Recycling constructional patterns: The role of chunks in early bilingual acquisition
Year: 2025
Type: article
Abstract: Aims and Objectives: Over the last decades, usage-based research into child language acquisition has shown that multi-word units play a key role in child language acquisition. This paper sets out to explore the role of multi-word units in the bilingual speech of two German-English bilingual children, focusing on their code-mixing and starting from the hypothesis that code-mixed utterances can be accounted for with the help of constructional patterns that are in turn abstracted away from recurrent multi-word units. Approach: We used the Chunk-Based Learner (CBL), a computational model developed by Stewart McCauley and Morten Christiansen. Data and Analysis: We applied the CBL to longitudinal data from two children growing up bilingually with the same language pair (German-English) but notably different input situations, to detect recurrent multi-word units in the data. Conclusions: The study shows that both monolingual and code-mixed utterances are built from the same constructional patterns, highlighting the crucial role of chunks in language acquisition. Although code-mixed utterances appear highly creative, they largely rely on fixed, formulaic patterns similar to those found in monolingual speech. This finding supports the usage-based approach, suggesting that chunk-based learning is fundamental across different language acquisition contexts. Originality: Using a strictly bottom-up approach allows us to identify recurrent chunks that are used as “building blocks” of early child language, including, importantly, code-mixed utterances. Significance: Our study adds to previous research emphasizing the role of multi-word units in early bilingual acquisition and contributes to ongoing efforts to pinpoint the way in which constructional patterns emerge from multi-word units in more detail.
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
Estimated APC paid: $3,650
Funder: Deutsche Forschungsgemeinschaft
OpenAlex ID: W4411429475
