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Learning morphology from cross-situational statistics

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Learning morphology from cross-situational statistics. / Zhu, Liuqi; Rebuschat, Patrick; Nixon, Jessie S. et al.
In: Studies in Second Language Acquisition, 08.09.2025, p. 1-27.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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APA

Zhu, L., Rebuschat, P., Nixon, J. S., & Monaghan, P. (2025). Learning morphology from cross-situational statistics. Studies in Second Language Acquisition, 1-27. Advance online publication. https://doi.org/10.1017/s027226312510106x

Vancouver

Zhu L, Rebuschat P, Nixon JS, Monaghan P. Learning morphology from cross-situational statistics. Studies in Second Language Acquisition. 2025 Sept 8;1-27. Epub 2025 Sept 8. doi: 10.1017/s027226312510106x

Author

Zhu, Liuqi ; Rebuschat, Patrick ; Nixon, Jessie S. et al. / Learning morphology from cross-situational statistics. In: Studies in Second Language Acquisition. 2025 ; pp. 1-27.

Bibtex

@article{b58f9f5e2cf147a7a3b8deb9a9581d4c,
title = "Learning morphology from cross-situational statistics",
abstract = "Non-native languages tend to be acquired through a combination of explicit and implicit learning, where implicit learning requires coordination of language information with referents in the environment. In this study, we examined how learners use both language input and environmental cues to acquire vocabulary and morphology in a novel language and how their language background influences this process. We trained 105 adults with native languages (L1s) varying in morphological richness (English, German, Mandarin) on an artificial language comprising nouns and verbs with morphological features (number, tense, and subject-verb [SV] agreement) appearing alongside referential visual scenes. Participants were able to learn both word stems and morphological features from cross-situational statistical correspondences between language and the environment, without any instruction. German-speakers learned SV agreement worse than other morphological features, which were acquired equally effectively by English or Mandarin speakers, indicating the subtle and varied influence of L1 morphological richness on implicit non-native language learning.",
keywords = "bottleneck hypothesis, statistical learning, cross-linguistic influence, morphology, cross-situational learning",
author = "Liuqi Zhu and Patrick Rebuschat and Nixon, {Jessie S.} and Padraic Monaghan",
year = "2025",
month = sep,
day = "8",
doi = "10.1017/s027226312510106x",
language = "English",
pages = "1--27",
journal = "Studies in Second Language Acquisition",
issn = "0272-2631",
publisher = "Cambridge University Press",

}

RIS

TY - JOUR

T1 - Learning morphology from cross-situational statistics

AU - Zhu, Liuqi

AU - Rebuschat, Patrick

AU - Nixon, Jessie S.

AU - Monaghan, Padraic

PY - 2025/9/8

Y1 - 2025/9/8

N2 - Non-native languages tend to be acquired through a combination of explicit and implicit learning, where implicit learning requires coordination of language information with referents in the environment. In this study, we examined how learners use both language input and environmental cues to acquire vocabulary and morphology in a novel language and how their language background influences this process. We trained 105 adults with native languages (L1s) varying in morphological richness (English, German, Mandarin) on an artificial language comprising nouns and verbs with morphological features (number, tense, and subject-verb [SV] agreement) appearing alongside referential visual scenes. Participants were able to learn both word stems and morphological features from cross-situational statistical correspondences between language and the environment, without any instruction. German-speakers learned SV agreement worse than other morphological features, which were acquired equally effectively by English or Mandarin speakers, indicating the subtle and varied influence of L1 morphological richness on implicit non-native language learning.

AB - Non-native languages tend to be acquired through a combination of explicit and implicit learning, where implicit learning requires coordination of language information with referents in the environment. In this study, we examined how learners use both language input and environmental cues to acquire vocabulary and morphology in a novel language and how their language background influences this process. We trained 105 adults with native languages (L1s) varying in morphological richness (English, German, Mandarin) on an artificial language comprising nouns and verbs with morphological features (number, tense, and subject-verb [SV] agreement) appearing alongside referential visual scenes. Participants were able to learn both word stems and morphological features from cross-situational statistical correspondences between language and the environment, without any instruction. German-speakers learned SV agreement worse than other morphological features, which were acquired equally effectively by English or Mandarin speakers, indicating the subtle and varied influence of L1 morphological richness on implicit non-native language learning.

KW - bottleneck hypothesis

KW - statistical learning

KW - cross-linguistic influence

KW - morphology

KW - cross-situational learning

U2 - 10.1017/s027226312510106x

DO - 10.1017/s027226312510106x

M3 - Journal article

SP - 1

EP - 27

JO - Studies in Second Language Acquisition

JF - Studies in Second Language Acquisition

SN - 0272-2631

ER -