Data-Driven approach as big data analytics in education within the context of digitalization Available to Purchase

The relevance of the study is determined by the fact that existing educational information systems and Big Data technologies for the first time in history make it possible for pedagogy to quickly, continuously and fully register an extensive array of observations of the learning process, behavior and academic performance of students. The purpose of the study is to present the Data-Driven methodology in the context of the transition from traditional descriptive analytics to decision–making analytics. The empirical basis of the study is the following list of works: David Niemi's "Learning Analytics in Education", " Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities" by Chintan Bhatt, Priti Srinivas Sajja, Sidath Liyanage, and "Intellectual analysis of educational data" conducted at University 2035. In the article, the author reveals the questions of what is the Data-Driven approach in general and how it can be applied in training; why it is important to track changes and how to do it; what questions need to be asked before building an analytics system for a training program; how data is collected for training analytics. The practical significance of the research results is provided by the fact that the presented Data-Driven methodology, as Big Data analytics in education in the context of digitalization, will allow the educational analytics system to automate many routine processes, identify problems at early stages and act proactively.