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Brown, H. 
ORCID: 0000-0001-9404-9515, Smith, K., Samara, A. and Wonnacott, E.,
2021.
Semantic cues in language learning: an artificial language study with adult and child learners.
Language, Cognition and Neuroscience.
ISSN 2327-3798
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Abstract
Grammatical regularities may correlate with semantics; e.g., grammatical gender is often partially predictable from the noun’s semantics. We explore whether learners generalise over semantic cues, and whether extent of exposure (1 versus 4 sessions) and number of exemplars for each semantic class (type-frequency) affect this. Six-year-olds and adults were exposed to semi-artificial languages where nouns co-occurred with novel particles, with particle usage fully or partially determined by the semantics of nouns. Both adults and children generalised to novel nouns when semantic cues were fully consistent. Adults (but not children) also generalised when cues were partially consistent. Generalisation increased with exposure, however there was no evidence that increasing type-frequency (i.e. more nouns per semantic class) increased generalisation. Post-experiment interviews also suggested that successful generalisation depended on explicit awareness. These results suggest that semantic cues are particularly difficult for children to exploit during the early stages of language acquisition.
| Item Type: | Journal article | ||||||
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| Publication Title: | Language, Cognition and Neuroscience | ||||||
| Creators: | Brown, H., Smith, K., Samara, A. and Wonnacott, E. | ||||||
| Publisher: | Taylor & Francis | ||||||
| Date: | 10 November 2021 | ||||||
| ISSN: | 2327-3798 | ||||||
| Identifiers: |
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| Rights: | This is an Accepted Manuscript of an article published by Taylor & Francis in Language, Cognition and Neuroscience on 10th November 2021, available online: http://www.tandfonline.com/10.1080/23273798.2021.1995612 | ||||||
| Divisions: | Schools > School of Social Sciences | ||||||
| Record created by: | Laura Ward | ||||||
| Date Added: | 17 Nov 2021 08:53 | ||||||
| Last Modified: | 10 Nov 2022 03:00 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/44836 |
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