LAUSR

Automaticity in word recognition has been hypothesized to be important in reading development (LaBerge & Samuels, 1974; Perfetti, 1985). However, when predicting educational outcomes, it is difficult to isolate the influence of automatic word recognition from factors such as processing speed or knowledge of grapheme-phoneme correspondences. Cognitive models suggest automaticity could be achieved in different components of word recognition (e.g., by memorizing familiar words or by tuning the mappings between orthography, phonology or semantics). However, the contributions of each path have not been assessed. This study developed a new measure of automaticity to overcome these limitations and relates automaticity to standard outcomes. Subjects were 58 middle-school students (mean age = 13.2 years ± 8 months) with average to below-average reading comprehension. To assess automaticity with an accuracy-based measure, backward masking was used: On half the trials, items were presented for 90 ms and replaced by a nonlinguistic mask; on the other half it was presented unmasked to assess children’s knowledge of the word. This was instantiated in 3 experimental tasks developed to maximize reliance on different reading mappings. Automaticity, particularly in a task stressing meaning, predicted reading fluency over and above knowledge of the relevant grapheme-phoneme mappings. Automaticity in tasks involving nonwords also predicted fluency, suggesting the possibility of automaticity in orthography to phonology mappings. Variation in automatic word recognition did not predict reading comprehension or decoding. This link between automatic written word recognition and fluency has important implications for how automaticity may be targeted to improve reading outcomes.