scholarly journals Reading as Statistical Learning

2018 ◽  
Vol 49 (3S) ◽  
pp. 634-643 ◽  
Author(s):  
Joanne Arciuli

Purpose The purpose of this tutorial is to explain how learning to read can be thought of as learning statistical regularities and to demonstrate why this is relevant for theory, modeling, and practice. This tutorial also shows how triangulation of methods and cross-linguistic research can be used to gain insight. Method The impossibility of conveying explicitly all of the regularities that children need to acquire in a deep orthography, such as English, can be demonstrated by examining lesser-known probabilistic orthographic cues to lexical stress. Detection of these kinds of cues likely occurs via a type of implicit learning known as statistical learning (SL). The first part of the tutorial focuses on these points. Next, studies exploring how individual differences in the capacity for SL relate to variability in word reading accuracy in the general population are discussed. A brief overview of research linking impaired SL and dyslexia is also provided. The final part of the tutorial focuses on how we might supplement explicit literacy instruction with implicit learning methods and emphasizes the value of testing the efficacy of new techniques in the classroom. The basic and applied research reviewed here includes corpus analyses, behavioral testing, computational modeling, and classroom-based research. Although some of these methods are not commonly used in clinical research, the depth and breadth of this body of work provide a compelling case for why reading can be thought of as SL and how this view can inform practice. Conclusion Implicit methods that draw on the principles of SL can supplement the much-needed explicit instruction that helps children learn to read. This synergy of methods has the potential to spark innovative practices in literacy instruction and remediation provided by educators and clinicians to support typical learners and those with developmental disabilities.

2020 ◽  
Author(s):  
Stephen Charles Van Hedger ◽  
Ingrid Johnsrude ◽  
Laura Batterink

Listeners are adept at extracting regularities from the environment, a process known as statistical learning (SL). SL has been generally assumed to be a form of “context-free” learning that occurs independently of prior knowledge, and SL experiments typically involve exposing participants to presumed novel regularities, such as repeating nonsense words. However, recent work has called this assumption into question, demonstrating that learners’ previous language experience can considerably influence SL performance. In the present experiment, we tested whether previous knowledge also shapes SL in a non-linguistic domain, using a paradigm that involves extracting regularities over tone sequences. Participants learned novel tone sequences, which consisted of pitch intervals not typically found in Western music. For one group of participants, the tone sequences used artificial, computerized instrument sounds. For the other group, the same tone sequences used familiar instrument sounds (piano or violin). Knowledge of the statistical regularities was assessed using both trained sounds (measuring specific learning) and sounds that differed in pitch range and/or instrument (measuring transfer learning). In a follow-up experiment, two additional testing sessions were administered to gauge retention of learning (one day and approximately one-week post-training). Compared to artificial instruments, training on sequences played by familiar instruments resulted in reduced correlations among test items, reflecting more idiosyncratic performance. Across all three testing sessions, learning of novel regularities presented with familiar instruments was worse compared to unfamiliar instruments, suggesting that prior exposure to music produced by familiar instruments interfered with new sequence learning. Overall, these results demonstrate that real-world experience influences SL in a non-linguistic domain, supporting the view that SL involves the continuous updating of existing representations, rather than the establishment of entirely novel ones.


1997 ◽  
Vol 20 (1) ◽  
pp. 82-82 ◽  
Author(s):  
A. Vinter ◽  
P. Perruchet

Clark & Thornton's conception finds an echo in implicit learning research, which shows that subjects may perform adaptively in complex structured situations through the use of simple statistical learning mechanisms. However, the authors fail to draw a distinction between, on the one hand, subjects' representations which emerge from type-1 learning mechanisms, and, on the other, their knowledge of the genuine abstract “recoding function” which defines a type-2 problem.


2008 ◽  
Vol 19 (12) ◽  
pp. 1247-1252 ◽  
Author(s):  
Jill Lany ◽  
Rebecca L. Gómez

A decade of research suggests that infants readily detect patterns in their environment, but it is unclear how such learning changes with experience. We tested how prior experience influences sensitivity to statistical regularities in an artificial language. Although 12-month-old infants learn adjacent relationships between word categories, they do not track nonadjacent relationships until 15 months. We asked whether 12-month-old infants could generalize experience with adjacent dependencies to nonadjacent ones. Infants were familiarized to an artificial language either containing or lacking adjacent dependencies between word categories and were subsequently habituated to novel nonadjacent dependencies. Prior experience with adjacent dependencies resulted in enhanced learning of the nonadjacent dependencies. Female infants showed better discrimination than males did, which is consistent with earlier reported sex differences in verbal memory capacity. The findings suggest that prior experience can bootstrap infants' learning of difficult language structure and that learning mechanisms are powerfully affected by experience.


