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 …

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 …

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

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 …

A significant amount of educational data mining (EDM) research consider students' past
performance or non-academic factors to build predictive models, paying less attention to …

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

While procrastination has been found as a crucial indicator that negatively affects
performance, no research has investigated using a learning management system (LMS) to …