The Science of Reading. Группа авторов. Читать онлайн. Newlib. NEWLIB.NET

Автор: Группа авторов
Издательство: John Wiley & Sons Limited
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Жанр произведения: Языкознание
Год издания: 0
isbn: 9781119705130
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can reproduce the phenomena the theory is meant to explain. This method has been widely embraced as an advance over the informal models of the “box‐and‐arrow” era in which the dual‐route approach originated (Seidenberg, 1988).

Schematic illustration of theory development and evaluation using computational models.

      With the benefit of 30‐some years of hindsight we can ask: Did computational models of reading yield the expected benefits? Did they indeed provide a basis for assessing competing theories? Did they yield new theoretical insights? In short, given the promise of the approach and several decades of modeling research, what have we learned?

      Like many others, we think that computational modeling proved to be an invaluable tool in both methodological and theoretical respects. Taken as a method for testing theories, attempts to implement models based on the dual‐route theory revealed apparently intractable limitations of the approach. Researchers were unable to implement models that reproduced basic behavioral phenomena concerning the pronunciation of regular and irregular words and nonwords that the dual‐route theory was developed to explain.

Categories of Words in Dual‐Route Theory
Regular/Rule‐governed Irregular/Exception
MUST CHAIR DIME BOAT HAVE DONE SAID PINT
Exceptions = words whose pronunciations are not correctly generated by rules.
Glushko Inconsistent Words
Regular but Inconsistent
SAVE (have) BONE (done) PAID (said) MINT (pint)
These words are rule‐governed according to dual‐route model, but they have one or more irregular neighbors (in parentheses).
Connectionist/Statistical Learning Approach
Degrees of Spelling‐Sound Consistency:
Low High
Strange words Exceptions Reg Inconsistent Regular
Words and nonwords exhibit varying degrees of spelling‐sound consistency. Regular, exception and inconsistent words occupy positions on this continuum, along with other intermediate cases. “Strange” words are oddballs like COLONEL and SPHINX. Locations on the continuum are approximate.

      It took many years of research within both approaches to arrive at these conclusions. Over time, successors to the DRC model discarded defining features of the approach in favor of networks incorporating distributed representations trained via weight‐adjusting learning procedures, the connectionist approach (e.g., Perry et al., 2007; Ziegler et al., 2014). This development reflects broader trends in cognitive science and neuroscience. Core PDP/connectionist ideas about distributed representations, quasiregularity, statistical learning, constraint satisfaction processing, and division of labor between components of the language system have been widely absorbed and continue to inform research (e.g., Chang et al., 2020; Chen et al., 2017; Gordon & Dell, 2003; Hoffman et al., 2015; Smith et al., 2021). This framework has proved particularly relevant to understanding the brain bases of reading, language, and visual cognition because the grain of the models is well matched to the grain of the data obtained using current neuroimaging methods (Cox et al., 2015). The computational models retain their relevance to understanding cognition and its brain bases even though they are simpler than deep learning networks that perform far more complex tasks, but are much harder to analyze and less closely tied to human experience (Joanisse & McClelland, 2015).

      We then examine “connectionist dual‐route models” (Perry et al., 2007, 2010; Ziegler et al., 2014). These hybrid models incorporate the major assumptions of the “triangle” framework but differ in one respect: They retain a second, lexical route. However, the phenomena this mechanism is intended to explain are explained in connectionist models that incorporate additional parts of the orthography➔phonology➔semantics triangle. The “lexical route” allows the authors to claim a degree of continuity with dual‐route models, but it is not required to explain any data. We close by considering the relevance of computational modeling for understanding how children learn to read. The dual‐route theory remains influential in areas where computational modeling results are not well known. These include reading acquisition and instruction, where research and pedagogy still focus on learning pronunciation rules and adding sight words to the lexicon, and in some areas of cognitive neuroscience (e.g., Bouhali et al., 2019). Modeling established the inadequacy of the