Busting a myth with the Bayes Factor: Effects of letter bigram frequency in visual lexical decision do not reflect reading processes

Psycholinguistic researchers identify linguistic variables and assess if they affect cognitive processes. One such variable is letter bigram frequency, or the frequency with which a given letter pair co-occurs in an orthography. While early studies reported that bigram frequency affects visual lexical decision, subsequent, well-controlled studies not shown this effect. Still, researchers continue to use it as a control variable in psycholinguistic experiments. We propose two reasons for the persistence of this variable: (1) Reporting no significant effect of bigram frequency cannot provide evidence for no effect. (2) Despite empirical work, theoretical implications of bigram frequency are largely neglected. We perform Bayes Factor analyses to address the first issue. In analyses of existing large-scale databases, we find no effect of bigram frequency in lexical decision in the British Lexicon Project, and some evidence for an inhibitory effect in the English Lexicon Project. We find strong evidence for an effect in reading aloud. This suggests that, for lexical decision, the effect is unstable, and may depend on item characteristics and task demands rather than reflecting cognitive processes underlying visual word recognition. We call for more consideration of theoretical implications of the presence or absence of a bigram frequency effect

Variations in the use of simple and context-sensitive grapheme-phoneme correspondences in English and German developing readers

Learning to read in most alphabetic orthographies requires not only the acquisition of simple grapheme-phoneme correspondences (GPCs) but also the acquisition of context-sensitive GPCs, where surrounding letters change a grapheme’s pronunciation. We aimed to explore the use and development of simple GPCs (e.g. a ➔ /æ/) and context-sensitive GPCs (e.g. [w]a ➔ /ɔ/, as in “swan” or a[l][d] ➔ /o:/, as in “bald”) in pseudoword reading. Across three experiments, English- and German-speaking children in grades 2–4 read aloud pseudowords, where vowel graphemes had different pronunciations according to different contexts (e.g. “hact”, “wact”, “hald”). First, we found that children use context-sensitive GPCs from grade 2 onwards, even when they are not explicitly taught. Second, we used a mathematical optimisation procedure to assess whether children’s vowel responses can be described by assuming that they rely on a mix of simple and context-sensitive GPCs. While the approach works well for German adults (Schmalz et al. in Journal of Cognitive Psychology, 26, 831–852, 2014), we found poor model fits for both German- and English-speaking children. Additional analyses using an entropy measure and data from a third experiment showed that children’s pseudoword reading responses are variable and likely affected by random noise. We found a decrease in entropy across grade and reading ability across all conditions in both languages. This suggests that GPC knowledge becomes increasingly refined across grades 2–4

Rules and statistics: What if it’s both? A basic computational model of statistical learning in reading acquisition

Orthographies contain statistical regularities, such as a systematic relationship between written word forms and their pronunciations. Based on this observation, reading researchers have proposed a tight link between reading acquisition and statistical learning ability, and a statistical learning deficit as a possible cause of developmental dyslexia. The empirical evidence for a link between statistical learning ability and reading ability is weak, and no existing theoretical framework is complete enough to be implementable as a computational model. I present a basic computational model which performs a simple statistical learning task. A variable rule learning mechanism supplements the statistical learning mechanism. Simulations varying this parameter, along with an additional encoding and uncertainty parameters, show that individual differences in statistical learning performance can occur without any changes to the efficiency of the statistical learning mechanism. This explains the apparent paradox, that knowledge of statistical regularities seems to be critical for efficient reading, but that the empirical link between statistical learning ability and reading ability is tenuous

Psycholinguistics and Research Methods Webinar Series

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