T.A. Kontsova1, E.P. Dogadina2

1,2 Financial University under the Government of the Russian Federation (Moscow, Russia)

Problem. Currently, the process of compiling a control or any other test work lies entirely with the teacher. However, the formation of the form of tasks for the control work takes place without taking into account the personal characteristics of the student. The success of writing a test paper often depends not only on the assessment, but also on the moral component of the success of the student. Because of this, it is very important not only to test the acquired knowledge and acquired skills, but also to make the process of passing the knowledge control more "smooth" for the student from a psycho-emotional point of view.

Target. To improve academic performance by developing a program for selecting control tasks for conducting an intermediate cut of knowledge, taking into account the individual characteristics of students.

Results. The paper developed a hybrid system of multi-criteria optimization with two fully connected neural networks, which determines the most appropriate model for compiling a test task, based on a number of features of a particular student.

Practical significance. The proposed algorithm, used to solve problems of multi-criteria optimization, can provide such results of optimization of the parameters of educational tasks that will lead not only to an increase in student performance, but also to a decrease in stress when performing control or verification work, taking into account the personal characteristics of students. In addition, the work is intended to relieve a number of responsibilities from the teacher in the preparation of control work.

Kontsova T.A., Dogadina E.P. Multi-criteria optimization of the preparation of control work for the student using neural networks. Neurocomputers. 2023. V. 25. № 5. Р. 41-49. DOI: https://doi.org/10.18127/j19998554-202305-06 (In Russian)

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