Collecting and analysing a student’s digital footprint is an integral part of the Russian education development in the conditions of the digital economy. This activity is connected, among the other things, with the assessment of the students’ formed competencies in the course of blended learning in the educational process. The purpose of the research is development of approaches, methods and tools for analysing the data generated in the digital educational environment (DEE), with a view to assessing the correlation between the structure and content of educational programmes and the results of the students’ educational activities under these programmes. The methodology of the essay is based on the Educational Data Mining (EDM), along with the methods for design and development of information systems and databases. The following data processing methods were used: correlation analysis and Distillation of Data for Human Judgment. The analysis used extensive detailed data on various aspects of the educational process, accumulated for over more than 10 years on the basis of Herzen State Pedagogical University of Russia. The authors have developed a tool for collecting and analysing the students’ digital footprint in a blended learning environment, using EDM methods. A series of calculations was made in accordance with the EDM methods, that make it possible to draw preliminary conclusions about the nature of relationship of some selected indicators (number of actions during the course, students’ activity in the course chat(s), final grade for the course work, attendance time at the course), obtained as part of the student work in the Moodle distance teaching system (DTS), with the interim certification results. For instance, the extent of interrelation between the final e-learning course grade and the results of interim certification is 0.7108, which is evidence of close interdependence. The extent of interrelation between the scope of course activities and the interim certification grade (0.314) shows only slight interdependence. Such calculations serve a basis for the assumptions in respect of assessing the impact of student activities on academic success, on the efficiency of e-learning courses and recommendations for modifying the educational resources with a view to improving their quality. The experience, approaches and results presented by the authors testify to expediency of using EDM methods for the analysis of the educational process.