The last few years have witnessed an upsurge in the number of studies using Machine and
Deep learning models to predict vital academic outcomes based on different kinds and …

The aim of this paper is to survey recent research publications that use Soft Computing
methods to answer education-related problems based on the analysis of educational data …

Content assessment has broadly improved in e-learning scenarios in recent decades.
However, the e-Learning process can give rise to a spatial and temporal gap that poses …

A significant amount of research has indicated that students' procrastination tendencies are
an important factor influencing the performance of students in online learning. It is, therefore …

Using Partial Least Squares-Structural Equation Modeling with WarpPLS, this study
examines the indirect effect of the relationship between learners' social media addiction and …

To examine the similarities and differences between two closely related yet distinct fields–
Educational Data Mining (EDM) and Learning Analytics (LA)–this study conducted a …

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

Research indicates that academic procrastination is a common attitude among learners, and
that it generally has a negative correlation with academic performance. The present …

The existing literature evidences the potential of the e-learning methodology, although some
call it into question. Our study aimed to analyse the real scope of applying this methodology …

The COVID-19 pandemic brought about significant changes in educational delivery methods
and student learning. E-learning systems, which previous research had found to be effective …