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From Klingon to Colbertian: Using Artificial Languages to Study Word Learning

Published online by Cambridge University Press:  18 October 2019

Sayuri Hayakawa ,
Siqi Ning  and
Viorica Marian
Sayuri Hayakawa*
Affiliation:
Northwestern University
Siqi Ning
Affiliation:
Northwestern University
Viorica Marian
Affiliation:
Northwestern University
*
Address for correspondence: Dr. Sayuri Hayakawa, Email: [email protected]
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Abstract

Vocabulary acquisition is a critical part of learning a new language. Yet, due to structural, historical, and individual variability associated with natural languages, isolating the impact of specific factors on word learning can be challenging. Artificial languages are versatile tools for addressing this problem, allowing researchers to systematically manipulate properties of the language and control for learners’ past experiences. Here, we review how artificial languages have been used to study bilingual word learning, with a particular focus on the influences of language input (e.g., word properties) and language experience (e.g., bilingualism). We additionally discuss the advantages and limitations of artificial languages for bilingual research and suggest resources for researchers considering the use of artificial languages. Used and interpreted properly, artificial language studies can inform our understanding of a wide range of factors relevant to word learning.

Keywords

artificial languagesword learningvocabulary acquisitionbilingualism
Type
Review Article
Information
Bilingualism: Language and Cognition , Volume 23 , Issue 1 , January 2020 , pp. 74 - 80
Copyright
Copyright © Cambridge University Press 2019 

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