As online learning has been widely adopted in higher education in recent years, artificial
intelligence (AI) has brought new ways for improving instruction and learning in online …

The potential influence of data mining analytics on the students' learning processes and
outcomes has been realized in higher education. Hence, a comprehensive review of …

Several challenges are associated with e‐learning systems, the most significant of which is
the lack of student motivation in various course activities and for various course materials. In …

The tremendous growth in electronic data of universities creates the need to have some
meaningful information extracted from these large volumes of data. The advancement in the …

A personalized e-learning system is effective in imparting enhanced learning to its users. As
compared to a conventional e-learning system, which provides similar contents to each …

Student performance modelling is one of the challenging and popular research topics in
educational data mining (EDM). Multiple factors influence the performance in non-linear …

An admissions system based on valid and reliable admissions criteria is very important to
select candidates likely to perform well academically at institutions of higher education. This …

Presently, educational institutions compile and store huge volumes of data, such as student
enrolment and attendance records, as well as their examination results. Mining such data …

Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …

The ability to predict student performance in a course or program creates opportunities to
improve educational outcomes. With effective performance prediction approaches …