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The Science of Reading


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      So, what is orthographic processing? I argue that orthographic processing is best defined as the processing of letter identities and letter positions. This definition of orthographic processing, and the hypothesized fundamental role it plays during reading, is based on the premise that written words are primarily recognized via their component letters.

      Historically, the “word shape” hypothesis (i.e., words are recognized holistically rather than via their component letters) was once dominant in theories of word recognition and reading – a mistaken view that had a major influence on educational practice for the better part of the twentieth century. The popularity of this hypothesis was founded in Cattell’s (1886) observation that words are read aloud more easily than single letters (the “word superiority effect”), which lead to the following reasoning: How can we possibly read words via their constituent letters if it is harder to read individual letters than to read words? The solution to this conundrum was provided by theoretical advances (e.g., McClelland & Rumelhart, 1981) showing how a word can be identified from the combination of partial information available at the level of each of its constituent letters (see Grainger, 2018, for further discussion of the word superiority effect and its interpretation).

      Although there is some evidence that word shape information might influence skilled word reading in certain situations (e.g., Perea & Rosa, 2002; Perea et al., 2015), there is abundant evidence that skilled readers use information about abstract letter identities to identify words, along with information about letter positions. Together, letter identity and letter position comprise orthographic information. We know from experiments using masked repetition priming (Forster & Davis, 1984) that letter identities are abstract: The processing of word targets is not affected by whether or not the prime word is presented in the same case or different case (e.g., TABLETABLE vs. tableTABLE, Grainger & Jacobs, 1993; Perea et al., 2014; Vergara‐Martinez et al., 2015). Likewise, although overt reading is handicapped by mixed case presentation (e.g., tAbLE), an effect that is probably due to the perceptual grouping of same‐case letters (Mayall et al., 1997), mixed‐case primes are just as effective as same case primes (Perea et al., 2015). Another example here is our ability to read CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) – those highly distorted words we are asked to read when an internet site is checking whether we are a human or a robot. Hannagan et al. (2012) demonstrated masked repetition priming effects using CAPTCHA primes. This demonstrates that our ability to solve even extreme cases of shape distortion is achieved automatically, without resort to slow inferential processes (for an analogous finding with handwritten words, see Gil‐López et al., 2011).

      Having reviewed the evidence for letter‐based word recognition, we now need to understand how letters are identified and their positions encoded during reading.

       Letter perception

Schematic illustration of adaptation of Riesenhuber and Poggio’s model of object identification to the case of letter perception.

      Grainger et al., 2008/With permission of Elsevier.

       Identifying letters in letter strings

      The preceding section examined the identification of letters in isolation, but the vast majority of written words are composed of more than one letter. We move now to consider the factors that govern the processing of letter identities in letter strings under conditions that minimize any higher‐level phonological, morphological, or lexical influences.