Literature DB >> 18411539

AGL StimSelect: software for automated selection of stimuli for artificial grammar learning.

Todd M Bailey1, Emmanuel M Pothos.   

Abstract

Artificial grammar learning (AGL) is an experimental paradigm that has been used extensively incognitive 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.

Mesh:

Year:  2008        PMID: 18411539     DOI: 10.3758/brm.40.1.164

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  4 in total

1.  Implicit chaining in cotton-top tamarins (Saguinus oedipus) with elements equated for probability of reinforcement.

Authors:  Charles Locurto; Laura Dillon; Meaghan Collins; Maura Conway; Kate Cunningham
Journal:  Anim Cogn       Date:  2013-01-24       Impact factor: 3.084

2.  Artificial grammar learning is facilitated by distributed practice: Evidence from a letter reordering task.

Authors:  Rachel Schiff; Ayelet Sasson; Hadas Green; Shani Kahta
Journal:  Cogn Process       Date:  2021-08-09

3.  An entropy model for artificial grammar learning.

Authors:  Emmanuel M Pothos
Journal:  Front Psychol       Date:  2010-06-17

Review 4.  Does complexity matter? Meta-analysis of learner performance in artificial grammar tasks.

Authors:  Rachel Schiff; Pesia Katan
Journal:  Front Psychol       Date:  2014-09-25
  4 in total

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