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Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language
Learning is typically understood as a process in which the behavior of an organism is progressively shaped until it closely approximates a target form. It is easy to comprehend how a motor skill or a vocabulary can be progressively learned—in each case, one can conceptualize a series of intermediate...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897795/ https://www.ncbi.nlm.nih.gov/pubmed/27375543 http://dx.doi.org/10.3389/fpsyg.2016.00867 |
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author | Cho, Pyeong Whan Szkudlarek, Emily Tabor, Whitney |
author_facet | Cho, Pyeong Whan Szkudlarek, Emily Tabor, Whitney |
author_sort | Cho, Pyeong Whan |
collection | PubMed |
description | Learning is typically understood as a process in which the behavior of an organism is progressively shaped until it closely approximates a target form. It is easy to comprehend how a motor skill or a vocabulary can be progressively learned—in each case, one can conceptualize a series of intermediate steps which lead to the formation of a proficient behavior. With grammar, it is more difficult to think in these terms. For example, center embedding recursive structures seem to involve a complex interplay between multiple symbolic rules which have to be in place simultaneously for the system to work at all, so it is not obvious how the mechanism could gradually come into being. Here, we offer empirical evidence from a new artificial language (or “artificial grammar”) learning paradigm, Locus Prediction, that, despite the conceptual conundrum, recursion acquisition occurs gradually, at least for a simple formal language. In particular, we focus on a variant of the simplest recursive language, a(n)b(n), and find evidence that (i) participants trained on two levels of structure (essentially ab and aabb) generalize to the next higher level (aaabbb) more readily than participants trained on one level of structure (ab) combined with a filler sentence; nevertheless, they do not generalize immediately; (ii) participants trained up to three levels (ab, aabb, aaabbb) generalize more readily to four levels than participants trained on two levels generalize to three; (iii) when we present the levels in succession, starting with the lower levels and including more and more of the higher levels, participants show evidence of transitioning between the levels gradually, exhibiting intermediate patterns of behavior on which they were not trained; (iv) the intermediate patterns of behavior are associated with perturbations of an attractor in the sense of dynamical systems theory. We argue that all of these behaviors indicate a theory of mental representation in which recursive systems lie on a continuum of grammar systems which are organized so that grammars that produce similar behaviors are near one another, and that people learning a recursive system are navigating progressively through the space of these grammars. |
format | Online Article Text |
id | pubmed-4897795 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-48977952016-07-01 Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language Cho, Pyeong Whan Szkudlarek, Emily Tabor, Whitney Front Psychol Psychology Learning is typically understood as a process in which the behavior of an organism is progressively shaped until it closely approximates a target form. It is easy to comprehend how a motor skill or a vocabulary can be progressively learned—in each case, one can conceptualize a series of intermediate steps which lead to the formation of a proficient behavior. With grammar, it is more difficult to think in these terms. For example, center embedding recursive structures seem to involve a complex interplay between multiple symbolic rules which have to be in place simultaneously for the system to work at all, so it is not obvious how the mechanism could gradually come into being. Here, we offer empirical evidence from a new artificial language (or “artificial grammar”) learning paradigm, Locus Prediction, that, despite the conceptual conundrum, recursion acquisition occurs gradually, at least for a simple formal language. In particular, we focus on a variant of the simplest recursive language, a(n)b(n), and find evidence that (i) participants trained on two levels of structure (essentially ab and aabb) generalize to the next higher level (aaabbb) more readily than participants trained on one level of structure (ab) combined with a filler sentence; nevertheless, they do not generalize immediately; (ii) participants trained up to three levels (ab, aabb, aaabbb) generalize more readily to four levels than participants trained on two levels generalize to three; (iii) when we present the levels in succession, starting with the lower levels and including more and more of the higher levels, participants show evidence of transitioning between the levels gradually, exhibiting intermediate patterns of behavior on which they were not trained; (iv) the intermediate patterns of behavior are associated with perturbations of an attractor in the sense of dynamical systems theory. We argue that all of these behaviors indicate a theory of mental representation in which recursive systems lie on a continuum of grammar systems which are organized so that grammars that produce similar behaviors are near one another, and that people learning a recursive system are navigating progressively through the space of these grammars. Frontiers Media S.A. 2016-06-08 /pmc/articles/PMC4897795/ /pubmed/27375543 http://dx.doi.org/10.3389/fpsyg.2016.00867 Text en Copyright © 2016 Cho, Szkudlarek and Tabor. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Cho, Pyeong Whan Szkudlarek, Emily Tabor, Whitney Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language |
title | Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language |
title_full | Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language |
title_fullStr | Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language |
title_full_unstemmed | Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language |
title_short | Discovery of a Recursive Principle: An Artificial Grammar Investigation of Human Learning of a Counting Recursion Language |
title_sort | discovery of a recursive principle: an artificial grammar investigation of human learning of a counting recursion language |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4897795/ https://www.ncbi.nlm.nih.gov/pubmed/27375543 http://dx.doi.org/10.3389/fpsyg.2016.00867 |
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