Student performance prediction is a great area of concern for educational institutions to
prevent their students from failure by providing necessary support and counseling to …

Student retention is a widely recognized challenge in the educational community to assist
the institutes in the formation of appropriate and effective pedagogical interventions. This …

Machine Learning (ML) technologies play a key role in improving the decision-making
process involved in higher education sector. Campus placement not only affects a student's …

Predicting students' performance has emerged as an attractive task among researchers.
They use supervised and unsupervised educational data mining (EDM) techniques to build …

One of the common problems that most of the engineering institutions face in recent times is
poor academic results. The statistics of the IOE semester result show that since 2009 AD, the …

The amount and variety of student data collected by the higher education institution, together
with the potential of Educational Data Mining and analytics, provide a potential for the …

Educational data mining is the process of applying data mining tools and techniques to
analyze data at educational institutions. In this paper, educational data mining was used to …

Purpose The prediction of student attrition is critical to facilitate retention mechanisms. This
study aims to focus on implementing a method to predict student attrition in the upper years …

Automatic Student performance prediction is a crucial job due to the large volume of data in
educational databases. This job is being addressed by educational data mining (EDM) …

Student dropout issue is a major concern among the academics and management of the
university. The higher rate of student dropout impacted the university reputation such as …