Leona Polyanskaya (Donostia)

Metacognitive Processing in Statistical Learning is Modulated by Bilingualism

Statistical learning is a set of mechanisms aimed to extract regularities from environmental input, which are then used to structure the environment. These mechanisms are also engaged when we listen to natural speech, for example, when we need to structure a continuous speech input into discrete constituents like words and phrases. Metacognition is the ability to evaluate one's own cognitive performance. In statistical learning, for example, this ability is expressed as evaluation whether sensory input is structured correctly. Metacognitive efficiency in a particular task may be potentially modulated by individual experience in this task. Consequently, people who have more experience with language tasks might potentially have better metacognition in language task (including statistical learning task, because these mechanisms are brought to bear when we listen to natural speech). We tested this hypothesis and looked at metacognition in statistical learning in bilinguals and monolinguals, and we found that bilinguals exhibit more efficient metacognitive processing in such tasks. We further accounted for this enhancement by better error-monitoring in language by bilinguals. At the end, I will present a brief outline of my research programme to investigate this phenomenon and its implications.