The use of machine learning techniques in higher education can be beneficial in optimizing
teaching and providing higher institutions with the solutions they need, like monitoring …

Abstract Machine learning has emerged as the most widely used tool in resolving
administrative and other educational-related problems like student dropout. Most of the …

Accompanied with the development of storage and processing capacity of modern
technology, educational data increases sharply. It is difficult for educational researchers to …

The quality of instructors' performance mainly influences the quality of educational services
in higher educational institutions. One of the major challenges of higher educational …

Data mining applications are feasible tools for tackling different business applications such
as financial, healthcare, telecommunication and e-learning, and so on. Most of the literature …

Students' perception on course satisfaction through student surveys has become more
influential in institutional operations because their experience in study may affect not only …

Prediction of student performance in educational institutions is a major topic of debate
among researchers in efforts to improve teaching and learning. Effective prediction …

Faced with the disruption generated by the COVID-19 pandemic, the advent of enforced and
exclusive online learning presented a challenging opportunity for researchers worldwide, to …

Data mining is most efficient when used deliberately to achieve a corporate goal, answer
business or research questions, or contribute to a problem-solving solution. Data mining …

Student's proficiency in a subject may be gauged through the use of Learning Management
Systems (LMS)(LMSs). Using a scoring algorithm to calculate the percentage of each …