Artificial language creation as a tool for assessing children’s metalinguistic abilities

Author:

Brykova A. A.1ORCID

Affiliation:

1. Saint Petersburg State University

Abstract

The author aims to analyse two projects of the artificial language Uniling. They were created by students of years 5 to 11 within the linguistic framework of the "Formula de Integreco" training camp in June 2017 and January 2018. The research methods included structural analysis of the artificial language, as well as its creation process in comparison with Russian, i. e. the native language for all participants in the experiment. Research results: the specific conditions for artificial language development enable us to trace the stages of its accelerated "evolution" and complexity buildup at all levels. The latter becomes possible by shifting the initial focus away from observing the economy principle in language and raising randomly occurring exceptions to the status of a rule. Such rules are further extrapolated to other same-level units of the artificial language. This indicates that children attach importance to the concept of linguistic norm, as well as the possibility of clear grammatical differentiation when the grammatical meaning is secondary relative to the lexical-conceptual one. Children give no less significance to the inner form of words, which makes it possible to create lexemes employing the means of the artificial language itself without relying on the material of natural substrate languages. Moreover, the inner form helps to outline the systemic connections within the thematic groups. However, the hypernym/hyponym relations are obviously weak as generic concepts are not found in the Uniling lexis. At the same time, the aesthetics and euphony notions often come to the fore, which is reflected in the expression plane of artificial language lexemes and in the idea of the pragmatic potential of the language. This is most clearly seen at the syntax level due to the introduction of particular semantic role markers not typical of the Russian language (benefactives and malefactives). Conclusions: artificial language analysis enables us to identify the strengths and weaknesses of children’s metalinguistic representations, which can be considered in the process of teaching Russian at school.

Publisher

Our Language

Reference14 articles.

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