Does the Relation between Rapid Automatized Naming and Reading Depend on Age or on Reading Level? A Behavioral and ERP Study

Abstract

Reading predictors evolve through age: phonological awareness is the best predictor of reading abilities at the beginning of reading acquisition while Rapid Automatized Naming (RAN) becomes the best reading predictor in more experienced readers (around 9–10 years old). Those developmental changes in the relationship between RAN and reading have so far been explained in term of participants' age. However, it should be noted that in the previous experiments age always co-vary with participants reading level. It is thus not clear whether RAN-reading relationship is developmental in nature or related to the reading system itself. This study investigates whether the behavioral changes in the relationship between RAN and reading and their electrophysiological correlates are related to the chronological age or to the reading level of the participants. Thirty two French-speaking children aged 7–10 years took part to the experiment: they were divided into groups contrasted on age but with similar reading levels and the other way round. Participants performed two reading tasks and four RAN tasks. EEG/ERP was recorded during discrete letter and picture RAN. Behavioral results revealed that alphanumeric RAN is more sensitive to age variations than reading level differences. The inverse profile was revealed for picture RAN, which discriminate poor and good readers among typically developed children within the same age-group. ERPs of both letter and picture RAN differed across age groups whereas only for the picture RAN ERPs differed across reading levels. Taken together, these results suggest that picture RAN is a particularly good indicator of reading level variance independently of age.

Validity Evidence of the Reading Screening Test for Portuguese First Graders

“…Slow performance on RAN tasks is associated with poor reading performance (Denkla and Rudel, 1976;Lúcio et al, 2017;Katzir et al, 2018;Landerl et al, 2019). Several studies confirm that RAN has a strong correlation with reading competence, with a progressively more relevant role throughout the school path (Cohen et al, 2018). This impact is especially strong on reading fluency (Araújo et al, 2015;Papadopoulos et al, 2016;Carvalho et al, 2017).…”

An Exploration of the Rapid Automatic Naming Test as Administered to Brazilian Children

“…In a study conducted by Koponen et al [58], it was found that RAN performance could predict other skills beyond the calcu-lation of reading fluency. In a longitudinal study conducted by Landerl and Wimmer [59], it was found that RAN is the most sensitive instrument for predicting fluency and spelling, in addition to the time of exposure to reading, in the case of letter naming [19].…”

“…The studies indicated that children without reading difficulties name letters and numbers more quickly than colors and objects and that the latter subtests require greater use of attentional and perceptual processes, a greater semantic load, and increased time for motor production (articulation). Some studies suggest that differences in naming objects and letters can differentiate between good and bad readers, particularly since the former generates a more effective lexical access than the latter as it requires lexical-phonological access [5,6,[18][19][20][21][22][23][24]. These data reinforce RAN's validity as they demonstrate its relationship with reading in cognitive and clinical processing.…”

Rapid Automatized Picture Naming as a Proficiency Assessment for Endangered Language Contexts: Results from Wilamowice

“…Although studies like these have been oft reproduced, the validity of naming speed as an indicator of reading abilities remains debated, especially in terms of the details of stimuli and presentation. More recently, however, a neuro-imaging study provides evidence in support of discrete RAN tests (one stimulus at a time) with image stimuli as an indicator of reading abilities, discriminating both poor and above-average readers from average readers (Cohen et al 2018).…”