Rapid Automatised Naming (RAN) is one of the strongest predictors of decoding abilities across orthographies and developmental conditions. In contrast to early attempts, recent studies suggest that intervention targeting RAN can improve reading decoding in children with Developmental Dyslexia or typical reading development. Nevertheless, a few studies verified the effectiveness of a RAN-based interventions on reading decoding in beginning readers within school settings, and the cognitive processes underlying their efficacy remain unclear. The present study aimed to test the effectiveness of a school-based RAN intervention on reading decoding in primary school children and contextually to measure the changes in visual search and lexical access. A class-randomised study was conducted with 71 primary second and third grade children. The intervention consisted of two 15-minutes sessions per week, conducted in pairs, over a period of 4 weeks. A school-adapted version (RANsc) of the App RANt (https://www.anastasis.it/run-the-ran/) was used. The results showed a significant improvement in the experimental group, compared to a control group that followed the school activities as usual, in RAN fluency, visual search fluency, reading fluency, and lexical access. Furthermore, although changes in RAN performance from pre-to post-training significantly correlated with gains in both visual search fluency and lexical access, only the improvements in RAN predicted the inter-subject variability in the reading fluency gains. These findings support the efficacy of gamified RAN exercises in enhancing decoding skills in primary school children, and confirm that RAN training provides added value to reading fluency beyond the contributions of isolated visual or verbal components.

Empowering reading decoding through training rapid automatised naming (RAN) in primary school: insights on methods and underpinning processes / Viola Margheri, Andrea Frascari, Giulia Baiocchini, Denise Scalambra, Chiara Tambaro & Chiara Pecini. - In: READING & WRITING. - ISSN 0922-4777. - ELETTRONICO. - (2025), pp. 0-0.

Empowering reading decoding through training rapid automatised naming (RAN) in primary school: insights on methods and underpinning processes

Viola Margheri;Chiara Pecini
2025

Abstract

Rapid Automatised Naming (RAN) is one of the strongest predictors of decoding abilities across orthographies and developmental conditions. In contrast to early attempts, recent studies suggest that intervention targeting RAN can improve reading decoding in children with Developmental Dyslexia or typical reading development. Nevertheless, a few studies verified the effectiveness of a RAN-based interventions on reading decoding in beginning readers within school settings, and the cognitive processes underlying their efficacy remain unclear. The present study aimed to test the effectiveness of a school-based RAN intervention on reading decoding in primary school children and contextually to measure the changes in visual search and lexical access. A class-randomised study was conducted with 71 primary second and third grade children. The intervention consisted of two 15-minutes sessions per week, conducted in pairs, over a period of 4 weeks. A school-adapted version (RANsc) of the App RANt (https://www.anastasis.it/run-the-ran/) was used. The results showed a significant improvement in the experimental group, compared to a control group that followed the school activities as usual, in RAN fluency, visual search fluency, reading fluency, and lexical access. Furthermore, although changes in RAN performance from pre-to post-training significantly correlated with gains in both visual search fluency and lexical access, only the improvements in RAN predicted the inter-subject variability in the reading fluency gains. These findings support the efficacy of gamified RAN exercises in enhancing decoding skills in primary school children, and confirm that RAN training provides added value to reading fluency beyond the contributions of isolated visual or verbal components.
2025
0
0
Viola Margheri, Andrea Frascari, Giulia Baiocchini, Denise Scalambra, Chiara Tambaro & Chiara Pecini
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1441083
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