Mathematical Apparatus for Some Quality Indicators Assessment of a Training Webinar Using Machine Learning
https://doi.org/10.55648/1998-6920-2024-18-1-121-143
Abstract
This article is the second stage of creating and researching a technology for assessing the quality of contact work at a university implemented through webinars. The mathematical support of the intelligent technology for analyzing the audio-video stream of an educational webinar recording is considered. The problem of increasing the efficiency and reliability of assessing some indicators of the quality of contact work at the Faculty of Distance Learning of SibSUTIS implemented through distance learning webinars is being solved. Machine learning methods and their implementation using standard Python modules and libraries are used for analysis. The scientific significance of the work lies in the development of new models and algorithms for intelligent analysis of audio-video streams parameterized for processing the recording of an educational event. The developed models and algorithms make it possible to increase the efficiency of the process of assessing the quality of contact work implemented through webinars.
About the Authors
V. V. PodkolzinRussian Federation
Vadim V. Podkolzin, Cand. of Sci. (Physical and Mathematical), Head at the Department of Information Technologies
Krasnodar
A. N. Poletaikin
Russian Federation
Aleksey N. Poletaikin, Cand. of Sci. (Engineering), Assistant Professor at the Information Technologies Department, Kuban State University; аssistant professor at the Mathematical Modeling and Digital Development of Business System Department, Siberian State University of Telecommunications and Information Science
Krasnodar, 630102, Novosibirsk, Kirov St. 86
M. Yu. Galkina
Russian Federation
Marina Yu. Galkina, Assistant Professor of the Department of Applied Mathematics and Cybernetics
630102, Novosibirsk, Kirov St. 86
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Review
For citations:
Podkolzin V.V., Poletaikin A.N., Galkina M.Yu. Mathematical Apparatus for Some Quality Indicators Assessment of a Training Webinar Using Machine Learning. The Herald of the Siberian State University of Telecommunications and Information Science. 2024;18(1):121-143. (In Russ.) https://doi.org/10.55648/1998-6920-2024-18-1-121-143