Individual Differences In Statistical Learning Research Articles

Statistical learning and children's emergent literacy in rural Côte d'Ivoire.

Studies of non-linguistic statistical learning (SL) have often linked performance in SL tasks with differences in language outcomes. Most of these studies have focused on Western and high-income educational contexts, but children worldwide learn in radically different educational systems and communities, and often in a second language. In the west African nation of Côte d'Ivoire, children enter fifth grade (CM-1) with widely varying ages and literacy skills. Across three iteratively-developed experiments, 157 children, age 8-15 years, in rural communities in the greater-Adzópe region of Côte d'Ivoire watched sequences of cartoon images with embedded triplet patterns on touchscreen tablets, while performing a target-detection task. We assessed these tablet-based adaptations of non-linguistic visual SL and asked whether the children's individual differences in performance on the SL tasks were related to their first and second language and literacy skills. We found group-level evidence that children used the statistical regularities in the image sequence to gradually decrease their response times, but their responses on post-test discrimination did not reflect this learning. When evaluating the correlation between SL and language skills, individual differences related to other task demands predicted oral language skills shared by first and second languages, while SL better predicted second language print skills. These findings suggest that non-linguistic SL paradigms can measure similar skills in Ivorian children as previous samples, but they also echo recent calls for further cross-cultural validation, greater internal reliability, and tests for confounding variables (such as processing speed) in studies of individual differences in statistical learning. RESEARCH HIGHLIGHTS: We iteratively adapted three visual statistical learning studies for children in rural Côte d'Ivoire. Group-level analyses indicates that the children learn the underlying statistical regularities. Individual-differences analyses reveal some evidence that the statistical learning measure is also correlated with task demands that may be driven by cross-cultural differences. Like previous research, statistical learning is correlated with second language literacy, but we did not find a relationship between SL and oral language skills in first and second languages.

The sources and consequences of individual differences in statistical learning for language development

Statistical learning (SL)—sensitivity to statistical regularities in the environment—has been postulated to support language development. While even young infants are capable of using distributional statistics to learn in linguistic and non-linguistic domains, efforts to measure SL at the level of the individual and link it to language proficiency in individual differences designs have been mixed, which has at least in part been attributed to problems with task reliability. In the current study we present the first prospective longitudinal study of the relationship between both non-linguistic SL (measured with visual stimuli) and linguistic SL (measured with auditory stimuli) and language in a group of English-speaking children. One-hundred and twenty-one (N = 121) children in their first two years of formal schooling (Mage = 6;1 years, Range: 5;2 – 7;2) completed tests of visual SL (VSL) and auditory SL (ASL) and several control variables at time 1. Both forms of SL were then measured every 6 months for the next 18 months, and at the final testing session (time 4) their language proficiency was measured using a standardised test. The results showed that the reliability of the SL tasks increased across the course of the study. A series of path analyses showed that both VSL and ASL independently predicted individual differences in language proficiency at time 4. The evidence is consistent with the suggestion that, when measured reliably, an observable relationship between SL and language proficiency exists. Theoretical and methodological issues are discussed.

Mediating factors of statistics anxiety in university students: a systematic review and meta-analysis.

Statistics plays a key role in many areas of modern society, including technology, social and behavior studies, economics, and the sciences. Statistics anxiety (SA) has a detrimental impact on academic experiences in university populations, although the mediating factors remain underexplored. We conducted the first systematic review and meta-analysis focused on SA in university students in the context of statistical performance, individual differences in statistical learning, self-perceptions regarding the statistics course and instructor, and sociodemographic factors. Searches were carried out in the PsycINFO, PubMed, Scielo, and Web of Science databases according to our preregistration. Forty studies were selected for systematic review. Seventeen were included in a series of six meta-analyses concerning academic achievement, attitudes, self-perception, procrastination, and gender. The findings reveal learning strategies, procrastination, self-efficacy, and self-awareness as predictors of SA. However, the impact of sociodemographic data in these moderators is still uncharted. We conclude with a critical appraisal of the selected studies and present future directions for research in SA.

