Please use this identifier to cite or link to this item: https://elar.rsvpu.ru/handle/123456789/40019
Title: Podcasts as a method of teaching the system of precedent texts in the language of sustainable education
Authors: Evtyugina, A.
Volkova, L.
Issue Date: 2020
Publisher: EDP Sciences
Abstract: The relevance of the problem under study is due to the increasing number of foreign students studying Russian and the need to expand approaches to their education in this area, taking into account the current state of the Russian language, its contextuality and precedence. The article is aimed at identifying the need to distinguish precedent units as a separate discipline for the course Russian as a foreign language and the selection of methodological tools that are relevant for this discipline, allowing students to develop speech skills based on the current state of Russian speech. The leading approach to the study of this problem is the method of predictive modeling, which makes it possible to identify the likely advantages of introducing methodological innovations into educational practice. Also, the research methods were a survey with subsequent analysis of the data obtained. The article substantiates the expediency of identifying a separate discipline based on precedent texts for students of Russian as a foreign language, based on the methodological use of educational podcasts. The materials of the article are of practical value for teachers of Russian as a foreign language in higher educational institutions. © The Authors, published by EDP Sciences, 2020.
Keywords: PREDICTIVE ANALYTICS
EDUCATIONAL INSTITUTIONS
FOREIGN LANGUAGE
FOREIGN STUDENTS
METHODOLOGICAL INNOVATIONS
METHODOLOGICAL TOOLS
PREDICTIVE MODELING
RUSSIAN LANGUAGES
SUSTAINABLE EDUCATIONS
STUDENTS
Conference name: 1st Conference on Sustainable Development: Industrial Future of Territories, IFT 2020
Conference date: 28 September 2020 through 29 September 2020
ISSN: 25550403
DOI: 10.1051/e3sconf/202020809033
SCOPUS: 85097712328
Russian Science Citation Index Identifier: 45076762
EDN: YZDBAD
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS

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