Date of Thesis

Spring 2026

Description

Language development research has established that infants can learn language rapidly and without explicit instruction through implicit learning mechanisms like statistical learning. These mechanisms can be used to learn word boundaries, sounds, meanings, and grammar rules of language. One method for investigating this is artificial grammar learning (AGL), in which people are exposed to sequences of nonwords to see if they can unconsciously learn their underlying grammars. While much of statistical learning and AGL research has focused on a monolingual perspective, most of the world’s population is multilingual. Studies like Weiss, Gerfen, and Mitchel (2009) and Mitchel and Weiss (2010) have shown that people can learn word boundaries from two different speech streams, particularly when they are given an indexical cue, such as different speaker voices or faces, to help them differentiate between the two streams. However, bilingual AGL studies like Conway and Christiansen (2006) found that participants don’t learn two artificial grammars if they are too perceptually similar.

The current study investigated whether indexical cues could facilitate the learning of two artificial grammars. Experiment 1 established baseline learning of each artificial grammar in isolation. Experiment 2, contrary to previous research, found that participants could learn two perceptually similar artificial grammars, even with overlapping words. In Experiment 3, participants watched videos where each grammar was spoken by a different person. This visual cue improved learning, suggesting that indexical cues may facilitate the learning of two grammars by improving participants’ ability to differentiate between two artificial grammars. These results suggest that having face cues for different languages may facilitate bilingual language education during early development. Overall, these results contribute to the growing body of research on how bilinguals can learn multiple languages simultaneously.

Keywords

bilingualism, artificial grammar learning, statistical learning, language development

Access Type

Honors Thesis

Degree Type

Bachelor of Science

Major

Neuroscience

First Advisor

Aaron Mitchel

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