Modeling and forecasting performance indicators for educational activites of higher educational institution

Introduction. In Russia, the effectiveness of educational activities of higher educational institutions is monitored on an annual basis. The Ministry of Education and Science of the Russian Federation established the monitoring procedure and eight threshold levels for performance indicators. A university may be revoked or reformed if at least four important indicators are below threshold levels. There is no special software for operational management of performance indicators. The aim of the research is to develop mathematical models, methods and programs for modeling and forecasting performance indicators. Materials and Methods. The developed complex of mathematical models consists of a model of system dynamics and a regression model. As the simulated variables, the basic performance indicators of the educational activities of the university are used: educational activities, research activities, international activities, financial and economic activities, the salaries of teaching staff, employment of graduates, a contingent of students, additional indicators of educational organizations. The adequacy of the developed mathematical models was checked with the help of actual values of performance indicators. The description of the numerical method for solving a system of differential equations through "manual" integration via use of a recurrent three-step procedure with an intuitive step selection is presented. The method is based on the Runge-Kutta method of the fourth order of accuracy. Results. An example of calculating the predicted values of the performance indicators of the Balakovo Branch of the Russian Presidential Academy of National Economy and Public Administration on the time interval in [0;3] years using the developed software is presented. The procedure for calculating the quadratic criterion used for operational management of performance indicators is described. The magnitude of the quadratic criterion is determined through using the Simpson method and the artificial Elman recurrent neural network to improve the accuracy of the computations. The structural scheme of interaction of users with the program module during monitoring is provided. Discussion and Conclusions. The developed mathematical software can be used to predict the performance indicators of the educational activities of the university in monitoring. This method reduces significantly the probability of emergence of critical situations. The operational management of performance indicators is carried out by varying the values of the quadratic criterion.