FORECASTING THE OBJECTIVE NUMBER OF HIGHER EDUCATION INSTITUTIONS IN RELATION TO MODERN FACTORS

Abstract

Introduction. Education is an indicator of the country's intellectual potential. Higher education is a strategic resource through which the state is competitive in the global labour market.complete higher education attests to the professional and cultural level of a considerable number of the population, especially young people, and is not only an indicator of economic growth but also of social stability. The purpose of investigation was determined by the analysis of current state of higher education institutions and the main influencing factors for them. The coefficient of interest of graduates in receiving higher education in Ukraine is determined on the basis of regression analysis. Arima models were constructed using time series theory for prediction of the number of higher education institutions for future periods. Purpose. The purpose of the study is the construction the predictive models of the dynamics of the number of future students and the number of higher education institutions in Ukraine. Methodology. Regression analysis is used as one of the main methods of scientific research in the process of writing the article; time series theory, in particular Arima modeling of the Statistica application package; methods of mathematical modeling, in particular approximating polynomials in the process of modeling the dynamics of the institutions of higher education and the number of students, to determine the ‘coefficient of interest’. Results. The study found that the number of institutions of higher education depends on the one hand on the time factor, on the other – on the number of students. Given that the number of students and the amount higher education institutions can be characterized as a dynamic process, the theory of time series, in particular Arima modelling, was applied. Using Arima models, the number of students and the number of higher education institutions for the next two years is predicted. The relative errors for these models are 6% and 0. 4%, respectively. Based on statistics on the number of graduates of all secondary education institutions and the number of students admitted to higher education institutions of Ukraine, a ‘coefficient of interest’ in higher education was derived, which allows predicting the number of future entrants. The Arima model predicts the number of Ukrainian students in foreign educational institutions. The obtained forecast values regarding the number of students, the amount of higher education institutions of Ukraine, by various methods, adequately reflect the real situation today.