scholarly journals Is Statistical Learning Ability Related to Reading Ability, and If So, Why?

2019 ◽  
Author(s):  
Xenia Schmalz ◽  
Kristina Moll ◽  
Claudio Mulatti ◽  
Gerd Schulte-Körne
Keyword(s):  
Statistical Learning ◽  
Developmental Dyslexia ◽  
Reading Ability ◽  
Empirical Support ◽  
Reading Acquisition ◽  
Bayes Factors ◽  
Learning Ability ◽  
Reading Tests ◽  
Causal Mechanisms ◽  
Potential Mediator

Previous studies found a relationship between performance on statistical learning (SL) tasks and reading ability and developmental dyslexia. Thus, it has been suggested that the ability to implicitly learn patterns may be important for reading acquisition. Causal mechanisms behind this relationship are unclear: Although orthographic sensitivity to letter bigrams may emerge through SL and facilitate reading, there is no empirical support for this link. We test 84 adults on two SL tasks, reading tests, and a bigram sensitivity task. We test for correlations using Bayes factors. This serves to test the prediction that SL and reading ability are correlated and to explore sensitivity to bigram legality as a potential mediator. We find no correlations between SL tasks and reading ability, SL and bigram sensitivity, or between the SL tasks. We conclude that correlating SL with reading ability may not yield replicable results, partly due to low correlations between SL tasks.

scholarly journals Developmental Dyslexia, Reading Acquisition, and Statistical Learning: A Sceptic’s Guide

2021 ◽  
Vol 11 (9) ◽  
pp. 1143
Author(s):  
Xenia Schmalz ◽  
Barbara Treccani ◽  
Claudio Mulatti
Keyword(s):  
Statistical Learning ◽  
Developmental Dyslexia ◽  
Individual Variation ◽  
Reading Ability ◽  
Causal Chain ◽  
Learning Ability ◽  
Learning Skills ◽  
Low Level ◽  
Underlying Processes ◽  
Theoretical Issues

Many theories have been put forward that propose that developmental dyslexia is caused by low-level neural, cognitive, or perceptual deficits. For example, statistical learning is a cognitive mechanism that allows the learner to detect a probabilistic pattern in a stream of stimuli and to generalise the knowledge of this pattern to similar stimuli. The link between statistical learning and reading ability is indirect, with intermediate skills, such as knowledge of frequently co-occurring letters, likely being causally dependent on statistical learning skills and, in turn, causing individual variation in reading ability. We discuss theoretical issues regarding what a link between statistical learning and reading ability actually means and review the evidence for such a deficit. We then describe and simulate the “noisy chain hypothesis”, where each intermediary link between a proposed cause and the end-state of reading ability reduces the correlation coefficient between the low-level deficit and the end-state outcome of reading. We draw the following conclusions: (1) Empirically, there is evidence for a correlation between statistical learning ability and reading ability, but there is no evidence to suggest that this relationship is causal, (2) theoretically, focussing on a complete causal chain between a distal cause and developmental dyslexia, rather than the two endpoints of the distal cause and reading ability only, is necessary for understanding the underlying processes, (3) statistically, the indirect nature of the link between statistical learning and reading ability means that the magnitude of the correlation is diluted by other influencing variables, yielding most studies to date underpowered, and (4) practically, it is unclear what can be gained from invoking the concept of statistical learning in teaching children to read.

scholarly journals Developmental dyslexia, reading acquisition, and statistical learning: A skeptic’s guide

2021 ◽  
Author(s):  
Xenia Schmalz ◽  
Barbara Treccani ◽  
Claudio Mulatti
Keyword(s):  
Statistical Learning ◽  
Developmental Dyslexia ◽  
Individual Variation ◽  
Reading Ability ◽  
Causal Chain ◽  
Learning Ability ◽  
Learning Skills ◽  
Low Level ◽  
Underlying Processes ◽  
Theoretical Issues

Many theories have been put forward that propose that developmental dyslexia is caused by low-level neural, cognitive or perceptual deficits. For example, statistical learning is a cognitive mechanism which allows the learner to detect a probabilistic pattern in a stream of stimuli, and to generalise the knowledge of this pattern to similar stimuli. The link between statistical learning and reading ability is indirect, with intermediate skills, such as knowledge of frequently co-occurring letters, likely being causally dependent on statistical learning skills and, in turn, causing individual variation in reading ability. We discuss theoretical issues regarding what a link between statistical learning and reading ability actually means, and review the evidence for such a deficit. We then describe and simulate the “Noisy Chain Hypothesis”, where each intermediary link between a proposed cause and the end-state of reading ability reduces the correlation coefficient between the low-level deficit and the end-state outcome of reading. We draw the following conclusions: (1) Empirically, there is evidence for a correlation between statistical learning ability and reading ability, but there is no evidence to suggest that this relationship is causal, (2) theoretically, focusing on a complete causal chain between a distal cause and developmental dyslexia, rather than the two end points of the distal cause and reading ability only, is necessary for understanding the underlying processes, (3) statistically, the indirect nature of the link between statistical learning and reading ability means that the magnitude of the correlation is diluted by other influencing variables, yielding most studies to date underpowered, and (4) practically, it is unclear what can be gained from invoking the concept of statistical learning in teaching children to read.

scholarly journals Is Statistical Learning Ability Related to Reading Ability, and If So, Why?

