In Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 262-267). Mahwah, NJ: Lawrence Erlbaum.
Active and passive statistical learning: Exploring the role of
feedback in artificial grammar learning and language
Active and passive statistical learning: Exploring the role of feedback in artificial grammar learning and language
Rick Dale
Morten H. Christiansen
Abstract
Language is immersed in a rich and active environment. One
general dimension of that environment, feedback, may
contribute greatly to learning language structure. Artificial grammar
learning offers an experimental means of exploring
different kinds of potential feedback. In this paper, two
experiments sought to investigate the role of feedback in an
artificial-grammar learning task designed to resemble some
aspects of language acquisition. An artificial language
composed of auditory nonsense syllables and an
accompanying visual semantics were created. Participants
faced the task of mapping a sample sentence to a visual
semantic scene. Results indicated that feedback is highly
useful, allows participants to reach a high level of competence
in the language, and also helps the acquisition of detailed
aspects of the artificial grammar. Implications for language
acquisition are discussed, and future directions considered.Click here to download a PDF version.
Please email suggestions/errors to mhc27@cornell.edu |