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Surface features can deeply affect artificial grammar learning (IACOBUS_Papers 2020/2021)

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Jiménez, L., Mendes Oliveira, H., & Soares, A. P. (2020). Surface features can deeply affect artificial grammar learning. Consciousness and Cognition, 80, 102919. doi: https://doi.org/10.1016/j.concog.2020.102919


 

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.
 

This study was conducted at the Psychology Research Centre (PSI/01662), University of Minho, and supported by the Grant POCI01-0145-FEDER-028212 from the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Science, Technology and Higher Education through national funds, and co-financed by FEDER through COMPETE2020 under the PT2020 Partnership Agreement. The research was also funded by the Spanish Ministerio de Economia y Competitividad with a research grant to Luis Jimenez (PSI2015-70990-P)

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