2018 ◽  
Vol 23 (1) ◽  
pp. 64-76 ◽  
Author(s):  
Xenia Schmalz ◽  
Kristina Moll ◽  
Claudio Mulatti ◽  
Gerd Schulte-Körne
Keyword(s):  
Statistical Learning ◽  
Reading Ability ◽  
Learning Ability

scholarly journals Reduced Visual Magnocellular Event-Related Potentials in Developmental Dyslexia

2021 ◽  
Vol 11 (1) ◽  
pp. 48
Author(s):  
John Stein
Keyword(s):  
Steady State ◽  
Developmental Dyslexia ◽  
Reading Ability ◽  
Event Related Potentials ◽  
Black And White ◽  
Reverse Pattern ◽  
Related Potentials ◽  
The Right ◽  
Visual Hemifields ◽  
Electroencephalogram Eeg

(1) Background—the magnocellular hypothesis proposes that impaired development of the visual timing systems in the brain that are mediated by magnocellular (M-) neurons is a major cause of dyslexia. Their function can now be assessed quite easily by analysing averaged visually evoked event-related potentials (VERPs) in the electroencephalogram (EEG). Such analysis might provide a useful, objective biomarker for diagnosing developmental dyslexia. (2) Methods—in adult dyslexics and normally reading controls, we recorded steady state VERPs, and their frequency content was computed using the fast Fourier transform. The visual stimulus was a black and white checker board whose checks reversed contrast every 100 ms. M- cells respond to this stimulus mainly at 10 Hz, whereas parvocells (P-) do so at 5 Hz. Left and right visual hemifields were stimulated separately in some subjects to see if there were latency differences between the M- inputs to the right vs. left hemispheres, and these were compared with the subjects’ handedness. (3) Results—Controls demonstrated a larger 10 Hz than 5 Hz fundamental peak in the spectra, whereas the dyslexics showed the reverse pattern. The ratio of subjects’ 10/5 Hz amplitudes predicted their reading ability. The latency of the 10 Hz peak was shorter during left than during right hemifield stimulation, and shorter in controls than in dyslexics. The latter correlated weakly with their handedness. (4) Conclusion—Steady state visual ERPs may conveniently be used to identify developmental dyslexia. However, due to the limited numbers of subjects in each sub-study, these results need confirmation.

scholarly journals Statistics in the Service of Science: Don't let the Tail Wag the Dog

2021 ◽  
Author(s):  
Henrik Singmann ◽  
Gregory Edward Cox ◽  
David Kellen ◽  
Suyog Chandramouli ◽  
Clintin Davis-Stober ◽  
...  
Keyword(s):  
Statistical Modeling ◽  
Statistical Models ◽  
Mixed Models ◽  
Model Comparison ◽  
Bayes Factors ◽  
Causal Mechanisms ◽  
Science Models ◽  
Scientific Goal ◽  
Coordination Function

Statistical modeling is generally meant to describe patterns in data in service of the broader scientific goal of developing theories to explain those patterns. Statistical models support meaningful inferences when models are built so as to align parameters of the model with potential causal mechanisms and how they manifest in data. When statistical models are instead based on assumptions chosen by default, Attempts to draw inferences can be uninformative or even paradoxical—in essence, the tail is trying to wag the dog.These issues are illustrated by van Doorn et al. (in press) in the context of using BayesFactors to identify effects and interactions in linear mixed models. We show that the problems identified in their applications can be circumvented by using priors over inherently meaningful units instead of default priors on standardized scales. This case study illustrates how researchers must directly engage with a number of substantive issues in order to support meaningful inferences, of which we highlight two: The first is the problem of coordination, which requires a researcher to specify how the theoretical constructs postulated by a model are functionally related to observable variables. The second is the problem of generalization, which requires a researcher to consider how a model may represent theoretical constructs shared across similar but non-identical situations, along with the fact that model comparison metrics like Bayes Factors do not directly address this form of generalization. For statistical modeling to serve the goals of science, models cannot be based on default assumptions, but should instead be based on an understanding of their coordination function and on how they represent causal mechanisms that may be expected to generalize to other related scenarios.

scholarly journals Effect of a Canine-Assisted Read Aloud Intervention on Reading Ability and Physiological Response: A Pilot Study

Animals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 474 ◽  
Author(s):  
Suk-Chun Fung
Keyword(s):  
Reading Fluency ◽  
Reading Ability ◽  
Preliminary Evidence ◽  
Third Graders ◽  
Read Aloud ◽  
Future Research ◽  
Reading Tests ◽  
Post Test ◽  
Character Reading ◽  
Grade 3

The aim of this study was to determine whether there is an increase in the reading fluency and accuracy of three lower performing third-graders after participating in a canine-assisted read-aloud program, as well as an increase in the relaxation level during and after the program. This study employed a pre-test-post-test design to test the hypotheses that gains would be made in both reading fluency and reading accuracy upon completion of the program. The three grade 3 students were assessed by the Chinese Character Reading Test and the Reading Fluency Test. During the intervention, they read to a trained canine in the presence of a handler. Three days after the completion of the seven 20-min interventions, the participants were assessed by the two standardized reading tests a second time. Heart rate variability (HRV) responses to the pre-test, the intervention and the post-test were recorded. The three grade 3 students attained a higher level of relaxation while reading to the dog and increased their reading fluency after the reading sessions. These results provided preliminary evidence that the canine-assisted read-aloud program can increase the reading performance of children with lower performance. Implications for future research and reading programs will be discussed.

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