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. 2013 Feb;126(2):268-84.
doi: 10.1016/j.cognition.2012.10.008. Epub 2012 Nov 28.

Language experience changes subsequent learning

Affiliations

Language experience changes subsequent learning

Luca Onnis et al. Cognition. 2013 Feb.

Abstract

What are the effects of experience on subsequent learning? We explored the effects of language-specific word order knowledge on the acquisition of sequential conditional information. Korean and English adults were engaged in a sequence learning task involving three different sets of stimuli: auditory linguistic (nonsense syllables), visual non-linguistic (nonsense shapes), and auditory non-linguistic (pure tones). The forward and backward probabilities between adjacent elements generated two equally probable and orthogonal perceptual parses of the elements, such that any significant preference at test must be due to either general cognitive biases, or prior language-induced biases. We found that language modulated parsing preferences with the linguistic stimuli only. Intriguingly, these preferences are congruent with the dominant word order patterns of each language, as corroborated by corpus analyses, and are driven by probabilistic preferences. Furthermore, although the Korean individuals had received extensive formal explicit training in English and lived in an English-speaking environment, they exhibited statistical learning biases congruent with their native language. Our findings suggest that mechanisms of statistical sequential learning are implicated in language across the lifespan, and experience with language may affect cognitive processes and later learning.

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Figures

Fig. 1
Fig. 1
Partial effects of the three independent corpus variables entered in the ordinal logistic regressions. Y axis indicates the probability of a higher constituent rank (a less cohesive phrase boundary) between any two words in the English and Korean corpora.
Fig. 2
Fig. 2
Upper half of the figure. A representation of the Markov rule chain used in Experiments 1–3. Arrows represent the possible continuations at time t + 1 for a given symbol at time t, and the associate probabilities. Values above arrows indicate forward probabilities and values below arrows indicate backward probabilities. In the lower half of the figure, a sample of the sequential template generated by the Markov process (first row), with the corresponding instantiation with syllable stimuli (second row) that English and Korean speakers listened to in the learning phase of Experiment 1. Perceptual parses could emerge during training either when the forward transitional probability between adjacent syllables was high and the backward probability was low (HiLo groupings, third row), or vice versa (LoHi groupings, fourth row). At test participants were queried about which of these two sets of groupings they preferred.
Fig. 3
Fig. 3
Proportion of endorsements for HiLo (versus LoHi) groupings of items in Experiments 1–3. Error bars are standard errors. Top left panel: Opposite preferences for predictive and retrodictive patterns by English and Korean speakers in Experiment 1 appear to reflect learning biases for regularities that are most relevant in the participant’s native language, based on the canonical word order of their native language. The results from the Korean speakers, who had received extended explicit formal instruction in English, suggest that implicit statistical learning biases may continue to ‘leak’ into second language learning and processing. Top right panel: Control condition in Experiment 1. Participants not trained on the sequence exhibited no preference for language-like groupings. Bottom left panel: No language bias emerges when participants are exposed to the same grammar instantiated with shapes. Bottom right panel: When instantiated with musical tones, both Korean and English speakers preferred HiLo patterns.

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