The impact of adjacent-dependencies and staged-input on the learnability of center-embedded hierarchical structures

A theoretical debate in artificial grammar learning (AGL) regards the learnability of hierarchical structures. Recent studies using an AnBn grammar draw conflicting conclusions (Bahlmann & Friederici, 2006; De Vries, Monaghan, Knecht, & Zwitserlood, 2008). We argue that 2 conditions cruciall...

Full description

Saved in:
Bibliographic Details
Published in:Cognition 2011-02, Vol.118 (2), p.265-273
Main Authors: Lai, Jun, Poletiek, Fenna H.
Format: Article
Language:English
Subjects:
Artificial grammar learning
Biological and medical sciences
Center-embedding
Cognition
Cognitive Psychology
Experiments
Female
Fundamental and applied biological sciences. Psychology
Grammar
Hierarchical structures
Hierarchy
Human
Humanistic Education
Humans
Learning
Learning. Memory
Linguistics
Male
Pedagogy
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Starting small
Testing
Training
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A theoretical debate in artificial grammar learning (AGL) regards the learnability of hierarchical structures. Recent studies using an AnBn grammar draw conflicting conclusions (Bahlmann & Friederici, 2006; De Vries, Monaghan, Knecht, & Zwitserlood, 2008). We argue that 2 conditions crucially affect learning AnBn structures: sufficient exposure to zero-level-of-embedding (0-LoE) exemplars and a staged-input. In 2 AGL experiments, learning was observed only when the training set was staged and contained 0-LoE exemplars. Our results might help understanding how natural complex structures are learned from exemplars.
ISSN:0010-0277
1873-7838
DOI:10.1016/j.cognition.2010.11.011