Year: 2025
Type: article
Abstract: Purpose. The purpose of this study is to develop a twelve-category classification of German–Ukrainian cognates in order to support psycholinguistic research and second language acquisition. The study aims to assess the recognizability of cognates across languages with typologically different structures and non-shared scripts (Latin and Cyrillic), using a data-driven and theoretically informed model. Methods. The main method is a psycholinguistic and corpus-based analysis of 1.000 high-frequency lexical items from German and Ukrainian. The classification is based on four criteria: semantic, phonological, morphological, and orthographic similarity. An adapted transparency scale (based on Van Bezooijen & Gooskens, 2007) was applied to categorize cognates across four recognizability levels: fully transparent, semi-transparent, partially opaque, and opaque. Computational tools such as Levenshtein distance and IPA-based transcription were used to assess formal similarity. Results. The analysis resulted in a twelve-category classification system for German–Ukrainian cognates, based on semantic, phonological, morphological, and orthographic criteria. Each category reflects a distinct combination of formal and functional similarity, with particular emphasis on transparency and recognizability. The transparency levels – fully transparent, semi-transparent, partially opaque, and opaque – were operationalized using adapted psycholinguistic criteria and applied to 1,000 high-frequency lexical items. The classification proved effective in highlighting patterns of cross-linguistic lexical accessibility, offering insights into bilingual lexical activation and potential transfer phenomena in language acquisition. The integration of Levenshtein distance and IPA-based transcription supported the objective categorization of items across different scripts. This systematic classification allows us to interpret the similarities between German and Ukrainian not as random coincidences, but as the result of consistent linguistic processes that can be understood and analysed. Conclusions. The twelve-category framework supports vocabulary acquisition, contrastive grammar instruction, and digital language learning. Although designed for German–Ukrainian, it is scalable to other typologically and orthographically distant languages. The model contributes to research on lexical transparency, script effects, and cross-linguistic transfer in bilingual processing. The present classification of German–Ukrainian cognates is not only of linguistic and didactic value, but also of psycholinguistic significance. By structuring lexical transparency across scripts, the model contributes to understanding bilingual lexical activation, cognitive processing in cross-script reading, and lexical transfer in second language acquisition. Furthermore, the framework provides a basis for optimizing language learning strategies and supports the development of cognitively informed algorithms in natural language processing and artificial intelligence.
Source: PSYCHOLINGUISTICS
Author: Nataliia Oberste-Berghaus
Institution: Osnabrück University
Language: Ukrainian
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $97
OpenAlex ID: W4416124382