Machine learning classifiers emerge as productive tools to develop prediction models which
forecast the final outcome of the students, in a course, and provide an opportunity to the …

During the teaching process of college courses, prediction of students' final performance at
early stages can help teachers intervene students and improve the teaching effects. In …

Predicting learners' prospective performance depending on their current educational data is
critical for implementing appropriate educational measures for guaranteeing learners' timely …

While modelling students' learning behavior or preferences has been found as a crucial
indicator for their course achievement, very few studies have considered it in predicting …

This study investigates the effectiveness of machine learning and deep learning models for
early prediction of student performance in higher education institutions. Using the Open …

In the past few years, interest in applying intelligent data-mining techniques to educational
datasets has increased rapidly, with goals ranging from identifying students who need …

While predictive analytics have been used in a wide range of situations, by far the most
common use of predictive analytics is to improve student retention and academic …

Predicting students' performance to identify which students are at risk of receiving a
D/Fail/Withdraw (DFW) grade and ensuring their timely graduation is not just desirable but …

One of the most crucial aspects is predicting students' performance in the educational
domains such as schools and universities, because it aids in the creation of effective …

This research investigates the impact of machine learning on higher education teaching and
learning, as well as strategies for enhancing the learning environment. There has been a …