Do children learn from their prediction mistakes? A registered report evaluating error-based theories of language acquisition



Fazekas, Judit, Jessop, Andrew, Pine, Julian ORCID: 0000-0002-7077-9713 and Rowland, Caroline
(2020) Do children learn from their prediction mistakes? A registered report evaluating error-based theories of language acquisition. Royal Society Open Science, 7 (11).

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Abstract

Error-based theories of language acquisition suggest that children, like adults, continuously make and evaluate predictions in order to reach an adult-like state of language use. However, while these theories have become extremely influential, their central claim—that unpredictable input leads to higher rates of lasting change in linguistic representations—has scarcely been tested. We designed a prime surprisal-based intervention study to assess this claim. As predicted, both 5- to 6-year-old children (n = 72) and adults (n = 72) showed a pre- to post-test shift towards producing the dative syntactic structure they were exposed to in surprising sentences. The effect was significant in both age groups together, and in the child group separately when participants with ceiling performance in the pre-test were excluded. Secondary predictions were not upheld: we found no verb-based learning effects and there was only reliable evidence for immediate prime surprisal effects in the adult, but not in the child group. To our knowledge, this is the first published study demonstrating enhanced learning rates for the same syntactic structure when it appeared in surprising as opposed to predictable contexts, thus providing crucial support for error-based theories of language acquisition.

Item Type: Article
Uncontrolled Keywords: Error-based learning, Language acquisition, Prediction
Depositing User: Symplectic Admin
Date Deposited: 20 Jan 2021 08:56
Last Modified: 09 Oct 2021 01:13
DOI: 10.1098/rsos.180877
Open Access URL: https://royalsocietypublishing.org/doi/10.1098/rso...
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URI: https://livrepository.liverpool.ac.uk/id/eprint/3114210

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