2020 ◽  
Vol 90 (4) ◽  
pp. 459-498
Author(s):  
Kelly Puzio ◽  
Glenn T. Colby ◽  
Dana Algeo-Nichols

With increasingly diverse students, schools and districts are under pressure to meet rigorous standards and raise student achievement in reading and literacy. Most teachers respond by differentiating their instruction to some extent, but not all scholars and educators agree on whether differentiated instruction works. This systematic review and meta-analysis seeks to determine the effects of Tier 1 differentiation, which is provided by the general education classroom teacher, on literacy outcomes. Distinguishing between designed differentiation and interactional differentiation, the authors provide multiple examples of content, process, and product differentiation in the context of literacy instruction. Reviewing more than 20 years of literacy research, the authors located 18 studies with 25 study cohorts. Outcomes include fluency, decoding, letter-word reading, vocabulary, comprehension, and writing achievement. The overall weighted mean effect size (g) was +0.13 (p = .002) with 88% of the individual point estimates being positive. Overall, the findings indicate that differentiated literacy instruction is an effective evidence-based practice at the elementary level. When teachers are supported to differentiate instruction, students have significantly higher literacy achievement scores, particularly for letter-word (g = +0.20, p = .014) and writing outcomes (g = +0.96, p < .001). The most successful programs took very different approaches to differentiation, including individualization, choice, and an alternate curriculum. However, across the studies, there was an alarming lack of information about the decision-making processes used to guide differentiation and there were no experimental or quasi-experimental studies on guided reading. This review may be helpful as schools clarify their vision for literacy differentiation.


Author(s):  
Jiaqiang Zhu ◽  
Xiaoxiang Chen ◽  
Fei Chen ◽  
Seth Wiener

Purpose: Individuals with congenital amusia exhibit degraded speech perception. This study examined whether adult Chinese Mandarin listeners with amusia were still able to extract the statistical regularities of Mandarin speech sounds, despite their degraded speech perception. Method: Using the gating paradigm with monosyllabic syllable–tone words, we tested 19 Mandarin-speaking amusics and 19 musically intact controls. Listeners heard increasingly longer fragments of the acoustic signal across eight duration-blocked gates. The stimuli varied in syllable token frequency and syllable–tone co-occurrence probability. The correct syllable–tone word, correct syllable-only, correct tone-only, and correct syllable–incorrect tone responses were compared respectively between the two groups using mixed-effects models. Results: Amusics were less accurate than controls in terms of the correct word, correct syllable-only, and correct tone-only responses. Amusics, however, showed consistent patterns of top-down processing, as indicated by more accurate responses to high-frequency syllables, high-probability tones, and tone errors all in manners similar to those of the control listeners. Conclusions: Amusics are able to learn syllable and tone statistical regularities from the language input. This extends previous work by showing that amusics can track phonological segment and pitch cues despite their degraded speech perception. The observed speech deficits in amusics are therefore not due to an abnormal statistical learning mechanism. These results support rehabilitation programs aimed at improving amusics' sensitivity to pitch.


Author(s):  
Dirk van Moorselaar ◽  
Jan Theeuwes

AbstractIncreasing evidence demonstrates that observers can learn the likely location of salient singleton distractors during visual search. To date, the reduced attentional capture at high-probability distractor locations has typically been examined using so called compound search, in which by design a target is always present. Here, we explored whether statistical distractor learning can also be observed in a visual detection task, in which participants respond target present if the singleton target is present and respond target absent when the singleton target is absent. If so, this allows us to examine suppression of the location that is likely to contain a distractor both in the presence, but critically also in the absence, of a priority signal generated by the target singleton. In an online variant of the additional singleton paradigm, observers had to indicate whether a unique shape was present or absent, while ignoring a colored singleton, which appeared with a higher probability in one specific location. We show that attentional capture was reduced, but not absent, at high-probability distractor locations, irrespective of whether the display contained a target or not. By contrast, target processing at the high-probability distractor location was selectively impaired on distractor-present displays. Moreover, all suppressive effects were characterized by a gradient such that suppression scaled with the distance to the high-probability distractor location. We conclude that statistical distractor learning can be examined in visual detection tasks, and discuss the implications for attentional suppression due to statistical learning.


2006 ◽  
Vol 10 (5) ◽  
pp. 233-238 ◽  
Author(s):  
Pierre Perruchet ◽  
Sebastien Pacton

Sign in / Sign up

Export Citation Format

Share Document