scholarly journals Desirable Difficulties in Language Learning? How Talker Variability Impacts Artificial Grammar Learning

2021 ◽  
Author(s):  
Federica Bulgarelli ◽  
Daniel J. Weiss
Keyword(s):  
Language Learning ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Talker Variability ◽  
Desirable Difficulties ◽  
Grammar Learning

scholarly journals An empirical review of language learning based on the micro-artificial grammar-learning paradigm

2018 ◽  
Vol 48 (11) ◽  
pp. 1487-1496
Author(s):  
Libo GENG ◽  
Li YANG ◽  
Yiming YANG
Keyword(s):  
Language Learning ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Learning Paradigm ◽  
Grammar Learning

scholarly journals Desirable difficulties in statistical learning? How talker variability impacts artificial grammar learning

2021 ◽  
Author(s):  
Federica Bulgarelli ◽  
Daniel Weiss
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Talker Variability ◽  
Multiple Components ◽  
Grammar Learning ◽  
Adult Participants ◽  
Learning Conditions ◽  
Invariant Properties ◽  
Current Paradigm

Contending with talker variability has been found to lead to processing costs but also benefits by focusing learners on invariant properties of the signal. These discrepant findings may indicate that talker variability acts as a desirable difficulty. That is, talker variability may lead to initial costs followed by long term benefits for retention and generalization. Adult participants learned an artificial grammar affording learning of multiple components by 1-, 2- or 8- talkers, tested at 3 time points. The 8-talker condition did not impact learning. The 2-talker condition negatively impacted some aspects of learning, but only under more difficult learning conditions. Across both experiments, generalization of the grammatical dependency was difficult. Taken together, we discovered that high and limited talker variability differentially impact artificial grammar learning. However, talker variability does not act as a desirable difficulty in the current paradigm, as the few evidenced costs were not related to long-term benefits.

Abstraction Processes in Artificial Grammar Learning

1997 ◽  
Vol 50 (1) ◽  
pp. 216-252 ◽  
Author(s):  
David R. Shanks ◽  
Theresa Johnstone ◽  
Leo Staggs
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

Artificial Grammar Learning: Influence of Number of Exemplars and Exemplar Prototypicality

2007 ◽  
Author(s):  
T. Porsius Jarry ◽  
H. Poletiek Fenna
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

The influence of resources limitation on decision-making processes in Artificial Grammar Learning Task

2013 ◽  
Author(s):  
Agnieszka Poplawska ◽  
Marta Roczniewska ◽  
Radoslaw Sterczynski
Keyword(s):  
Decision Making ◽  
Learning Task ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning ◽  
Decision Making Processes

Information theory and artificial grammar learning: inferring grammaticality from redundancy

2015 ◽  
Vol 80 (2) ◽  
pp. 195-211 ◽  
Author(s):  
Randall K. Jamieson ◽  
Uliana Nevzorova ◽  
Graham Lee ◽  
D. J. K. Mewhort
Keyword(s):  
Information Theory ◽  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning

The information acquired during artificial grammar learning.

1994 ◽  
Vol 20 (1) ◽  
pp. 79-91 ◽  
Author(s):  
Barbara J. Knowlton ◽  
Larry R. Squire
Keyword(s):  
Artificial Grammar Learning ◽  
Artificial Grammar ◽  
Grammar Learning
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