Individual Differences in Leveraging Regularity in Emergent L2 Readers in Rural Côte d’Ivoire

Abstract

Purpose: Statistical learning (SL) approaches to reading maintain that proficient reading requires assimilation of the rich statistical regularities in the writing system. Reading skills in developing first- and second-language readers in English have been shown to be predicted by individual differences in sensitivity to statistical regularities in orthography and semantics, with good readers relying more on orthographic consistency, and less on semantic associations. However, the study of SL and its relation to reading has been primarily studied in English readers in WEIRD countries, limiting the universality of our theories. Method: We examine individual differences in sensitivity to regularities utilising a word naming task in emergent French readers in rural communities in Côte d’Ivoire (N=134). Results: We show that, in contrast to previous studies, in our cohort better readers leverage semantic associations more strongly, while individual differences in sensitivity to orthographic consistency did not predict reading skill. Relatively little variance in reading skill was explained by sensitivity to these regularities. Conclusion: This showcases the importance of cross-linguistic and cross-cultural research to back up universal theories of literacy, and suggests that current SL accounts of reading must be updated to account for this variance in reading skills.

Is a Phone‐Based Language and Literacy Assessment a Reliable and Valid Measure of Children's Reading Skills in Low‐Resource Settings?

“…We specifically avoided using a picture‐based vocabulary task, as images can often be strongly culturally‐bound and therefore inappropriate for rural Ivorian context. Notably, all in‐person measures were previously implemented in Côte d'Ivoire to assess the language and literacy skills of children in this age range (see Akpé et al, 2021; Ball et al, 2022; Brice et al, 2023; Jasińska, Akpe, et al, 2022; Jasińska, Zinszer, et al, 2022; Whitehead et al, 2023; Zinszer et al, 2023a, 2023b).…”