Artificial Intelligence is increasingly being employed in education, specifically through
machine learning techniques, to improve the quality of education and refine teaching and …

This study uses three machine learning models to predict student dropouts based on
students' transcript, demographic, and learning management system (LMS) data from a …

In the educational landscape, educational data mining has emerged as an indispensable
tool for institutions seeking to deliver exceptional and high-quality education. However …

Introduction Student dropout, as a dynamic and complex system, requires a broad
conceptualization. The aim of this article is to analyze the concept of student dropout in …

Dropout refers to the phenomenon of students leaving school before completing their
degree or program of study. Dropout is a major concern for educational institutions, as it …

The problem of student dropout in higher education has gained significant attention within
the Educational Data Mining research community over the years. Since student dropout is a …

The features present in large datasets significantly affect the performance of machine
learning models. Redundant and irrelevant features will be rejected and cause a decrease …

Designing proper treatment plans to manage diabetes requires health practitioners to pay
heed to the individuals remaining life along with the comorbidities affecting them. Older …

Introducción: La educación superior está transformándose con la adopción de modalidades
virtuales e integración de tecnologías como la inteligencia artificial (IA), machine learning …

The opportunity to pursue tertiary education has increased in recent years, attributed to the
initiatives and efforts made by governments, industry players, and educational institutions to …