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Statistical learning (SL) approaches to reading maintain that proficient reading requires assimilation of rich statistical regularities in the writing system. Reading skills in developing first-language readers are predicted by individual differences in sensitivity to regularities in mappings from orthography to phonology (O-P) and semantics (O-S), where good readers rely more on O-P consistency, and less on O-S associations. However, how these regularities are leveraged by second-language (L2) learners remains an open question. We utilize an individual-differences approach, measuring L2 English learners’ sensitivity to O-P, O-S, and frequency during word-naming, across two years of immersion. We show that reliance on O-P is leveraged by better readers, while reliance on O-S is slower to develop, characterizing less proficient readers. All factors explain substantial individual variance in L2 reading skills. These findings show how SL plays a key role in L2 reading development through its role in assimilating sublexical regularities between print and speech.
Frost's critique reveals the limitations of the reverse-engineering approach to cognitive modeling – the style of psychological explanation in which a stipulated internal organization (in the form of a computational mechanism) explains a relatively narrow set of phenomena. An alternative is to view organization as both the explanation for some phenomena and a phenomenon to be explained. This move poses new and interesting theoretical challenges for theories of word reading.