Analysis of the Pedagogical Experiment Results on the Implementation of Distance Learning Technologies in the Teaching of Mathematical Disciplines for Technical Specialties of Universities

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Abstract

The article considers the results of a pedagogical experiment on the implementation of modern distance educational technologies in the teaching of mathematical disciplines to students of technical specialties of higher education. As a basis for the experiment, an electronic textbook on the course "Theory of the function of a complex variable" was used. It was used as part of the distance learning system CLASS.NET to teach this discipline at the Moscow Aviation Institute. The article presents the results of the preliminary statistical analysis of the homogeneity of experimental and control groups of students and the results of their questionnaire in order to identify the motivation for the use of distance learning tools in the educational process. A comparative analysis of the current ratings of students of experimental and control groups, calculated at the time of conducting control measures during the semester, is provided. The effectiveness of using the developed distance learning technology (LMS) in the educational process is confirmed by the results of statistical studies of the final assessments of students obtained during full-time testing.

General Information

Keywords: electronic textbook, distance learning, statistical analysis, questionnaire, effectiveness of LMS, intrinsic motivation, extrinsic motivation

Journal rubric: Method of Teaching

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2023130211

Funding. The reported study was funded by Russian Science Foundation (RSF), project number 22-28-00588.

Received: 10.05.2023

Accepted:

For citation: Martyushova Y.G. Analysis of the Pedagogical Experiment Results on the Implementation of Distance Learning Technologies in the Teaching of Mathematical Disciplines for Technical Specialties of Universities. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2023. Vol. 13, no. 2, pp. 194–205. DOI: 10.17759/mda.2023130211. (In Russ., аbstr. in Engl.)

References

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Information About the Authors

Yanina G. Martyushova, PhD in Education, Associate Professor of the Department of Probability Theory and Computer Modeling, Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0000-0001-7803-5914, e-mail: ma1554@mail.ru

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