Applying digital natural language processing tools to optimize subject teacher training in a multilingual educational environment
Zaripova Rinata Raisovna
Kazan Federal University
Submitted: 16.12.2023
Abstract. The aim of the research is to automate the analysis process of the most common grammatical forms and syntactic structures of a foreign or second language to optimize the content and acquisition of English language programs in the training of future Mathematics teachers for professional activities in a multilingual educational environment. The paper theoretically justifies the necessity of a comprehensive frequency analysis of language structures. Software tools for natural language processing (the Python programming language and the spaCy library) were developed, which were subsequently applied in the course “Methods of Mathematical Data Processing” to identify the most frequent grammatical forms and syntactic structures characteristic of the English language of Mathematics. Based on the data obtained, methodological recommendations were formulated for the content and outcomes of English language programs for future Mathematics teachers in a multilingual educational environment. The scientific novelty of the research lies in using digital natural language processing (NLP) tools for a quantitative and statistical analysis of language data, necessary for the development of methodological recommendations for the content and outcomes of foreign/second language programs for subject teacher training. As a result of the research, it was found that digital natural language processing tools can be used to improve the language training of subject teachers in a multilingual educational environment.
Key words and phrases: полилингвальное образование, русский язык, английский язык, обработка естественного языка, технология предметно-языкового интегрированного обучения, multilingual education, Russian language, English language, natural language processing, Content and Language Integrated Learning (CLIL)
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