Non-linear development in statistical learning of visual orthographic regularities
Abstract Statistical learning is a core ability for individuals in extracting and integrating regularities and patterns from linguistic input. Yet, the developmental trajectory of visual statistical learning has not been fully examined in the orthographic learning domain. Employing an artificial ort...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | npj Science of Learning |
| Online Access: | https://doi.org/10.1038/s41539-025-00298-2 |
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| Summary: | Abstract Statistical learning is a core ability for individuals in extracting and integrating regularities and patterns from linguistic input. Yet, the developmental trajectory of visual statistical learning has not been fully examined in the orthographic learning domain. Employing an artificial orthographic learning task, we manipulated three levels of positional consistency of radicals, i.e., high (100%), moderate (80%), and low (60%), embedded in pseudocharacters to investigate visual statistical learning across a wide age range between 4–12-year-olds and adults. The non-linear power-function models indicated that the rates of improvement in acquiring varying positional consistencies increased with age, particularly for high and moderate levels. Specifically, we observed a significant enhancement in statistical learning abilities between the ages of 4–5 years and 5–6 years, followed by a stabilization of performance after 8–9 years. Our findings support the age-dependent perspective that individuals’ visual statistical learning ability improves significantly in early childhood and then decelerates its improvement progressively until adulthood. |
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| ISSN: | 2056-7936 |