City Research Online

Abstract

Artificial Grammar Learning (AGL) is an experimental paradigm that has been used extensively in cognitive research for many years to study implicit learning, associative learning, and generalization based either on similarity or rules. Without computer assistance it is virtually impossible to generate appropriate grammatical training stimuli along with grammatical or non-grammatical test stimuli that control relevant psychological variables. We present the first flexible, fully automated software for selecting AGL stimuli. The software allows users to specify a grammar of interest, and to manipulate characteristics of training and test sequences, and their relationship to each other. The user thus has direct control over stimulus features that may influence learning and generalization in AGL tasks. The software enables researchers to develop AGL designs that would not be feasible without automatic stimulus selection. It is implemented in Matlab.

Publication Type:	Article
Additional Information:	The final publication is available at Springer via http://dx.doi.org/10.3758/BRM.40.1.164
Subjects:	B Philosophy. Psychology. Religion > BF Psychology P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments:	School of Health & Psychological Sciences > Psychology
SWORD Depositor:	Symplectic Administrator

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