Understanding, modeling, and predicting student performance in higher education poses
significant challenges concerning the design of accurate and robust diagnostic models …

Predicting student academic performance is a critical area of education research. Machine
learning (ML) algorithms have gained significant popularity in recent years. The capability to …

Abstract Learning Management Systems (LMS) contain large amounts of student data that
can be used to help improve student learning by applying machine learning. Earlier studies …

The anticipation of student performance stands as a pivotal element in educational systems,
with organizations aspiring to enrich the learning experience and elevate student outcomes …

Today, the main aim of educational institutes is to provide a high level of education to
students, as career selection is one of the most important and quite difficult decisions for …

This chapter presents a comprehensive analysis of the results obtained from the predictive
model developed to forecast students' academic performance using machine learning …

College context and academic performance are important determinants of academic
success; using students' prior experience with machine learning techniques to predict …

Educational Data Mining is a discipline focused on developing ways for studying the unique
and increasingly large-scale data generated by educational settings and applying those …

One of the key applications of Learning Analytics is offering an opportunity to the institutions
to track the students' academic activities and provide them with real-time adaptive …

The utilization of machine learning methods for predicting student grades has emerged as a
valuable approach to assessing the educational advancement of academic institutions …