Applying data mining (DM) in education is an emerging interdisciplinary research field also
known as educational data mining (EDM). It is concerned with developing methods for …

The usage of learning management systems in education has been increasing in the last
few years. Students have started using mobile phones, primarily smart phones that have …

Machine learning (ML) techniques are increasingly prevalent in education, from their use in
predicting student dropout to assisting in university admissions and facilitating the rise of …

Classroom teaching becomes viable and efficient based on increase in participation of the
student. This can be made possible by taking needed measure by finding the emotions of …

In the area of machine learning and data science, decision tree learning is considered as
one of the most popular classification techniques. Therefore, a decision tree algorithm …

In higher educational institutes, many students have to struggle hard to complete different
courses since there is no dedicated support offered to students who need special attention …

Electronic learning (e‑learning) plays a significant role in improving the efficiency of the
education process. However, in many cases in developing countries, technology transfer …

Student performance predictive analysis has played a vital role in education in recent years.
It allows for the understanding students' learning behaviours, the identification of at-risk …

Purpose Educational data mining (EDM) and learning analytics, which are highly related
subjects but have different definitions and focuses, have enabled instructors to obtain a …

Educational data mining (EDM) is an emerging discipline that focuses on applying data
mining tools and techniques to educationally related data. The discipline focuses on …