< jats: p> The primary task of machine learning is to extract valuable information from the
data that is generated every day, process it to learn from it, and take useful actions. Original …

Students' success has recently become a primary strategic objective for most institutions of
higher education. With budget cuts and increasing operational costs, academic institutions …

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 …

Purpose Many higher education institutions are investigating the possibility of develo**
predictive student success models that use different sources of data available to identify …

The early classification of university students according to their potential academic
performance can be a useful strategy to mitigate failure, to promote the achievement of …

In this competitive scenario of the educational system, the higher education institutes use
data mining tools and techniques for academic improvement of the student performance and …

Educational Data Mining (EDM) and Learning Analytics (LA) research have emerged as
interesting areas of research, which are unfolding useful knowledge from educational …

The capacity to predict student academic outcomes is of value for any educational institution
aiming to improve student performance and persistence. Based on the generated …

To successfully reduce student attrition, it is imperative to understand what the underlying
determinants of attrition are and which students are at risk of drop** out. We develop an …

Data-driven machine learning (ML) methods are extensively employed for modeling and
simulation of highly complicated processes. ML techniques confirmed their great predictive …