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Simultaneous acquisition of vocabulary and grammar in an artificial language learning task

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published

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Simultaneous acquisition of vocabulary and grammar in an artificial language learning task. / Walker, Neil; Schoetensack, Christine; Monaghan, Padraic et al.
CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition. The Cognitive Science Society, 2017. p. 1307-1312 (CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Walker, N, Schoetensack, C, Monaghan, P & Rebuschat, P 2017, Simultaneous acquisition of vocabulary and grammar in an artificial language learning task. in CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition. CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, The Cognitive Science Society, pp. 1307-1312, 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017, London, United Kingdom, 26/07/17. <https://www.proceedings.com/35829.html>

APA

Walker, N., Schoetensack, C., Monaghan, P., & Rebuschat, P. (2017). Simultaneous acquisition of vocabulary and grammar in an artificial language learning task. In CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition (pp. 1307-1312). (CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition). The Cognitive Science Society. https://www.proceedings.com/35829.html

Vancouver

Walker N, Schoetensack C, Monaghan P, Rebuschat P. Simultaneous acquisition of vocabulary and grammar in an artificial language learning task. In CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition. The Cognitive Science Society. 2017. p. 1307-1312. (CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition).

Author

Walker, Neil ; Schoetensack, Christine ; Monaghan, Padraic et al. / Simultaneous acquisition of vocabulary and grammar in an artificial language learning task. CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition. The Cognitive Science Society, 2017. pp. 1307-1312 (CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition).

Bibtex

@inproceedings{aef959fd121c444fab2863e6648c6d1a,
title = "Simultaneous acquisition of vocabulary and grammar in an artificial language learning task",
abstract = "Learning syntax requires determining relations between the grammatical categories of words in the language, but learning those categories requires understanding the role of words in the syntax. In this study, we examined how this chicken and egg problem is resolved by learners of an artificial language comprising nouns, verbs, adjectives and case markers following syntactic rules. We found that the language could be acquired through cross-situational statistical correspondences with complex scenes and without explicit feedback, and that knowledge was maintained after 24 hours. Results also showed that verbs and word order were the first to be acquired, followed by nouns, adjectives and finally case markers. Interdependencies in learning were found for word order and verbs, and also for nouns, adjectives and case markers. Grammar and vocabulary can be acquired simultaneously, but with distinctive patterns of acquisition - grammar and the role of verbs first, then the vocabulary of other lexical categories.",
keywords = "artificial language learning, grammar, language acquisition, statistical learning, vocabulary",
author = "Neil Walker and Christine Schoetensack and Padraic Monaghan and Patrick Rebuschat",
note = "Publisher Copyright: {\textcopyright} CogSci 2017.; 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017 ; Conference date: 26-07-2017 Through 29-07-2017",
year = "2017",
language = "English",
series = "CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition",
publisher = "The Cognitive Science Society",
pages = "1307--1312",
booktitle = "CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society",

}

RIS

TY - GEN

T1 - Simultaneous acquisition of vocabulary and grammar in an artificial language learning task

AU - Walker, Neil

AU - Schoetensack, Christine

AU - Monaghan, Padraic

AU - Rebuschat, Patrick

N1 - Publisher Copyright: © CogSci 2017.

PY - 2017

Y1 - 2017

N2 - Learning syntax requires determining relations between the grammatical categories of words in the language, but learning those categories requires understanding the role of words in the syntax. In this study, we examined how this chicken and egg problem is resolved by learners of an artificial language comprising nouns, verbs, adjectives and case markers following syntactic rules. We found that the language could be acquired through cross-situational statistical correspondences with complex scenes and without explicit feedback, and that knowledge was maintained after 24 hours. Results also showed that verbs and word order were the first to be acquired, followed by nouns, adjectives and finally case markers. Interdependencies in learning were found for word order and verbs, and also for nouns, adjectives and case markers. Grammar and vocabulary can be acquired simultaneously, but with distinctive patterns of acquisition - grammar and the role of verbs first, then the vocabulary of other lexical categories.

AB - Learning syntax requires determining relations between the grammatical categories of words in the language, but learning those categories requires understanding the role of words in the syntax. In this study, we examined how this chicken and egg problem is resolved by learners of an artificial language comprising nouns, verbs, adjectives and case markers following syntactic rules. We found that the language could be acquired through cross-situational statistical correspondences with complex scenes and without explicit feedback, and that knowledge was maintained after 24 hours. Results also showed that verbs and word order were the first to be acquired, followed by nouns, adjectives and finally case markers. Interdependencies in learning were found for word order and verbs, and also for nouns, adjectives and case markers. Grammar and vocabulary can be acquired simultaneously, but with distinctive patterns of acquisition - grammar and the role of verbs first, then the vocabulary of other lexical categories.

KW - artificial language learning

KW - grammar

KW - language acquisition

KW - statistical learning

KW - vocabulary

M3 - Conference contribution/Paper

AN - SCOPUS:85059275564

T3 - CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition

SP - 1307

EP - 1312

BT - CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society

PB - The Cognitive Science Society

T2 - 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017

Y2 - 26 July 2017 through 29 July 2017

ER -