Learning language requires acquiring the grammatical categories of words in the language, but learning those categories requires understanding the role of words in the syntax. In this study, we examined how this chicken and egg problem is resolved by learners of an artificial language comprising nouns, verbs, adjectives, and case markers following…

New linguistic information must be integrated into our existing language system. Using a novel experimental task that incorporates a syntactic priming paradigm into artificial language learning, we investigated how new grammatical regularities and words are learned. This innovation allowed us to control the language input the learner received,…

A hallmark of grammatical knowledge is the ability to parse novel syntactic structures. Previous artificial language studies have examined learning hierarchical structures, but few have involved meaningful language and shown generalization to novel structures. This study addressed this issue using the semiartificial language paradigm. The…

Situated within second language (L2) research about the acquisition of morphosyntax, this study investigated English L2 speakers' detection and primed production of a novel construction with morphological and structural features. We report on two experiments with Thai (n = 69) and Farsi (n = 70) English L2 speakers, respectively, carried out an…

Humans are remarkably sensitive to the statistical structure of language. However, different mechanisms have been proposed to account for such statistical sensitivities. The present study compared adult learning of syntax and the ability of two models of statistical learning to simulate human performance: Simple Recurrent Networks, which learn by…