Statistically Induced Chunking Recall: A Memory‐Based Approach to Statistical Learning

Abstract

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Using Utterance Recall to Assess Second Language Proficiency

“…In the memory literature, serial recall of lists of items (words, letters, digits) have been used extensively to measure the effect of chunking on memory abilities (e.g., Jones & Macken, 2015). Variations of this task have been used to test general statistical learning (e.g., Isbilen et al., 2017, in press)—the ability to learn distributional patterns of co‐occurrence in language and other aspects of cognition (see Frost, Armstrong, & Christiansen, 2019; Rebuschat & Williams, 2012, for reviews). Under the guise of “sentence imitation,” recall of whole sentences has long been used to assess L1 acquisition in children (e.g., Frizelle, O'Neill, & Bishop, 2017; Slobin & Welsh, 1967).…”

“…From this perspective, Christiansen and Chater argue that rapid chunking of language input is central to language proficiency. Though there has been some work using chunking to measure general skill learning (e.g., Isbilen, McCauley, Kidd, & Christiansen, 2017, in press—see Christiansen, 2019; Gobet et al., 2001, for reviews), chunking is mostly ignored in L2‐learning measures.…”

Short-Term Memory for Serial Order Moderates Aspects of Language Acquisition in Children With Developmental Language Disorder: Findings From the HelSLI Study

“…Although SL is generally thought of as an implicit process, not available to conscious reflection, its results are usually tested by explicit forced-choice decisions. Recently, SL has also been shown to affect the accuracy of serial short-term memory tasks: better serial recall was seen for sequences that had first been included in an SL task (Isbilen et al, 2020). As SL has been shown to correlate with developmental language measures (for a review, see Siegelman, 2020) and has been suggested to play a role in DLD (Mainela-Arnold and Evans, 2014), possible modality-specific differences in the learnability of regularities in temporal SL sequences could also affect STM for serial order.…”

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

“…This work investigated the degree to which perceptual fluency influences statistical learning, and to what extent perceptual fluency reflects stimulus familiarity vs complexity. Recognising that SL relies on basic memory processes (Frank et al, 2010;Frost et al, 2019;Isbilen et al, 2020), we hypothesised that participants would learn the same statistical distribution better when they found items to be easier to perceptually distinguish, parse, and remember. This hypothesis was uniformly supported across three experiments.…”

“…Moreover, in the case of Siegelman et al (2018), they suggest that prior learning constitutes an important yet understudied component of the process. As a result, statistical learning has more recently been conceptualised as a multi-component process (Arciuli, 2017;Frost et al, 2019;Siegelman, Bogaerts, & Frost, 2017), grounded in basic perception and cognition ( (Frank, Goldwater, Griffiths, & Tenenbaum, 2010;Christiansen, 2019;Isbilen et al, 2020). However, the specifics of those components are far from clear, as Siegelman et al (2017) note: "in contrast with general intelligence ... the dimensions of SL as an individual ability are yet to be empirically established."…”