scholarly journals The contribution of individual differences in statistical learning to reading and spelling performance in children with and without dyslexia

Dyslexia ◽  
2021 ◽  
Author(s):  
Merel Witteloostuijn ◽  
Paul Boersma ◽  
Frank Wijnen ◽  
Judith Rispens
Keyword(s):  
Individual Differences ◽  
Statistical Learning ◽  
Spelling Performance ◽  
Reading And Spelling

An Exploration of Individual Differences in Statistical Learning

2014 ◽  
Author(s):  
Lucy C. Erickson ◽  
Michael Kaschak ◽  
Erik D. Thiessen ◽  
Cassie Berry
Keyword(s):  
Individual Differences ◽  
Statistical Learning

Normal Variation in Reading Acquisition

1986 ◽  
Vol 62 (3) ◽  
pp. 691-716 ◽  
Author(s):  
Virginia Wise Berninger
Keyword(s):  
Individual Differences ◽  
Reading Instruction ◽  
Cognitive Skills ◽  
Verbal Ability ◽  
First Grade ◽  
Normal Variation ◽  
Word Decoding ◽  
Linguistic Skills ◽  
Whole Word ◽  
Reading And Spelling

Visual, linguistic, reading, and spelling tests were administered to the same 45 children at the end of kindergarten and of first grade. Normal variation, i.e., diversity not related to pathology, was found in the visual and linguistic skills and was shown to be related to reading and spelling achievement for a sample of suburban children of similar socioeconomic status. Individual differences in three visual skills—selective attention to letter information (RT), memory for a component letter (accuracy), and memory for a whole word (accuracy)—and two linguistic skills—phonemic analysis and vocabulary understanding—were reliable over the first year of formal reading instruction and had concurrent validity in that they were correlated with achievement in word decoding/encoding at the end of kindergarten and of first grade. Of these five skills, phonemic analysis accounted for more variance in achievement (52% to 64%, depending upon achievement measure) than any other single skill. Significantly mote variance in achievement was accounted for when both a visual skill (memory for a sequence) and a linguistic skill (phonemic analysis) were considered than when either alone was at end of first grade. The predictive validity of quantitatively defined “disabilities” (at or more than a standard deviation below the mean) was investigated; disabilities in both visual and linguistic skills at the end of kindergarten were associated with low achievement in word decoding/encoding at the end of first grade. Two pairs of identical twin girls (each co-twin taught by a different teacher) were not mote congruent on several achievement measures than two pairs of unrelated girls, taught by the same teacher and matched to each other and a twin pair on verbal ability and age. Normal variation in acquisition of word decoding/encoding probably results from an interaction between genetic individual differences in cognitive skills and the processes of assimilation and accommodation during environmental transactions proposed by Piaget.

scholarly journals Information-theoretic Modeling of Perceived Musical Complexity

2019 ◽  
Vol 37 (2) ◽  
pp. 165-178
Author(s):  
Sarah A. Sauvé ◽  
Marcus T. Pearce
Keyword(s):  
Individual Differences ◽  
Computational Model ◽  
Information Content ◽  
Statistical Learning ◽  
Probabilistic Prediction ◽  
Information Theoretic ◽  
Musical Background ◽  
Musical Excerpts ◽  
Definition Of ◽  
Perceived Complexity

What makes a piece of music appear complex to a listener? This research extends previous work by Eerola (2016), examining information content generated by a computational model of auditory expectation (IDyOM) based on statistical learning and probabilistic prediction as an empirical definition of perceived musical complexity. We systematically manipulated the melody, rhythm, and harmony of short polyphonic musical excerpts using the model to ensure that these manipulations systematically varied information content in the intended direction. Complexity ratings collected from 28 participants were found to positively correlate most strongly with melodic and harmonic information content, which corresponded to descriptive musical features such as the proportion of out-of-key notes and tonal ambiguity. When individual differences were considered, these explained more variance than the manipulated predictors. Musical background was not a significant predictor of complexity ratings. The results support information content, as implemented by IDyOM, as an information-theoretic measure of complexity as well as extending IDyOM's range of applications to perceived complexity.

scholarly journals What drives individual differences in statistical learning? The role of perceptual fluency and familiarity

2018 ◽  
Author(s):  
Amy Perfors ◽  
Evan Kidd
Keyword(s):  
Individual Differences ◽  
Statistical Learning ◽  
Learning Task ◽  
Perceptual Fluency ◽  
Learning Performance ◽  
Visual Modality ◽  
Learning Skills ◽  
Domain Specific ◽  
Different Levels

Humans have the ability to learn surprisingly complicated statistical information in a variety of modalities and situations, often based on relatively little input. These statistical learning (SL) skills appear to underlie many kinds of learning, but despite their ubiquity, we still do not fully understand precisely what SL is and what individual differences on SL tasks reflect. Here we present experimental work suggesting that at least some individual differences arise from variation in perceptual fluency — the ability to rapidly or efficiently code and remember the stimuli that statistical learning occurs over. We show that performance on a standard SL task varies substantially within the same (visual) modality as a function of whether the stimuli involved are familiar or not, independent of stimulus complexity. Moreover, we find that test-retest correlations of performance in a statistical learning task using stimuli of the same level of familiarity (but distinct items) are stronger than correlations across the same task with different levels of familiarity. Finally, we demonstrate that statistical learning performance is predicted by an independent measure of stimulus-specific perceptual fluency which contains no statistical learning component at all. Our results suggest that a key component of SL performance may be unrelated to either domain-specific statistical learning skills or modality-specific perceptual processing.

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