Academic institutions operate in an extremely demanding and competitive environment.
Some difficulties confronting most schools are delivering high-quality education to the …

The study examines the prospects and challenges of machine learning (ML) applications in
academic forecasting. Predicting academic activities through machine learning algorithms …

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

Opportunities to apply data mining techniques to analyze educational data and improve
learning are increasing. A multitude of data are being produced by institutional technology, e …

A problem that pervades throughout students' careers is their poor performance in high
school. Predicting students' academic performance helps educational institutions in many …

Abstract Virtual Learning Environments (VLE), such as Moodle and Blackboard, store vast
data to help identify students' performance and engagement. As a result, researchers have …

Machine learning is emerging nowadays as an important tool for decision support in many
areas of research. In the field of education, both educational organizations and students are …

Education is one of the sectors that improves the future of societies; unfortunately, the
pandemic generated by coronavirus disease 2019 has caused a variety of problems that …

The primary goal of educational systems is to enrich the quality of education by maximizing
the best results and minimizing the failure rate of poor-performing students. Early predicting …

This study presents the development of a deep learning model to predict droughts in the
coastal region of Ecuador. Historical information from local meteorological stations was …