Proceedings of the Annual Meeting of the Cognitive Science Society

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.