In several areas, including education, the use of machine learning, such as artificial neural
networks, has resulted in significant improvements in predicting tasks. The opacity of these …

Predicting student performance using educational data is a significant area of machine
learning research. However, class imbalance in datasets and the challenge of developing …

Successful prediction of student performance has significant impact to many stakeholders,
including students, teachers and educational institutes. In this domain, it is equally important …

In every educational institution, predicting pupils' performance is a vital responsibility. Due to
this, a variety of data mining techniques, such as clustering, classification, and regression …

The education domain is growing at an exponential rate, maturing with the introduction of
innovative and improved offerings to the learning community aided by various Education …

With the emergence of more new teaching systems, such as Massive Open Online Courses
(MOOCs), massive amounts of data are constantly being collected. There is a huge value in …

The careful analysis and evaluation of students' results are an important part of the
educational activity, with a potentially strong impact on the students' future development …

An essential component of the educational activity is rigorous examination and assessment
of students' results, with a potential substantial influence on student growth. This paper offers …

Previous studies widely report the optimization of performance predictions to highlight at‐
risk students and advance the achievement of excellent students. They also have …

Predicting students' performance in advance could help assist the learning process; if “at-
risk” students can be identified early on, educators can provide them with the necessary …