The last few years have witnessed an upsurge in the number of studies using Machine and
Deep learning models to predict vital academic outcomes based on different kinds and …

The increased availability of technology in higher education has led to the growth of online
learning platforms. However, a significant concern exists regarding dropout rates in online …

With the immersion of a plethora of technological tools in the early post-COVID-19 era in
university education, instructors around the world have been at the forefront of implementing …

The need for data-driven decision-making primarily motivates interest in analysing Big Data
in higher education. Although there has been considerable research on the value of Big …

Nowadays social media usage has increased drastically among the stakeholders of higher
educational institutions. The COVID-19 pandemic has suddenly increased the surge of …

Privacy poses a significant obstacle to the progress of learning analytics (LA), presenting
challenges like inadequate anonymization and data misuse that current solutions struggle to …

The use of computational tools to predict academic success has become increasingly
popular. Machine learning algorithms, trained on past study histories, have been shown to …

The prediction of university dropout is a complex problem, given the number and diversity of
variables involved. Therefore, different strategies are applied to understand this educational …

Student dropouts are a long-standing, substantial issue in academia that has never received
meaningful attention globally. Numerous research studies have indisputably demonstrated …

Introduction: In the present study, data mining is applied to predict the academic
performance of university Engineering students at the National Autonomous University of …