DEFINITION OF THE COEFFICIENTS OF THE MATHEMATICAL MODEL OF QUALITY MANAGEMENT OF TRAINING BY THE METHOD OF LINEAR PROGRAMMING
V.I. Sumin, L.D. Kuznetsova, M.A. Lukin
This article examines the process of analyzing the level of quality of education in a higher educational institution. This problem was solved on the basis of using problem-oriented components of the educational process management system of the higher educational institution. To form problem-oriented components of the educational process management system of a higher educational institution, it is necessary to develop a model and algorithm for the process of making managerial decisions in it. Formalization and typification of educational information is carried out, which takes into account the time and indicators of the evaluation of the effectiveness of the quality management of training. Formed sets and sequence of a set of actions on the information that is used in the management of the quality of training. The processing time of elements of educational information in a higher educational institution is considered known on the grounds that it is regulated by normative documents. An evaluation of the duration of the step of taking managerial influences is determined on the basis of a certain set of procedures that in a certain sequence process the educational information of a higher educational institution. The coefficients of importance of the elements of providing information that determine the formation of managerial influence are determined. The procedures for providing information perform functions: determining parameters for a particular procedure, selecting and arranging the selected information, developing mathematical models. A mathematical formulation of the problem is defined in a general form, which allows us to formalize the task of optimizing the management impact, which is used in the management of the quality of instruction using the linear programming method.
Keywords: predicate, predicate significance, variable-valued logical function, logical neural network, cognitive map, cluster analysis, neural network.