Big data: some ways to solve the problems of higher education

Abstract

The article deals with issues related to the transition to digitalization of higher professional education, as well as with the widespread use of distance education technologies. The analysis of methods for monitoring the quality of education of university students is carried out. There are five types of data that require the application of big data analysis methods: personal data; data on the interaction of students with and between e-learning systems; data on the effectiveness of educational material; administrative data; forecasts. To solve a number of problems, we propose the use of Education Data Mining technology, which will allow us to design digital education management systems based on data and ways to systematize them for making organizational, pedagogical and managerial decisions. The analysis of educational data is based on the prediction of models, the identification of learning structures, and the identification of relationships. The possible ways of developing the individual trajectory of a student studying at the university, his further caree.