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Abstract: The article considers an approach to modeling actual grammar skills based on the data about the development of linguistic personality in ontogenesis using corpus tools. The actual grammar skills, i.e. a set of grammatical forms on the basis of which the speaker constructs their speech, can become the basis for developing new methods of teaching Russian grammar. The object of this study is modeling of the child’s actual grammar skills by means of the grammatical corpus of children’s speech. The study of the grammatical patterns of children’s speech using corpus methods is complicated because of the lack of readymade (marked) corpora. To solve this problem, the author makes an attempt to create an analogue corpus of children’s speech in order to study the process of acquisition of grammar in ontogenesis. The statistical data about the grammatical patterns of children’s speech extracted from the created corpus make it possible to identify and clarify the composition of genetically earlier grammatical forms and categories and to identify the frequently used grammatical forms and those located on the periphery of the child’s grammatical competence. These forms are acquired at an older age and remain rare in the child’s active grammar skills. The potential of this corpus is illustrated using the material of the speech of children aged 2–3 years: the study reveals the set of children’s grammar skills, singles out the most relevant grammatical oppositions, and highlights the word forms most frequently used in this period of speech development. The grammatical corpus of children’s speech is used as an instrument for studying grammatical patterns and for creating a frequency profile of the child’s grammar skills; for identifying the most common word forms in the period under study; and for demonstrating the dynamic nature of grammar skills development.

About the author(s) :

Evgeniya S. Krasnoperova
Ural State Pedagogical University (Russia, Ekaterinburg)
ORCID ID: https://orcid.org/0000-0001-9675-1367

Publication Timeline:

Date of receipt: 07.05.2024; date of publication: 24.06.2024

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