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

Using an individual differences approach in children with and without dyslexia, this study investigated the hypothesized relationship between statistical learning ability and literacy (reading and spelling) skills. We examined the clinical relevance of statistical learning (serial reaction time and visual statistical learning tasks) by controlling for potential confounds at the participant level (e.g., non‐verbal reasoning, attention and phonological skills including rapid automatized naming and phonological short‐term memory). A 100 Dutch‐speaking 8‐ to 11‐year‐old children with and without dyslexia participated (50 per group), see also van Witteloostuijn et al. (2019) for a study with the same participants. No evidence of a relationship between statistical learning and literacy skills is found above and beyond participant‐level variables. Suggestions from the literature that the link between statistical learning and literacy attainment, and therefore its clinical relevance, might be small and strongly influenced by methodological differences between studies are not contradicted by our findings.

Individual Differences in Verb Bias Sensitivity in Children and Adults With Developmental Language Disorder.

A number of experiments support the hypothetical utility of statistical information for language learning and processing among both children and adults. However, tasks in these studies are often very general, and only a few include populations with developmental language disorder (DLD). We wanted to determine whether a stronger relationship might be shown when the measure of statistical learning is chosen for its relevance to the language task when including a substantial number of participants with DLD. The language ability we measured was sensitivity to verb bias – the likelihood of a verb to appear with a certain argument or interpretation. A previous study showed adults with DLD were less sensitive to verb bias than their typical peers. Verb bias sensitivity had not yet been tested in children with DLD. In Study 1, 49 children, ages 7–9 years, 17 of whom were classified as having DLD, completed a task designed to measure sensitivity to verb bias through implicit and explicit measures. We found children with and without DLD showed sensitivity to verb bias in implicit but not explicit measures, with no differences between groups. In Study 2, we used a multiverse approach to investigate whether individual differences in statistical learning predicted verb bias sensitivity in these participants as well as in a dataset of adult participants. Our analysis revealed no evidence of a relationship between statistical learning and verb bias sensitivity in children, which was not unexpected given we found no group differences in Study 1. Statistical learning predicted sensitivity to verb bias as measured through explicit measures in adults, though results were not robust. These findings suggest that verb bias may still be relatively unstable in school age children, and thus may not play the same role in sentence processing in children as in adults. It would also seem that individuals with DLD may not be using the same mechanisms during processing as their typically developing (TD) peers in adulthood. Thus, statistical information may differ in relevance for language processing in individuals with and without DLD.

Do current statistical learning tasks capture stable individual differences in children? An investigation of task reliability across modality.

Do commonly used statistical-learning tasks capture stable individual differences in children? Infants, children, and adults are capable of using statistical learning (SL) to extract information about their environment. Although most studies have looked at group-level performance, a growing literature examines individual differences in SL and their relation to language-learning outcomes: Individuals who are better at SL are expected to show better linguistic abilities. Accordingly, studies have shown positive correlations between SL performance and language outcomes in both children and adults. However, these studies have often used tasks designed to explore group-level performance without modifying them, resulting in psychometric shortcomings that impact reliability in adults (Siegelman, Bogaerts, Christiansen, & Frost in Transactions of the Royal Society B, 372, 20160059, 2017a; Siegelman, Bogaerts, & Frost in Behavior Research Methods, 49, 418-432, 2017b). Even though similar measures are used to assess individual differences in children, no study to date has examined the reliability of these measures in development. This study examined the reliability of common SL measures in both children and adults. It assessed the reliability of three SL tasks (two auditory and one visual) twice (two months apart) in adults and children (mean age 8 years). Although the tasks showed moderate reliability in adults, they did not capture stable individual variation in children. None of the tasks were reliable across sessions, and all showed internal consistency measures well below psychometric standards. These findings raise significant concerns about the use of current SL measures to predict and explain individual differences in development. The article ends with a discussion of possible explanations for the difference in reliability between children and adults.

Individual differences in statistical learning predict children's reading ability in a semi-transparent orthography

Learning to read is a milestone in a child's life, and reading ability is a strong predictor of academic outcomes. Some studies have revealed that individual differences in the capacity for implicit statistical learning are linked with children's reading skills in English, which has a deep orthography, but we do not know whether the same relation is found in semi-transparent orthographies such as Norwegian. Additionally, the relative contribution of statistical learning alongside other cognitive measures known to be related to reading has not been examined. This study of sixty-five Norwegian school children (M = 10.3 years) found that performance on an independent statistical learning task predicted a small, but unique amount of variance in reading ability in Norwegian, even when a number of other reading-related cognitive skills were taken into account. This suggests that children's implicit learning of statistical regularities is associated with proficiency with written language in a semi-transparent orthography such as Norwegian.

