Natural languages contain systematic relationships between verb meaning and verb argument structure. Artificial language learning studies typically remove those relationships and instead pair verb meanings randomly with structures. Adult participants in such studies can detect statistical regularities associated with words in these languages and…

The Spanish verbal system offers more evidence for agreement and tense than English, where morphological evidence is less robust. With a focus on the comprehension of verbal agreement morphology by child second (L2) learners of Spanish and English, we extend the Variational Learning account to L2 acquisition to investigate whether the abundance of…

When linguistic input contains inconsistent use of grammatical forms, children produce these forms more consistently, a process called "regularization." Deaf children learning American Sign Language from parents who are non-native users of the language regularize their parents' inconsistent usages. In studies of artificial languages…

The present study investigates the multiple constraints on the processing of English dative alternation by Chinese EFL (English as a Foreign Language) learners. The intermediate and advanced learners completed an acceptability judgment task which was composed of 30 dative alternations selected from a spoken corpus. The results showed that the…

Successful language acquisition hinges on organizing individual words into grammatical categories and learning the relationships between them, but the method by which children accomplish this task has been debated in the literature. One proposal is that learners use the shared distributional contexts in which words appear as a cue to their…

The phenomenon of regularization -- learners imposing systematicity on inconsistent variation in language input -- is complex. Studies show that children are more likely to regularize than adults, but adults will also regularize under certain circumstances. Exactly why we see the pattern of behaviour that we do is not well understood, however.…