The role of statistical learning in the L2 acquisition and use of nonadjacent predicate-argument constructions

Abstract While statistical learning of adjacent constructions is well-documented in SLA, our knowledge of this cognitive mechanism concerning nonadjacent constructions remains limited. To address this, we investigated the acquisition of Mandarin predicate-argument constructions containing the preposition duì. Specifically, via a corpus-based approach, we probed whether learners’ core predicate use within these nonadjacent constructions mirrors the patterns of frequency and contingency in their natural language input. Our findings show that learners’ usage aligns with target language distributional regularities, which is consistent with statistical learning. However, our study underscores the necessity of going beyond a sole focus on distributional factors within learners’ input to more fully comprehend L2 production choices and the intricacies of statistical learning. This includes examining variables that shape learners’ exposure to input, such as input accessibility, proficiency, and prototypicality. Finally, we demonstrate the suitability of mixed-effects negative binomial regression to effectively address non-normality and overdispersion in linguistic data.