Proceedings of the Annual Meeting of the Cognitive Science Society

In recent years, a number of methodological approaches has been developed that allow for identifying patterns in first language acquisition. In most cases, such methods have been used to analyze monolingual acquisition. In a global perspective, however, monolingual acquisition is the exception, and multilingualism is the norm. This raises the question to what extent such pattern-detection methods can be used for multilingual data as well, especially in the case of code-mixing, i.e. the use of more than one language in a single utterance. In this paper, we explore the potential of a data-driven approach to child language data proposed by McCauley & Christiansen (2019a), viz. chunk-based learning, to account for multilingual acquisition data. In particular, we compare the patterns found in the children’s code-mixed utterances with those in their monolingual utterances to test the hypothesis that both types of utterances are ultimately constructed from the same “building blocks”.