Predicting students' performance is one of the most important issues in educational data
mining (EDM), which has received more and more attention. By predicting students' …

Numerous students suffer from academic procrastination; it is a common problem and
phenomenon in academic settings. Many previous researchers have analyzed its …

E-learning is achieved by the deep integration of modern education and information
technology, and plays an important role in promoting educational equity. With the …

Data mining is employed to extract useful information and to detect patterns from often large
data sets, closely related to knowledge discovery in databases and data science. In this …

As universities around the world have begun to use learning management systems (LMSs),
more learning data have become available to gain deeper insights into students' learning …

The GoKoan e-learning platform supports face-to-face training in an educational community.
Its aim is to optimise the way and the time of study in order to improve academic …

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

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 …

The swelling use of computerized learning, accompanied by the rapid growth of information
technology has become a surge of interest in the research community. Consequently …

The early prediction of students' performance is a valuable resource to improve their
learning. If we are able to detect at-risk students in the initial stages of the course, we will …