Poor academic performance of students is a concern in the educational sector, especially if it
leads to students being unable to meet minimum course requirements. However, with timely …

Poor academic performance of students is a concern in the educational sector, especially if it
leads to students being unable to meet minimum course requirements. However, with timely …

This paper presents the outcomes of linking an educational data mining approach to model
students' academic performance. Three data mining classification models (Naïve Bayes …

Educational data mining is widely deployed to extract valuable information and patterns from
academic data. This research explores new features that can help predict the future …

Elements of applied statistics and computer science are quickly integrating and being
applied to a diverse set of problems in academia and industry. Here I explore the potential …

While predictive analytics have been used in a wide range of situations, by far the most
common use of predictive analytics is to improve student retention and academic …

Educational Data Mining (EDM) involves the extraction of concepts and similar useful
information from data sets that store information about academic work. EDM incorporates a …

Purpose This paper aims to evaluate educational data mining methods to increase the
predictive accuracy of student academic performance for a university course setting. Student …

In every educational institution, predicting pupils' performance is a vital responsibility. Due to
this, a variety of data mining techniques, such as clustering, classification, and regression …

The increasing numbers enrolling for college courses, and increased diversity in the
classroom, poses a challenge for colleges in enabling all students achieve their potential …