputation and the students' future careers. High dropout rates can directly …