Artificial Language Learning in Children

IF 3 1区 文学 0 LANGUAGE & LINGUISTICS Annual Review of Linguistics Pub Date : 2019-01-16 DOI:10.1146/ANNUREV-LINGUISTICS-011718-012329
J. Culbertson, Kathryn D. Schuler
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引用次数: 16

Abstract

Artificial language learning methods—in which learners are taught miniature constructed languages in a controlled laboratory setting—have become a valuable experimental tool for research on language development. These methods offer a complement to natural language acquisition data, allowing researchers to control both the input to learning and the learning environment. A large proportion of artificial language learning studies has aimed to understand the mechanisms of learning in infants. This review focuses instead on investigations into the nature of early linguistic representations and how they are influenced by both the structure of the input and the cognitive features of the learner. Looking not only at young infants but also at children beyond infancy, we discuss evidence for early abstraction, conditions on generalization, the acquisition of grammatical categories and dependencies, and recent work connecting the cognitive biases of learners to language typology. We end by outlining important areas for future research.
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儿童人工语言学习
人工语言学习方法——学习者在受控的实验室环境中学习微型构建的语言——已经成为语言发展研究的一种有价值的实验工具。这些方法为自然语言习得数据提供了补充,使研究人员能够控制学习的输入和学习环境。人工语言学习研究的很大一部分旨在了解婴儿的学习机制。这篇综述的重点是研究早期语言表征的本质,以及它们如何受到输入结构和学习者认知特征的影响。我们不仅关注幼儿,也关注婴儿期以后的儿童,讨论了早期抽象的证据、泛化条件、语法类别和依赖关系的习得,以及最近将学习者的认知偏见与语言类型学联系起来的研究。最后,我们概述了未来研究的重要领域。
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来源期刊
CiteScore
7.20
自引率
6.20%
发文量
37
期刊介绍: The Annual Review of Linguistics, in publication since 2015, covers significant developments in the field of linguistics, including phonetics, phonology, morphology, syntax, semantics, pragmatics, and their interfaces. Reviews synthesize advances in linguistic theory, sociolinguistics, psycholinguistics, neurolinguistics, language change, biology and evolution of language, typology, as well as applications of linguistics in many domains.
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