A model of digital transformation of the learning process in higher education

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Abstract

Problem statement . The article explores the issues of digitalisation of the process of teaching mathematical disciplines in higher education. The need for serious transformations in the content of teaching of many academic disciplines within the framework of the developed strategy of digital transformation of science and higher education forms the relevance of this topic. The aim of the article is to develop the digital transformation of the learning process in higher education, to develop a structural and functional model of digital transformation of the learning process and the prospects for its use in higher education. Methodology. The following methods were used: integration of corporate information environment, IT-tools, and virtual learning environment with the content of academic disciplines; graphical method; experiment; and student survey. Results. The main features of digitalisation of teaching elements of probability theory at the Faculty of Economics using the corporate information system of the university are revealed. Examples of both lecture and seminar classes following the compiled learning model are presented. Theoretical analysis of mathematical, scientific, methodological literature on digital transformation of the learning process in Russia and some foreign countries was conducted. Conclusion. The practical significance of the study lies in the possibility of using the model of digital transformation of the learning process in various disciplines for both higher schools and secondary general education institutions planning to move to digitalisation of the learning process in the near future. The scientific novelty of the article is in the fact that the feasibility of digital transformation of the teaching process of probability theory in higher education in Russia has been theoretically substantiated and practically confirmed.

About the authors

Olga V. Ivanova

Financial University under the Government of the Russian Federation

Author for correspondence.
Email: oviva75@mail.ru
ORCID iD: 0000-0002-8978-5611
SPIN-code: 9731-3121

Candidate of Pedagogical Sciences, Associate Professor at the Department of Mathematics, Faculty of Information Technologies and Big Data Analysis

49/2 Leningradsky Prospect, Moscow, 125167, Russian Federation

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