An analysis of reading skill development using E-Z Reader

Abstract

Previously reported simulations using the E-Z Reader model of eye-movement control suggest that the patterns of eye movements observed with children versus adult readers reflect differences in lexical processing proficiency (Reichle et al., 2013). However, these simulations fail to specify precisely what aspect(s) of lexical processing (e.g., orthographic processing) account for the concurrent changes in eye movements and reading skill. To examine this issue, the E-Z Reader model was first used to simulate the aggregate eye-movement data from 15 adults and 75 children to replicate the finding that gross differences in reading skill can be accounted for by differences in lexical processing proficiency. The model was then used to simulate the eye-movement data of individual children so that the best-fitting lexical-processing parameters could be correlated to measures of orthographic knowledge, phonological-processing skill, sentence comprehension, and general intelligence. These analyses suggest that orthographic knowledge accounts for variance in the eye-movement measures that is observed with between-individual differences in reading skill. The theoretical implications of this conclusion will be discussed in relation to computational models of reading and our understanding of reading skill development.

Using support vector machines to identify literacy skills: Evidence from eye movements

“…These results and the results of recent simulation studies suggest that language skills are related to individual differences in eye movement behavior (Reichle, et al, 2013). This suggestion is further supported by the computational models of eye movement control, which posit that lexical processing and post-lexical language processing can affect eye movements during reading (Inhoff, Greenberg, Solomon, & Wang, 2009;Pollatsek, Juhasz, Reichle, Machacek, & Rayner, 2008;Reichle, Warren, & McConnell, 2009), as well as predict that reading skill development is reflected in certain aspects of eye movement behavior (Mancheva, et al, 2015;Reichle et al, 2013;Reichle & Sheridan, 2015). Thus, eye movement data can be used to predict literacy level.…”

What is the most plausible account of the role of parafoveal processing in reading?

“…This interpretation is consistent with systematic simulations of the E‐Z Reader model which showed that eye‐movement differences between children and adults could not be simulated by changing parameters directly related to eye‐movement control. However, virtually, all of the developmental differences in both English (Reichle et al, ) and French readers (Mancheva et al, ) were accurately simulated by modifying a single parameter determining the rate of lexical processing. Individual differences in orthographic knowledge were also better predictors of eye‐movement data than measures of sentence processing or general intelligence (Mancheva et al, ), consistent with the view that lexical quality plays a critical role in online reading.…”

An Analysis of the Time Course of Lexical Processing During Reading

“…Both these changes were motivated by Simulation 1, which showed that the model's default parameters tended to under-predict the degree to which word frequency modulated the first-of-multiple fixation durations. These changes were also motivated-as indicated in our earlier exposition of the E-Z Reader model-by a considerable amount of previous work showing that the values of these parameters appear to be related to differences in reading ability and text materials (Mancheva et al, 2015;Rayner et al, 2006;; see also, e.g., Miellet, Sparrow, & Sereno, 2007). And it is also worth emphasizing that neither parameter adjustment weakens the model's core assumption that attention is allocated in a strictly serial manner-that assumption is completely determined by the model's architecture (i.e., how information and control of processing is passed between the L 1 , L 2 , and A components in Fig.…”

“…Similarly, to simulate the eye movements of elderly readers, the values of a 1 and a 2 were increased to (respectively) slow lexical processing and increase the degree to which it is modulated by word frequency (Rayner, Reichle, Stroud, Williams, & Pollatsek, 2006). And most recently, the values of a 1 have been shown to correlate with between-individual variability in both eye movements and psychometric measures of orthographic knowledge of a large sample of children (Mancheva et al, 2015).…”