Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills

Abstract

Statistical views of literacy development maintain that proficient reading requires the assimilation of myriad statistical regularities present in the writing system. Indeed, previous studies have tied statistical learning (SL) abilities to reading skills, establishing the existence of a link between the two. However, some issues are currently left unanswered, including questions regarding the underlying bases for these associations as well as the types of statistical regularities actually assimilated by developing readers. Here we present an alternative approach to study the role of SL in literacy development, focusing on individual differences among beginning readers. Instead of using an artificial task to estimate SL abilities, our approach identifies individual differences in children's reliance on statistical regularities as reflected by actual reading behavior. We specifically focus on individuals' reliance on regularities in the mapping between print and speech versus associations between print and meaning in a word naming task. We present data from 399 children, showing that those whose oral naming performance is impacted more by print-speech regularities and less by associations between print and meaning have better reading skills. These findings suggest that a key route by which SL mechanisms impact developing reading abilities is via their role in the assimilation of sub-lexical regularities between printed and spoken language -and more generally, in detecting regularities that are more reliable than others. We discuss the implications of our findings to both SL and reading theories.

Keywords: Individual differences; Print-speech regularities; Reading acquisition; Statistical learning.

Figure 1.

Significant interactions in the group-level analysis of Study 1. Left panel: greater impact of frequency in higher levels of surprisal (i.e. when O-P regularities are less consistent). Right panel: greater impact of frequency in higher levels of imageability. Plots created using the interact_plot() function in interactions package in R (Long, 2019).

Figure 2.

Variability among participants in Study 1 in sensitivity to imageability (y-axis) and O-P regularities (x-axis). Vertical and horizontal dashed lines show mean sensitivity to O-P regularity and imageability, respectively. Dashed trend line show correlation between the two slope measures. Color scale presents raw scores on Letter-Word Identification task.

Figure 3.

RD diagnosis (in color) as a function of sensitivity to imageability (y-axis) and O-P regularity (x-axis).

Figure 4

Variability among participants in Study 2 in sensitivity to imageability (y-axis) and O-P regularities (x-axis). Vertical and horizontal dashed lines show mean sensitivity to O-P regularity and imageability, respectively. Dashed trend line show correlation between the two slope measures. Color scale presents raw score on Letter-Word Identification task.

Figure 5

Variability among participants across the two studies in sensitivity to imageability (y-axis) and O-P regularities (x-axis). Vertical and horizontal dashed lines show mean sensitivity to O-P regularity and imageability, respectively. Dashed trend line show correlation between the two slope measures. Color scale presents raw score on Letter-Word Identification task.

Figure 6

GAM results based on the aggregated data (n=399). Panel A: Estimated effects of the smoothed terms of sensitivity to imageability and O-P regularity on (residualized) Letter-Word Identification (left) and Word Attack (right) scores. Panel B: Predicted scores in Letter-Word Identification (left) and Word Attack (right) as a function of sensitivity to O-P regularity (x-axis) and imageability (y-axis).