Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

AGL StimSelect: Software for automated selection of stimuli for artificial grammar learning

Bailey, Todd M. and Pothos, Emmanuel M. 2008. AGL StimSelect: Software for automated selection of stimuli for artificial grammar learning. Behavior Research Methods 40 (1) , pp. 164-176. 10.3758/BRM.40.1.164

Full text not available from this repository.


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 on the basis of either similarity or rules. Without computer assistance, it is virtually impossible to generate appropriate grammatical training stimuli along with grammatical or nongrammatical 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 therefore has direct control over stimulus features that may influence learning and generalization in AGL tasks. The software, AGL StimSelect, enables researchers to develop AGL designs that would not be feasible without automatic stimulus selection. It is implemented in MATLAB.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Publisher: Psychonomic Society
ISSN: 1554-351X
Last Modified: 05 Jun 2020 02:30

Citation Data

Cited 7 times in Google Scholar. View in Google Scholar

Cited 13 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item