Statistical Learning, Implicit Learning, and First Language Acquisition: A Critical Evaluation of Two Developmental Predictions

Abstract

The role of distributional information in language learning, and learning more generally, has been studied extensively in both the statistical learning and the implicit learning literatures. Despite the similarity in research questions, the two literatures have remained largely separate. Here, we draw on findings from the two traditions to critically evaluate two developmental predictions that are central to both. The first is the question of age invariance: Does learning improve during development or is it fully developed in infancy? The combined findings suggest that both implicit and statistical learning improve during childhood, contra the age invariance prediction. This raises questions about the role of implicit statistical learning (ISL) in explaining the age‐related deterioration in language learning: Children's better language learning abilities cannot be attributed to their improved distributional learning skills. The second issue we examine is the predictive relation to language outcomes: Does variation in learning predict variation in language outcomes? While there is evidence for such links, there is concern in both research traditions about the reliability of the tasks used with children. We present data suggesting that commonly used statistical learning measures may not capture stable individual differences in children, undermining their utility for assessing the link to language outcomes in developmental samples. The evaluation of both predictions highlights the empirical parallels between the implicit and statistical learning literatures, and the need to better integrate their developmental investigation. We go on to discuss several of the open challenges facing the study of ISL during development.

Grammatical performance in children with dyslexia: the contributions of individual differences in phonological memory and statistical learning

“…Recently, the reliability of statistical learning measures has been questioned, especially in child participants (e.g., Arnon, 2019a;West et al, 2017). Therefore, current statistical learning measures may not be suitable to examine the hypothesized relationship with linguistic performance (e.g., Arnon, 2019b). Note, however, that the statistical learning measures used in the present study were reliable at detecting learning in child participants with and without dyslexia overall.…”

“…In line with concerns relating to reliability, statistical learning measures have been shown to only weakly correlate amongst each other (e.g., Schmalz et al, 2019;Siegelman & Frost, 2015), which may help explain the mixed results regarding the relationship between statistical learning and measures of linguistic performance (i.e., some studies reporting significant correlations and others reporting null findings). Of course, these factors do not exclude the possibility that statistical learning plays an important role in language acquisition and is therefore related to children's grammatical performance, but merely affect our ability to evaluate this link (Arnon, 2019b). More research is needed in order to improve on present methodologies of measuring statistical learning and to more reliably evaluate its relationship to language.…”

Editors’ Introduction: Aligning Implicit Learning and Statistical Learning: Two Approaches, One Phenomenon

“…Distinctions in memory between declarative and procedural memory have typically been associated with implicit and explicit learning, respectively (Ullman, ). There are exciting future prospects for drawing together understanding of memory and development and the systems that are involved in language learning in infancy and childhood (Arnon, ; Gómez & Edgin, ; Kidd & Arciuli, ; Peter and Rowland, ; Romberg & Saffran, ). Relatedly, Batterink et al.…”

“…The next four articles in the special issue closely examine the role of implicit statistical learning in the acquisition of a novel language. Arnon () explores the link between implicit learning, statistical learning, and language development. Are the learning processes observed in typical implicit statistical learning experiments likely to play a role in language learning in the wild?…”

Child-directed speech is statistically optimized for meaning extraction

“…During social interactions, infants rely on a dynamic interpretation of words provided by the network of surrounding words embedded in a specific contextual situation (11,12). Learning these networks requires a highly efficient machinery of distributional learning that relies on statistical distributions of elements in the linguistic and extra-linguistic environment (6,(13)(14)(15)(16)(17). Children use statistical cues from the speech they hear for structural generalizations in perception (18)(19)(20) and the generalization of word classes, such as nouns or verbs (21)(22)(23)(24).…”