Statistical Learning and Language: An Individual Differences Study

Abstract

Although statistical learning and language have been assumed to be intertwined, this theoretical presupposition has rarely been tested empirically. The present study investigates the relationship between statistical learning and language using a within-subject design embedded in an individual-differences framework. Participants were administered separate statistical learning tasks involving adjacent and nonadjacent dependencies, along with a language comprehension task and a battery of other measures assessing verbal working memory, short-term memory, vocabulary, reading experience, cognitive motivation, and fluid intelligence. Strong interrelationships were found among statistical learning, verbal working memory, and language comprehension. However, when the effects of all other factors were controlled for, performance on the two statistical learning tasks was the only predictor for comprehending relevant types of natural language sentences.

Individual Differences in Statistical Learning: Conceptual and Measurement Issues

“…1 We acknowledge that uncertainty exists over how SL is related to other forms of implicit learning as indexed by a variety of distinct tasks across a diverse set of literatures (e.g., [40]). In what follows, we presume that SL and implicit learning are closely related constructs, and that individual variation in SL is akin to the individual variation in implicit learning that others have studied (e.g., [27]).…”

“…From this perspective, a straightforward prediction is that individual differences in SL ability should be related to variation in language outcomes, with the specific expectation that individuals who are better at SL should show better language learning and processing (e.g., [1,9,25,26]). Although this prediction flows naturally from a number of extant psycholinguistic theories (e.g., [10,12]), it has received comparatively little attention in the literature.…”

“…On a theoretical level, different proposals carve up SL in different ways: some suggest that it is a unitary process (e.g., [40]), whereas others suggest it is an umbrella term for multiple processes, but differ on the number and nature of these underlying processes (e.g., [9,34]). On a methodological level, different measures of SL are quite different, and not necessarily correlated (e.g., [1,41,42]). …”

“…When two different measures of SL are uncorrelated or differ in some obvious way, this may reflect the fact that they tap into different underlying processes, the fact that the measures themselves have low reliability, or the fact that the measures have very distinct task demands. Consider the lack of correlation evidenced by the two SL measures used by Misyak and Christiansen [1]. The two measures indexed adjacent and nonadjacent regularities, respectively, and range of performance on the nonadjacent SL task was truncated by a ceiling effect.…”

“…Recent linguistic theories suggest that adaptation to probabilistic information characterizes both language acquisition in infancy [7,8,9], and language comprehension and production in adulthood (e.g., [10,11,12]). Within the domain of language, the acquisition of probabilistic structure has often been termed statistical learning (SL) 1 . SL has been demonstrated in learning and use of phonemic categories [13], lexical forms [14,15], phonotactic and phonological regularities characterizing words [16,17,18], word meaning [19], and syntactic structure [20,21,22,23,24].…”