Bilingualism and statistical learning: Lessons from studies using artificial languages

Weiss, Daniel J.; Schwob, Natalie; Lebkuecher, Amy L.

doi:10.1017/s1366728919000579

Cited by 20 publications

(18 citation statements)

References 54 publications

(63 reference statements)

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“…Other studies using linguistic stimuli with transitional probabilities have started to investigate how to attenuate the persistent effect of the already acquired statistical representations (Weiss, Schwob, & Lebkuecher, 2019). By presenting two artificial speech streams in smaller alternating blocks, individuals were able to learn both statistical structures underlying the input streams, without using explicit contextual cues (e.g., change in speaker) denoting the transitions across streams (Zinszer & Weiss, 2013).…”

Section: Discussionmentioning

confidence: 99%

Perceiving structure in unstructured stimuli: Implicitly acquired prior knowledge impacts the processing of unpredictable transitional probabilities

Kóbor

Horváth

Kardos

et al. 2019

Preprint

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AbstractIt is unclear how implicit prior knowledge is involved and remains persistent in the extraction of the statistical structure underlying sensory input. Therefore, this study investigated whether the implicit knowledge of 2nd order transitional probabilities characterizing a stream of visual stimuli impacts the processing of unpredictable transitional probabilities embedded in a similar input stream. Young adults (N = 50) performed a four-choice reaction time (RT) task that consisted of structured and unstructured blocks. In the structured blocks, more probable and less probable short-range nonadjacent transitional probabilities were present. In the unstructured blocks, the unique combinations of the short-range transitional probabilities occurred with equal probability; therefore, they were unpredictable. All task blocks were visually identical at the surface level. While one-half of the participants completed the structured blocks first followed by the unstructured blocks, this was reversed in the other half of them. The change in the structure was not explicitly denoted, and no feedback was provided on the correctness of each response. Participants completing the structured blocks first showed faster RTs to more probable than to less probable short-range transitional probabilities in both the structured and unstructured blocks, indicating the persistent effect of prior knowledge. However, after extended exposure to the unstructured blocks, they updated this prior knowledge. Participants completing the unstructured blocks first showed the RT difference only in the structured blocks, which was not constrained by the preceding exposure to unpredictable stimuli. The results altogether suggest that implicitly acquired prior knowledge of predictable stimuli influences the processing of subsequent unpredictable stimuli. Updating this prior knowledge seems to require a longer stretch of time than its initial acquisition.

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Section: Discussionmentioning

confidence: 99%

Perceiving structure in unstructured stimuli: Implicitly acquired prior knowledge impacts the processing of unpredictable transitional probabilities

Kóbor

Horváth

Kardos

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…External Force: Neighborhood Density in the Learning Environment Although the internal structure of the bilingual mental lexicon is likely to impact word learning, the external learning environment may also play a role (see Fourtassi et al, 2020). Indeed, bilingual individuals may also be specifically attuned to patterns in the external learning environment, given their exposure to two different linguistic systems (e.g., Poepsel & Weiss, 2016; for a discussion, see Weiss, Schwob, & Lebkuecher, 2020). The external learning environment comprises the entire language network that the learner tries to acquire, including words that are already known by the learner as well as words that are present in their environment (Hills et al, 2009;Siew & Vitevitch, 2020).…”

Section: Word Learning In Bilingual Individualsmentioning

confidence: 99%

Learning, Inside and Out: Prior Linguistic Knowledge and Learning Environment Impact Word Learning in Bilingual Individuals

et al. 2022

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Although several studies have focused on novel word learning and lexicalization in (presumably) monolingual speakers, less is known about how bilinguals add novel words to their mental lexicon. In this study we trained 33 English-French bilinguals on novel word-forms that were neighbors to English words with no existing neighbors. The number of novel neighbors to each English word varied, as did the cross-linguistic orthographic overlap between the English word and its French translation. We assessed episodic memory and lexicalization of the novel words before and after a consolidation period. Cross-linguistic similarity enhanced episodic memory of novel neighbors only when neighborhood density among the novel neighbors was low. We also found evidence that novel neighbors of English words with high cross-linguistic similarity became lexicalized after a consolidation period. Overall, the results suggest that similarity to preexisting lexical representations crucially impacted lexicalization of novel words by bilingual individuals.

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“…The AGL paradigm allows control over the regularities available to learners in the input, manipulating complexity level and assessing participants' sensitivity to the level of associative chunk strength of the test stimuli. It also enables testing the distributed practice effect, using a small-scale experimental task with compact periods of familiarization to measure learning (Weiss et al 2020).…”

Section: Statistical Learningmentioning

confidence: 99%

Artificial grammar learning is facilitated by distributed practice: Evidence from a letter reordering task

et al. 2021

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Previous studies have shown that distributed practice-a training strategy that is known to facilitate memory-is likely to result in greater learning than massed practice. This effect has been demonstrated largely in explicit tasks. The purpose of this study was to test whether statistical learning of artificial grammar is affected by the lag between learning sessions overall, and by high and low complexity stimuli (as measure by chunk strength). Two groups (spaced-short and spaced-long) learned strings of letters created according to a set of rules and were required to produce new strings using given letter sets. For the spaced-short group, the two learning sessions, each including training and a test phase, took place sequentially with a 10-min break, whereas for the spaced-long group, learning sessions were distributed across two days (1-day lag). Overall results showed improved performance following spaced-long practice compared to spaced-short practice. The results also indicated that in the low chunk strength strings (indicating high complexity), both groups demonstrated similar improvement from first to second testing, while in the high chunk strength strings (indicating low complexity), improvement in letter reordering performance was significantly higher when the learning sessions were distributed across two days. This pattern of findings suggests that stimuli complexity affects the extent to which distributed practice enhance artificial grammar learning.

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Bilingualism and statistical learning: Lessons from studies using artificial languages

Cited by 20 publications

References 54 publications

Perceiving structure in unstructured stimuli: Implicitly acquired prior knowledge impacts the processing of unpredictable transitional probabilities

Perceiving structure in unstructured stimuli: Implicitly acquired prior knowledge impacts the processing of unpredictable transitional probabilities

Learning, Inside and Out: Prior Linguistic Knowledge and Learning Environment Impact Word Learning in Bilingual Individuals

Artificial grammar learning is facilitated by distributed practice: Evidence from a letter reordering task

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