(untitled) (JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, 2023)
Abstract In recent days, a wide variety of tools have appeared for performing educational data mining (EDM) . The current education systems show that there are several factors affecting students’ performances. First and foremost, students need motivation in order to learn and this motivation results into their success. The prediction of student performances is an important field of research in Educational Data Mining, particularly through the application of different data mining techniques. The majority of EDM research focuses on prediction algorithms. The current work presents a review of the data mining predicting algorithms and tools that have been adopted in EDM. It also provides insight into the algorithms and powerful data mining tools that most widely used in student performance prediction. This will mainly be of use for educators, instructors and institutions, increasing the students’ levels of study.