The role of feedback in implicit and explicit artificial grammar learning: a comparison between dyslexic and non-dyslexic adults

2017 ◽  
Vol 67 (3) ◽  
pp. 333-355 ◽  
Author(s):  
Rachel Schiff ◽  
Ayelet Sasson ◽  
Galit Star ◽  
Shani Kahta
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning ◽  
Implicit And Explicit

scholarly journals The Role of Anti-harmony in Learning Neutral Vowels

2019 ◽  
Vol 7 ◽  
Author(s):  
Sara Finley
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Vowel Harmony ◽  
Front Vowel ◽  
Learning Paradigm ◽  
Grammar Learning ◽  
Back Vowel

The present study used an artificial grammar learning paradigm to explore the prediction that exposure to anti-harmony might help learners infer that a neutral vowel in a vowel harmony language is transparent. Participants were exposed to a back/round harmony language with a neutral vowel [a]. This neutral vowel either always selected a back vowel suffix,  always selected a front vowel suffix, or selected both front-and back vowel suffixes, in adherence to anti-harmony. Results indicated that exposure to a back/round harmony with the neutral vowel selecting either back vowel suffixes, or both front and back vowel suffixes, could induce a bias towards transparent vowels. Assuming that participants inferred that the centralized [a] paired with [o] harmonically, then the predictions that exposure to anti-harmony could induce a bias towards a transparent vowel interpretation were borne out. However, the bias towards a transparent vowel was not significantly different between the anti-harmony conditions and the harmony condition, suggesting that this effect should be replicated with other neutral vowels.

The role of working memory in artificial grammar learning

2009 ◽  
Author(s):  
Michelle A. Hendricks ◽  
Christopher M. Conway ◽  
Ronald T. Kellogg
Keyword(s):  
Working Memory ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

Volitional control in the learning of artificial grammars

1999 ◽  
Vol 22 (5) ◽  
pp. 757-758
Author(s):  
Peter A. Bibby ◽  
Geoffrey Underwood
Keyword(s):  
Explicit Knowledge ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Volitional Control ◽  
Knowledge Representations ◽  
Feeling Of Knowing ◽  
Grammar Learning ◽  
Artificial Grammars ◽  
Access To Knowledge ◽  
Implicit And Explicit

Dienes & Perner argue that volitional control in artificial grammar learning is best understood in terms of the distinction between implicit and explicit knowledge representations. We maintain that direct, explicit access to knowledge organised in a hierarchy of implicitness/explicitness is neither necessary nor sufficient to explain volitional control. People can invoke volitional control when their knowledge is implicit, as in the case of artificial grammar learning, and they can invoke volitional control when any part of their knowledge representation is implicit, as can be seen by examining “feeling of knowing” phenomena.

The Role of Simple Semantics in the Process of Artificial Grammar Learning

2017 ◽  
Vol 46 (5) ◽  
pp. 1285-1308
Author(s):  
Birgit Öttl ◽  
Gerhard Jäger ◽  
Barbara Kaup
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

scholarly journals Role of selective attention in artificial grammar learning

2008 ◽  
Vol 15 (6) ◽  
pp. 1154-1159 ◽  
Author(s):  
Daisuke Tanaka ◽  
Sachiko Kiyokawa ◽  
Ayumi Yamada ◽  
Zoltán Dienes ◽  
Kazuo Shigemasu
Keyword(s):  
Selective Attention ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning
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