Toward a Typology of Writing Errors in the Kazakh Language: Corpus-Based Data and Cognitive Interpretation
https://doi.org/10.55491/2411-6076-2025-4-132-144
Abstract
The article presents a comprehensive analysis of language errors found in written texts in the Kazakh language (compositions, essays, dictations, and other written works). The study is based on a corpus approach and includes the classification of over 100 types of errors: orthographic, punctuation, grammatical, lexical, stylistic, and technical. The paper analyzes common writing errors occurring in the works of students of different age groups. The relevance of the study lies in the need for a systematic description and digital documentation of writing errors in Kazakh, which contributes to the creation of a specialized Error Corpus – a new research database designed to reveal the patterns of linguistic interference, features of linguistic worldview, and the dynamics of written language norms. The development of this corpus allows not only objective description of language deviations but also their cognitive and psycholinguistic interpretation. The research employs a comprehensive approach combining corpus linguistics and cognitive modeling methods. The results show that the most frequent errors are orthographic, lexical, grammatical, and punctuation errors, arising under the influence of Russian interference, cognitive information processing patterns, and automated speech templates. The obtained data form the foundation for the further development of the Kazakh Error Corpus and contribute to improving written language norms, teaching methodology, and diagnostic practices.
About the Authors
M. AbayevaKazakhstan
Madina Abayeva, Corresponding Author, Сandidate of Philological Sciences, Associate Professor
Almaty
A. Nazarova
Kazakhstan
Aliya Nazarova, Doctoral Student
Almaty
Sh. Kazakbayeva
Kazakhstan
Shakhlo Kazakbayeva, Doctoral Student
Almaty
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Review
For citations:
Abayeva M., Nazarova A., Kazakbayeva Sh. Toward a Typology of Writing Errors in the Kazakh Language: Corpus-Based Data and Cognitive Interpretation. Tiltanym. 2025;100(4):132-144. (In Russ.) https://doi.org/10.55491/2411-6076-2025-4-132-144
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