Training Reading Speed and Naming Speed
The software designed to improve reading speed targets a core issue for children with reading difficulties who are acquiring a relatively transparent orthography: the automation of word recognition. The program aims to increase students’ reading speed by masking the reading material—ranging from frequent orthographic patterns, prefixes and suffixes, and morphemes to words, sentences, and texts—syllable by syllable or word by word, at a rate adapted to the student’s initially assessed individual reading speed. If the student successfully manages the practice material at the current speed, the rate at which the material is masked is gradually increased.
By masking the reading material syllable by syllable or word by word, the program seeks to motivate students with reading difficulties to move away from decoding words letter by letter (phonological recoding) and instead direct their attention toward larger orthographic units (syllables, words), processing them holistically and simultaneously. In doing so, it supports students with reading difficulties in transitioning from the alphabetic strategy of phonological recoding to an orthographic reading strategy.
Naming speed—or “rapid automatized naming” (RAN)—is considered the most stable predictor of the automation of word recognition (and thus reading speed) across different orthographies. Naming speed is defined as the ability to “visually process and identify a sequence of simultaneously visible, familiar images or symbols (e.g., letters, numbers, colors) as quickly as possible, to activate the corresponding phonological representations in the mental lexicon […], and to articulate the corresponding word (or sound)” (Mayer, 2021, p. 99).
The development was carried out under the expert leadership of Prof. Dr. Andreas Mayer, LMU Munich (Chair of Speech-Language Pathology/Special Education with a focus on language and speech therapy). The programs are now available for commercial purchase. More information and download of the programs: LMU München
