Valdois-Roulin-2019

• Visual attention span reflects visual attention capacity for simultaneous processing.

• Pre-readers’ visual attention span predicts reading fluency at the end of Grade 1.

• Visual attention uniquely contributes to word, pseudo-word and text reading.

• A conceptual model of the role of visual attention in learning to read is proposed.

The processing of letters within strings is challenging for beginning readers. Letter identification is affected by visual similarity, loss of information with eccentricity and interference from nearby letters. In contrast, visual attention enhances letter identification. We here explored whether visual attention resources for multi-element processing, as measured through tasks of visual attention span prior to literacy instruction, predicted reading fluency performance one year later. One hundred and twenty-four mainstream children were assessed in kindergarten on their visual attention span abilities, phonological awareness, letter-name knowledge, early literacy knowledge, verbal short-term memory and non-verbal IQ. The participants’ reading performance was measured at the end of grade 1 using tasks of irregular word, pseudo-word and text reading. Results from regression analyses showed that kindergarteners’ VA span predicted reading fluency for text, irregular words and pseudo-words one year later, after controlling for age, non-verbal IQ, phonological skills, letter name knowledge and early literacy skills. Path analyses carried out to estimate the differential contribution of VA span to the different reading skills revealed a stronger contribution for pseudo-word reading than irregular word or text reading at the end of Grade 1. These results suggest that pre-reading visual attention resources contribute to later reading fluency, whatever the reading subskills and whatever the reading context (words in isolation or in sentences), with higher involvement to pseudo-word reading. We propose a new conceptual model of the role of visual attention in reading acquisition and argue that many aspects of the models are already supported by available findings.