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. 2020 Apr:80:102919.
doi: 10.1016/j.concog.2020.102919. Epub 2020 Mar 19.

Surface features can deeply affect artificial grammar learning

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Surface features can deeply affect artificial grammar learning

Luis Jiménez et al. Conscious Cogn. 2020 Apr.

Abstract

Three experiments explored the extent to which surface features explain discrimination between grammatical and non-grammatical strings in artificial grammar learning (AGL). Experiment 1 replicated Knowlton and Squire's (1996) paradigm using either letter strings as in the original study, or an analogous set of color strings to further explore if learning was affected by type of stimuli. Learning arose only with letter strings, but the results were mostly due to the discrimination of non-grammatical strings containing highly salient illegal features. Experiments 2 and 3 tested a new grammar devised to control for those features. Experiment 2 showed reduced grammar learning effects, and again only for letter materials. Experiment 3 explored the effect of additional practice with letter stimuli, and found increased learning only in the spaced practice condition, though additional practice also produced more explicit knowledge. These findings call for further research on the boundary conditions of learning in AGL paradigms.

Keywords: Artificial grammar learning; Chunk learning; Implicit learning.

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