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Open Access Publications from the University of California

Can you tell them apart? Using machine learning to classify bilinguals’ and multilinguals’ cognitive and linguistic performance


The debate of whether bilingualism provides a cognitive and or linguistic advantage is a lasting one. Underlying this debate is the idea that an additional language shapes cognition and linguistic processing. The current research analyzes a behavioral dataset containing individuals’ performance in different general cognitive and linguistic tests using a machine learning approach to classify individuals as bilinguals or multilinguals based on their performance. Using an extreme gradient boosting model, we were able to achieve a balanced accuracy of 77%. High scores on a prescriptive grammar test, a verbal fluency test, and a picture naming test were predictive for multilingualism. The implications of the reported results for the field and future research are discussed.

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