Predicting students' performance is one of the most important issues in educational data
mining (EDM), which has received more and more attention. By predicting students' …

Educational Data Mining (EDM) is a promising area of research that leverages
computational methods to improve educational outcomes by extracting valuable insights …

The growing need for tailored learning experiences in post-secondary education has
resulted in the adoption of educational data mining (EDM) methodologies to derive …

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

Ensuring fair access to quality education is essential for every education system to fully
realize every student's potential. Nowadays, machine learning (ML) is transforming …

Students' performance prediction systems play a vital role in enhancing the educational
performance inside universities, schools, and training centers. Big data can come from …

Aspect-based sentiment analysis (ABSA) has gained a rising concentration recently. It aims
to provide a set of aspect terms and sentiments from a piece of text. Educational Data Mining …

There is an increasing trend of learning analytics dashboards (LADs) being used to provide
feedback to learners. However, there is little empirical evidence about the influence of their …

Predicting students at risk of academic failure is valuable for higher education institutions to
improve student performance. During the pandemic, with the transition to compulsory …

The educational data mining researchers have achieved significant efficiency in predicting
student performance during the tenure of the course. However, an early prediction before …