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-  2018 

FORECASTING THE CHANGE IN THE TEACHER'S CONTRIBUTION TO THE WORK OF THE DEPARTMENT USING THE METHODS OF DATA MINING

DOI: https://doi.org/10.33407/itlt.v63i1.1949

Keywords: teacher assessment, data mining, forecasting, regression, neural networks, perceptron, information system, Unified Modeling Language, Object-Pascal

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Abstract:

The existing forms and methods of assessing the work of teachers of higher educational institutions are described. The conclusion is made that the combination of indicators into groups (categories) and the introduction of different weight factors depends on the specifics of the institution and the prevailing ideas about the priority of this or that type of activity. Practically all the considered methods do not take into account the change in the contribution share of each teacher in the integral indicator of the work of the whole department (department, faculty). The goal was to predict the change in the contribution of an individual teacher to the indicators of a higher education institution by means of mathematical modeling and intellectual decision-making. The prediction task is identified as a suitable data mining task. Methods for forecasting the assessment of the work of teachers - regression and neural network - were chosen. An object-oriented model of a projected computer system in the language of visual modeling of UML is described. Diagrams of use cases, classes and states are given. The program implementation of the intellectual decision-making system for evaluating the work of teachers of a higher education institution and an example of the system's operation based on real data are described. Conclusions are made about a possible change in the contribution share of each teacher in the indicators of the department

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