Neuroscientists devise formulas to measure multilingualism

(Press-News.org) More than half of the world’s population speaks more than one language—but there is no consistent method for defining “bilingual” or “multilingual.” This makes it difficult to accurately assess proficiency across multiple languages and to describe language backgrounds accurately. 

A team of New York University researchers has now created a calculator that scores multilingualism, allowing users to see how multilingual they actually are and which language is their dominant one. 

The work, which uses innovative formulas to build the calculator, is reported in the journal Bilingualism: Language and Cognition.

“Multilingualism is a very broad label,” explains Esti Blanco-Elorrieta, an assistant professor of psychology and neural science at NYU and the paper’s senior author. “These new formulas provide a clear, evidence-based way to understand your language strengths and how multilingual you truly are, bringing scientific clarity to an everyday part of life for millions of people.”

The calculator works in nearly 50 languages, including American Sign Language, and allows users to fill in an unlisted language. 

Blanco-Elorrieta and Xuanyi Jessica Chen, an NYU doctoral student and the paper’s lead author, developed the formulas—embedded in a multilingual calculator that users can deploy to measure their multilingualism and language dominance—that are drawn from two primary variables:

Age of language acquisition for listening, reading, speaking, and writing

Self-rated language proficiency for listening, reading, speaking, and writing

The calculator then yields a multilingualism score, which indicates how multilingual a person is on a scale from monolingual to perfect polyglot. The language-dominance is separately tabulated by calculating the difference in ability between languages.

In this video, a trio of multilingual NYU students tried it out to test their abilities in different languages—with results that were both surprising and affirming (video by Jonathan King/NYU).

The authors—both multilingual speakers—note that past research has shown that self-rated language proficiency is, in fact, an accurate and efficient measure of actual language proficiency. The researchers also implemented other statistical controls to minimize self-rating bias. They add that, similarly, age of language acquisition has been shown to be a predictor of abilities: the earlier one learns a language, the more likely it is they will be able to master native-like proficiency in that language. 

The researchers validated their measure by testing it in two distinct populations: healthy young bilinguals and older bilinguals with language impairments. They compared their results to those obtained from existing methods that rely on acquiring much more extensive language background information. Across both groups, the formulas produced language-dominance results that were nearly identical to those generated by more complicated measures, showing that the new approach is both simple and accurate.

“Rather than just labeling someone as ‘bilingual’ or ‘monolingual,’ this tool quantifies how multilingual one is,” notes Chen.

“This calculator offers a transparent, quantitative tool that researchers, clinicians, and educators can adopt to better characterize multilingual populations, ultimately improving research quality and real-world applications—from language education to clinical assessment,” concludes Blanco-Elorrieta. 

The research was supported by grants from the National Institutes of Health (R00DC019973) and the National Science Foundation (2446452).

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