One of the most popular phrases in recent years has become “Big data”, “data mining”. These technologies are widely used in distance education, forming the optimal learning path. But can they help students who prefer full-time education, and full-time universities themselves in shaping their development trajectories? The location of the university is much more important to the full-time studies rather than for part-time and distance learning. The development of the university as a whole or individual areas of training takes place in the conditions of its surrounding city, country and related restrictions and directions of the university development.

Rankings, indices show the current situation in the country and the region in various aspects. Every year new rankings appear; already existing ones clarify their methodology and accumulate information by year. When processing the countries data using statistical and machine learning methods, these data can reveal common relationships and patterns, while analyzing the dynamics of various activities of a country and region based on macroeco- nomic laws using modern Big data, data mining technologies, it is possible to build short-term and medium-term development forecasts for countries and regions.

For example, using the analysis of world rankings, a comple- mentary study was performed. At the first stage, it was shown that the education level index given in two independent rankings does not depend on its absolute funding. In other words, the number of people who receive education at all levels does not depend on public and private expenditures on education, including grants and donations from international agencies and non-governmen- tal organizations. At the second stage, a model was created that confirmed the hypothesis that corruption has a significant impact on the lack of correlation between education financing and edu- cation quality, for which an index of corruption deterrence was introduced into the study.

Retrospective analysis allows identifying existing patterns and looking at them in dynamics, for example, a retrospective anal- ysis of education financing (as a percentage of GDP) depending on what proportion of GDP natural resources constitute, that is, strategies for long-term investment in human resources with varying degrees of natural resource endowment. A study of data from 1970 to 2014 showed that countries that are more dependent on natural resources invest less in education than countries that do not have significant natural resources, and this stratification is only growing.

But for the rankings use development in the sphere of education, it is important that universities can form their individual strategies from the data on existing dependencies between various aspects of life, the level of development and dynamics of countries and regions. How is it possible to use countries and regions rankings for the development of the university? Universities, which main- tain premises, hostels and stadiums, conduct training within the framework of curriculum and schedule, have a permanent staff, structured into departments, consisting ultimately of teachers and students, largely depend on their location. The average salary of teachers, the level of material and technical base of the university are linked to the socio-economic situation of the country. Legal aspects, the level of freedoms, the level of preparation of students, health protection, ecology and many other aspects influence the educational process, which, in turn, depends on the country and region. Just as a university cannot develop in isolation from social, economic, political and other conditions, so university development strategies should not be compiled without taking into account the specific features and advantages and disadvantages of a country and a region. It is possible to evaluate all this with the help of multifactor ranking analysis. For example, an analysis of the relationship of the place of countries in the innovation ranking with the number of universities in these countries in the university rankings showed a correlation of 0.79, which indicates a strong relationship between these indicators. A detailed analysis showed that the relationship between the number of graduates from the best universities in the country and the level of innovation should be even higher.

A joint analysis of university and region rankings provides in- formation about favorable conditions for development directions of the region and country, about the conditions to be created, about the professions in demand.

In turn, each student can form his/her own educational path depending on the combination of all the factors that he/she expects from learning, and these include the environment, communica- tion with professors and peers, living on campus as well as the prospects for the development of the university, country, region. The system of university choosing should become the result of a complex machine analysis of all conditions using bid data and complex data mining technologies.

The results obtained through rankings multifactor analysis allow us to assess the prospects of further research. A correctly constructed model of the country, in turn, will allow universities to build their development strategies based on forecasting the development of a country, a region, or the world as a whole. And if such development models exist for countries and universities, the academic mobility will receive a new impetus when a student choosing an educational trajectory will be able to use an additional tool for planning his/her future.

published in: Countries and regions ranking indicators dynamics as the key to university and student individual strategy. Bebenina E.V. THE UNESCO PROJECT “FUTURES OF EDUCATION”. Moscow, 2019. pp. 12-14