Дослідження впливу якості засвоєння попереднього матеріалу на успішність здобувачів освіти з окремої дисципліни

Abstract

The paper considers the basic concepts related to the quality of education in general and the assimilation of students of educational material. The problem of predicting a student's grade in any discipline is formulated, having grades in "providing" disciplines. A list of methods that can be applied to solve the problem (multivariate regression analysis method, artificial neural networks method, k nearest neighbors method) is presented, a conclusion is made about the expediency of using the artificial neural networks method. The formulation of the problem of predicting the assimilation of knowledge and programming skills is described. The architecture used was a perceptron with four input neurons, one output neuron, and 10 hidden layer neurons. By conducting a series of numerical experiments, the optimal architecture of the neural network was selected. As an example, the curriculum and the structural and logical scheme of the educational and professional program "Intelligent Decision Making Systems" of the specialty 124 "System Analysis" were used. The created information model of the designed system is described in the visual modeling language UML (diagrams of use cases, classes, cooperation, sequence, states, activities and components). The possibilities of the system for studying the influence of the assimilation of the previous material on the prediction of students' grades in a particular discipline are described, an example of the functioning of this system is given, and an analysis of the results of calculations is carried out. It is indicated that the system allows analysis of the results of calculations for further selection of the best method for forecasting.