Abstract
The paper deals with the problem of constructing a system of rating indicators to stimulate the work of the teaching staff of a higher educational institution. A lot of directions of the teacher's activity (educational, scientific, international, etc.) has laid the basis for selecting groups of indicators in the system. The social challenge for improving the quality of educational services has determined the relevance of the research in the field of modeling and forecasting the indicators that characterize the work of a higher education teacher. The use of the information hypercube for the structure of the initial data has made it possible to take into account the individual characteristics of each parameter that is part of the mathematical model for describing the rating indicators. The drift of indicators means that the introduction of new indicators, the removal of existing indicators, the relocation of indicators between groups are taken into account. For the first time the authors have introduced a quantitative indicator of the variability of groups, the value of which determines the forecasting strategy in the future period of a teacher's work at the higher educational institution. To predict the total amount of incentives, a comprehensive methodology has been proposed that contains four modules: modeling the values within the existing range in the previous period; modeling the values of a new indicator based on the assumptions entered using the generator of a random number; excluding the range of values of remote indicators; modeling new values on the basis of studying a modern trend of indicators. The presence of a flexible information structure in the form of a hypercube and a complex mathematical model has made it possible to carry out a computational exper-iment for predicting the values of group and individual indicators. In the course of the experiment, the structural stability of the values has been revealed, which has not lead to a great change in the quantitative ratio between the groups of indicators.
Keywords
Management, faculty, rating system, model, forecast.
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