EXPERT SYSTEM OF SUCCESS IN HIGHER EDUCATIONAL INSTITUTIONS ON THE BASIS OF FUZZY LOGIC

L. V. Dranishnikov, T. M. Gordienko

Abstract


An essential feature of higher education is the complexity of quantitative assessment of learning processes. An unambiguously understood list of quality indicators for training does not exist, since there are no clear ideas about what quantitatively measurable factors influence it, what reliably evaluating indicators it expresses, what is the reliability of these indicators, etc. The vagueness of such a view does not allow outdated methods of mathematical modeling to obtain adequate quantitative descriptions of the parameters studied, and therefore makes it necessary to search for solutions to the classical problems of the educational process by non-classical methods.

It is proposed to carry out the current and intermediate control of the development of each discipline by a student within the framework of an accumulative point-rating system.

Based on the analysis of current performance, a production model of an expert system of forecasting performance in higher educational institutions has been built. Accounting for quantitative and qualitative factors in the integrated assessment of student knowledge was carried out using linguistic variables. For the built fuzzy model in the C # language and Windows Forms components of the Microsoft Visual Studio 2015 environment, the software was developed.

The practical significance of the study lies in the possibility of using the constructed system as a universal means for determining student performance; the student has the ability to predict the results of his educational activity and thereby manage the process of developing his individual competence, and the teacher or the head of the department has the ability to control this process. It should be noted that the proposed methodology of fuzzy modeling of an expert system of success in higher educational institutions is adaptive to systems of various nature.

Keywords


expert system; fuzzy model; the linguistic variable; membership function; success

References


Заде Л.А. Понятие лингвистической переменной и его применение к принятию при-ближенных решений/ Л.А.Заде. – М.: Мир, 1976. – 165с.

Дранишников Л.В. Інтелектуальні методи в управлінні: навч. посіб. Кам’янське: ДДТУ, 2018. 416с.




DOI: https://doi.org/10.31319/2519-2884.35.2019.58

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Copyright (c) 2019 L. V. Dranishnikov, T. M. Gordienko

ISSN (print) 2519-2884

ISSN (online) 2617-8389