Towards a theory of individual differences in statistical learning.

In recent years, statistical learning (SL) research has seen a growing interest in tracking individual performance in SL tasks, mainly as a predictor of linguistic abilities. We review studies from this line of research and outline three presuppositions underlying the experimental approach they employ: (i) that SL is a unified theoretical construct; (ii) that current SL tasks are interchangeable, and equally valid for assessing SL ability; and (iii) that performance in the standard forced-choice test in the task is a good proxy of SL ability. We argue that these three critical presuppositions are subject to a number of theoretical and empirical issues. First, SL shows patterns of modality- and informational-specificity, suggesting that SL cannot be treated as a unified construct. Second, different SL tasks may tap into separate sub-components of SL that are not necessarily interchangeable. Third, the commonly used forced-choice tests in most SL tasks are subject to inherent limitations and confounds. As a first step, we offer a methodological approach that explicitly spells out a potential set of different SL dimensions, allowing for better transparency in choosing a specific SL task as a predictor of a given linguistic outcome. We then offer possible methodological solutions for better tracking and measuring SL ability. Taken together, these discussions provide a novel theoretical and methodological approach for assessing individual differences in SL, with clear testable predictions.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.

Second Language Experience Facilitates Statistical Learning of Novel Linguistic Materials.

Recent research has begun to explore individual differences in statistical learning, and how those differences may be related to other cognitive abilities, particularly their effects on language learning. In this research, we explored a different type of relationship between language learning and statistical learning: the possibility that learning a new language may also influence statistical learning by changing the regularities to which learners are sensitive. We tested two groups of participants, Mandarin Learners and Naïve Controls, at two time points, 6months apart. At each time point, participants performed two different statistical learning tasks: an artificial tonal language statistical learning task and a visual statistical learning task. Only the Mandarin-learning group showed significant improvement on the linguistic task, whereas both groups improved equally on the visual task. These results support the view that there are multiple influences on statistical learning. Domain-relevant experiences may affect the regularities that learners can discover when presented with novel stimuli.

Measuring individual differences in statistical learning: Current pitfalls and possible solutions

Most research in statistical learning (SL) has focused on the mean success rates of participants in detecting statistical contingencies at a group level. In recent years, however, researchers have shown increased interest in individual abilities in SL, either to predict other cognitive capacities or as a tool for understanding the mechanism underlying SL. Most if not all of this research enterprise has employed SL tasks that were originally designed for group-level studies. We argue that from an individual difference perspective, such tasks are psychometrically weak, and sometimes even flawed. In particular, the existing SL tasks have three major shortcomings: (1) the number of trials in the test phase is often too small (or, there is extensive repetition of the same targets throughout the test); (2) a large proportion of the sample performs at chance level, so that most of the data points reflect noise; and (3) the test items following familiarization are all of the same type and an identical level of difficulty. These factors lead to high measurement error, inevitably resulting in low reliability, and thereby doubtful validity. Here we present a novel method specifically designed for the measurement of individual differences in visual SL. The novel task we offer displays substantially superior psychometric properties. We report data regarding the reliability of the task and discuss the importance of the implementation of such tasks in future research.

Individual Differences in Statistical Learning: Conceptual and Measurement Issues

The ability to adapt to statistical structure (often referred to as “statistical learning”) has been proposed to play a major role in the acquisition and use of natural languages. Several recent studies have explored the relationship between individual differences in statistical learning and language outcomes. These studies have produced mixed results, with some studies finding a significant relationship between statistical learning and language outcomes, and others finding weak or null results. Furthermore, the few studies that have used multiple measures of statistical learning have reported that they are not correlated (e.g., [1]). The current study assesses the reliability of various measures of auditory statistical segmentation, and their consistency over time. That is, do the generally low correlations observed between measures of statistical learning stem from task demands, the psychometric properties of the measures, or the fact that statistical learning may be a highly fragmented construct? Our results confirm previous reports that individual measures of statistical learning tend not to correlate with each other, and suggest that the somewhat weak reliability of the measures may be an important factor in the low correlations. Our data also suggest that aggregating performance across tasks may be an avenue for improving the reliability of the measures.

