The role of translation equivalents in bilingual word learning

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Abstract/Contents

Abstract
Bilingual environments present an interesting context for word learning, notably due to the existence of translation equivalents (TEs)—words in different languages that share very similar meanings. Understanding how these TEs are learnt may give us insight into mechanisms underlying word learning in young children. In Study 1, we investigated this by conducting a systematic literature review and meta-analysis of TEs in children's vocabularies, finding significant variability with age as a moderator. In Study 2, we then conducted an analysis of Communicative Development Inventory (CDI) data from bilingual children, finding that older children and children with more balanced language exposure had a higher proportion of TE pairs in their vocabularies. However, both of these approaches were susceptible to the baseline problem—the potential confound of overall vocabulary growth (which would lead to a greater set of opportunities for learning TEs). Hence, in Study 3, we moved to an item-level analysis, finding that knowing a word's TE increased the likelihood of knowing that word itself for younger children, and for TEs that are more similar phonologically. Thus, TEs provide an alternative source of information for younger children, thereby allowing bilingual children to bootstrap their word learning in one language using their knowledge of the other language.

Description

Type of resource text
Date modified December 5, 2022
Publication date July 22, 2022

Creators/Contributors

Author Tan, Alvin W. M. ORCiD icon https://orcid.org/0000-0001-5551-7507 (unverified)
Thesis advisor Frank, Michael C.
Thesis advisor Marchman, Virginia A.

Subjects

Subject Bilingualism in children
Subject Learning
Subject Language acquisition
Genre Text
Genre Thesis

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Preferred citation
Tan, A. (2022). The role of translation equivalents in bilingual word learning. Stanford Digital Repository. Available at https://purl.stanford.edu/ks986rr0159

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Master's Theses, Symbolic Systems Program, Stanford University

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