Supporting data for “Statistical Learning of Multiple Regularities in Multilingual Indian Children With and Without Language Disorders"

Multilingualism has emerged as a global necessity in the dynamically evolving digital age. With exposure to multiple languages and writing systems, neurotypical children develop awareness of diverse linguistic rules. Statistical properties in the language environment enable implicit learning of co-occurring pattern distribution, which is known as implicit statistical learning (ISL). Although previous research has examined ISL in language and reading acquisition, the impact of multilingual exposure on individuals’ potential for acquiring multiple regularities remains underexplored. Examining ISL’s abilities in multilingual children with and without language impairments is essential for understanding the role of associated cognitive mechanisms dedicated to learning multiple regularities within and across languages. In three empirical studies, this thesis examined ISL among Indian multilingual children with and without developmental language disorder (DLD) and developmental dyslexia (DD). The first study examined the effect of multilingualism on multiple regularity ISL and its association with meta-linguistic skills and reading in typically developing children. The second study examined the age and multiple regularity effects in visuo-motor ISL among children and adolescents with and without DD using a non-linguistic serial reaction time paradigm. Finally, employing a novel Zipfian distribution-based naturalistic language stimuli, the third study investigated the role of the chunking mechanism in multiple regularity ISL in children with and without DLD and DD.