Perceptual context and individual differences in the language proficiency of preschool children

Although the contribution of perceptual processes to language skills during infancy is well recognized, the role of perception in linguistic processing beyond infancy is not well understood. In the experiments reported here, we asked whether manipulating the perceptual context in which stimuli are presented across trials influences how preschool children perform visual (shape–size identification; Experiment 1) and auditory (syllable identification; Experiment 2) tasks. Another goal was to determine whether the sensitivity to perceptual context can explain part of the variance in oral language skills in typically developing preschool children. Perceptual context was manipulated by changing the relative frequency with which target visual (Experiment 1) and auditory (Experiment 2) stimuli were presented in arrays of fixed size, and identification of the target stimuli was tested. Oral language skills were assessed using vocabulary, word definition, and phonological awareness tasks. Changes in perceptual context influenced the performance of the majority of children on both identification tasks. Sensitivity to perceptual context accounted for 7% to 15% of the variance in language scores. We suggest that context effects are an outcome of a statistical learning process. Therefore, the current findings demonstrate that statistical learning can facilitate both visual and auditory identification processes in preschool children. Furthermore, consistent with previous findings in infants and in older children and adults, individual differences in statistical learning were found to be associated with individual differences in language skills of preschool children.

Individual Differences in Statistical Learning Predict Children's Comprehension of Syntax.

Variability in children's language acquisition is likely due to a number of cognitive and social variables. The current study investigated whether individual differences in statistical learning (SL), which has been implicated in language acquisition, independently predicted 6- to 8-year-old's comprehension of syntax. Sixty-eight (N = 68) English-speaking children completed a test of comprehension of four syntactic structures, a test of SL utilizing nonlinguistic visual stimuli, and several additional control measures. The results revealed that SL independently predicted comprehension of two syntactic structures that show considerable variability in this age range: passives and object relative clauses. These data suggest that individual differences in children's capacity for SL are associated with the acquisition of the syntax of natural languages.

Statistical learning as an individual ability: Theoretical perspectives and empirical evidence.

Although the power of statistical learning (SL) in explaining a wide range of linguistic functions is gaining increasing support, relatively little research has focused on this theoretical construct from the perspective of individual differences. However, to be able to reliably link individual differences in a given ability such as language learning to individual differences in SL, three critical theoretical questions should be posed: Is SL a componential or unified ability? Is it nested within other general cognitive abilities? Is it a stable capacity of an individual? Following an initial mapping sentence outlining the possible dimensions of SL, we employed a battery of SL tasks in the visual and auditory modalities, using verbal and non-verbal stimuli, with adjacent and non-adjacent contingencies. SL tasks were administered along with general cognitive tasks in a within-subject design at two time points to explore our theoretical questions. We found that SL, as measured by some tasks, is a stable and reliable capacity of an individual. Moreover, we found SL to be independent of general cognitive abilities such as intelligence or working memory. However, SL is not a unified capacity, so that individual sensitivity to conditional probabilities is not uniform across modalities and stimuli.

Statistical Learning is Related to Early Literacy-Related Skills.

It has been demonstrated that statistical learning, or the ability to use statistical information to learn the structure of one's environment, plays a role in young children's acquisition of linguistic knowledge. Although most research on statistical learning has focused on language acquisition processes, such as the segmentation of words from fluent speech and the learning of syntactic structure, some recent studies have explored the extent to which individual differences in statistical learning are related to literacy-relevant knowledge and skills. The present study extends on this literature by investigating the relations between two measures of statistical learning and multiple measures of skills that are critical to the development of literacy-oral language, vocabulary knowledge, and phonological processing-within a single model. Our sample included a total of 553 typically developing children from prekindergarten through second grade. Structural equation modeling revealed that statistical learning accounted for a unique portion of the variance in these literacy-related skills. Practical implications for instruction and assessment are discussed.

On-line individual differences in statistical learning predict language processing

Considerable individual differences in language ability exist among normally developing children and adults. Whereas past research have attributed such differences to variations in verbal working memory or experience with language, we test the hypothesis that individual differences in statistical learning may be associated with differential language performance. We employ a novel paradigm for studying statistical learning on-line, combining a serial-reaction time task with artificial grammar learning. This task offers insights into both the timecourse of and individual differences in statistical learning. Experiment 1 charts the micro-level trajectory for statistical learning of nonadjacent dependencies and provides an on-line index of individual differences therein. In Experiment 2, these differences are then shown to predict variations in participants’ on-line processing of long-distance dependencies involving center-embedded relative clauses. The findings suggest that individual differences in the ability to learn from experience through statistical learning may contribute to variations in linguistic performance.