Enhancing Student Success in Physical Education Through Educational Data Mining Techniques

Each year, universities and colleges assess the rates of success in order to improve the academic performance and failure rates of students. Different techniques, including statistical analysis, physical examinations, and in-course data mining are employed to determine these rates. This paper implements an educational data mining approach, which examines large data sets, in order to extricate important information that will enable to optimize students’ academic and physical life. We consider data concerning their performance, class behavior, activity participation, and other traits. The data is harvested through the KNIME platform and other algorithms.