2020
DOI: 10.1017/s0305000920000264
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Starting Big: The Effect of Unit Size on Language Learning in Children and Adults

Abstract: Multiword units play an important role in language learning and use. It was proposed that learning from such units can facilitate mastery of certain grammatical relations, and that children and adults differ in their use of multiword units during learning, contributing to their varying language-learning trajectories. Accordingly, adults learn gender agreement better when encouraged to learn from multiword units. Previous work has not examined two core predictions of this proposal: (1) that children also benefi… Show more

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Cited by 14 publications
(9 citation statements)
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“…In these cases, the predictive relation between the grammatical element and the object it modifies is strong enough, and does not need the boost that comes from being initially part of the same unit. These predictions have been supported in a series of artificial language learning studies: children and adults show better learning of gender agreement when exposed to unsegmented input first compared to segmented input first: Importantly, the facilitation is driven by an increased reliance on multiword units (Arnon & Ramscar, 2012; Siegelman & Arnon, 2015; Havron & Arnon, 2020). This facilitative effect was also found when English-speakers were taught a Chinese classifier system (Paul & Grüter, 2016).…”
Section: The Impact Of Multiword Units On Learning: Some Core Predictionsmentioning
confidence: 85%
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“…In these cases, the predictive relation between the grammatical element and the object it modifies is strong enough, and does not need the boost that comes from being initially part of the same unit. These predictions have been supported in a series of artificial language learning studies: children and adults show better learning of gender agreement when exposed to unsegmented input first compared to segmented input first: Importantly, the facilitation is driven by an increased reliance on multiword units (Arnon & Ramscar, 2012; Siegelman & Arnon, 2015; Havron & Arnon, 2020). This facilitative effect was also found when English-speakers were taught a Chinese classifier system (Paul & Grüter, 2016).…”
Section: The Impact Of Multiword Units On Learning: Some Core Predictionsmentioning
confidence: 85%
“…In line with this, literacy impacts the degree to which learners extract multiword units from novel speech: literate adults show increased reliance on word units compared to illiterate adults (Havron & Arnon, 2016), as do literate children compared to pre-literate ones (Havron & Arnon, 2017). Literacy also impacts learning biases in the expected direction: pre-literate children showed better learning of article-noun agreement patterns compared to mastery of individual nouns, while literate children and adults showed the opposite pattern (Havron, Raviv & Arnon, 2018; Havron & Arnon, 2020). That is, literacy contributes to a reduced reliance on multiword units in learning a novel language.…”
Section: The Impact Of Multiword Units On Learning: Some Core Predictionsmentioning
confidence: 99%
“…Recently, a set of studies has taken code-mixing onto usage-based grounds suggesting that fixed chunks and frame-and-slot patterns that have been shown to play a major role in monolingual acquisition can also account for children's code-mixing. Lexically fixed patterns make execution faster and less effortful because they are uttered without close monitoring (e.g., Havron and Arnon, 2021 ). On this view, code-mixing is suggested to be constructed around frame-and-slot patterns with the frame activated in one language and the open slot being filled with elements from the other language, e.g., [ that's my __ ] + Bademantel “bathing gown” → that's my Bademantel (Fion, 03;11.16).…”
Section: Theoretical Preliminaries and Main Hypothesesmentioning
confidence: 99%
“…Of course, word associations and other lexical-level factors are not the only force affecting lexical processing; n-gram (or chunk) frequency is also a major factor (Lorenz and Tizón-Couto, 2019;Supasiraprapa, 2019). Usage-based approaches posit that the comprehender does not access, concatenate, or integrate the component words of highfrequency n-grams but rather retrieves chunks of varying sizes holistically (Blumenthal-Dramé, 2017;Ambridge, 2020;Havron and Arnon, 2021). Further, higher n-gram frequency correlates with greater speed and accuracy in comprehension, production, and acquisition regardless of other lexical-level factors, and this effect is consistently found in self-paced reading paradigms (McConnell and Blumenthal-Dramé, 2019).…”
Section: Bigram Pairingmentioning
confidence: 99%