EDM METHODS FOR PREDICTING THE ACADEMIC PERFORMANCE OF UNIVERSITY STUDENTS BASED ON REGRESSION ANALYSIS

Abstract

The article substantiates the relevance of the application of Educational Data Mining methods arising within the educational process for the study of the implementation of the educational program.   Educational Data Mining is closely related to Learning analytics. Educational Data Mining and Learning Analytics are relatively new directions and require the creation of a methodology and appropriate tools .   Data mining is used to extract useful information and discover patterns from often large datasets closely related to knowledge discovery in databases and data science. In this paper, linear regression is used from machine learning algorithms to determine the loan relationship between student performance and learning outcomes of disciplines from the cycle of general education subjects of the educational program. The purpose of this study is to use the Knowledge Data Discovery process to extract useful information about the implementation of the educational program.