A.Yu. Cherepkov1, O.V. Druzhinina2

1,2 Bunin Yelets State University (Yelets, Russia)

2 FRС «Computer Science and Control» of Russian Academy of Sciences (Moscow, Russia)

1cherepkov.andrey@mail.ru; 2ovdruzh@mail.ru 

Currently, ensuring the process of assessing students' knowledge is associated with the development of adaptive instrumental and methodological support, which allows you to take into account and adjust the level of training of each student. Machine learning methods and artificial neural networks are widely used in solving problems of modeling and instrumental support of pedagogical processes. It should be noted that effective results can be obtained using multinomial logistic regression based on an integrated approach combining interactive testing and predictive modeling tools. The purpose of the article is to develop instrumental and methodological support for the assessment and forecasting of knowledge in the pedagogical process, taking into account the use of interactive testing algorithms and predictive modeling based on multinomial logistic regression. A software package has been developed to assess students' knowledge and predict academic performance in the educational process, which combines interactive testing tools with predictive modeling using multinomial logistic regression. For the development of the software package, the high-level Python language was used with the involvement of mathematical libraries. The aspects of the development of a support system for the course "Intelligent transport systems" in higher and additional education systems are considered. The obtained results can be used in solving problems of improving intellectual educational environments and in modeling pedagogical processes. In addition, the results can be used to analyze the effectiveness of teaching methods, identify trends and patterns in the educational process, as well as predict student academic performance.

Cherepkov A.Yu., Druzhinina O.V. Instrumental and methodological support for the assessment and forecasting of knowledge in the pedagogical process. Nonlinear World. 2024. V. 22. № 1. P. 15-21. DOI: https://doi.org/10.18127/ j20700970-202401-02 (In Russian)

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