Literacy effects on artificial grammar learning (AGL) with letters and colors: evidence from preschool and primary school children

Abstract

Literacy affects many aspects of language and cognition, including the shift from a more holistic mode of processing to a more analytical part-based mode of processing. Here we examined whether this shift impacts the ability of preschool and primary school children to learn the rules underlying a finite-state grammar using an artificial grammar learning (AGL) paradigm implemented with either linguistic (letters) or non-linguistic (colors) materials to further examine if children’s AGL performance was modulated by type of stimuli. Both tasks involved a training phase in which half of the preschool children and half of the primary school children were exposed to a set of either letter or color strings without any information about the rules underlying the construction of those strings. Later, in the test phase, they were asked to decide whether a new set of letter or color strings conformed to those rules to test grammar learning. Results showed that only primary school children showed evidence of learning, and, importantly, only with colors. These findings seem to support the view that learning to read promotes reliance on smaller linguistic units that might hinder the ability of first-graders to learn the rules underlying finite-state grammars implemented with linguistic materials.

Learning Words While Listening to Syllables: Electrophysiological Correlates of Statistical Learning in Children and Adults

“…Nonetheless, it is important to note that the differences in the 2-AFC performance across groups were made at the expense of the absence of reliable signs of learning in the group of children, hence recommending a more nuanced interpretation of the age-related differences in behavioral SL outcomes. Although the lack of behavioral signs of SL for children, even when explicit instructions were provided, might stem from the complexity of the speech streams used – which entailed a larger and more diverse number of triplets than in previous works – it is worth noting that these findings are in accordance with Raviv and Arnon’s (2018) and Shufaniya and Arnon’s (2018) studies, which did not find behavioral signs of SL for children below 6 years age [see also van Witteloostuijn et al (2019) and Lukács et al (2021) for similar results with 3-AFC tasks, and Soares et al (2021d) for similar findings with the artificial learning paradigm]. Thus, more than a failure to track the statistical structure embedded in the input, what these behavioral results seem to indicate is that the 2-AFC task is not appropriate for assessing SL, particularly in children of this age, once they seem to lack the cognitive abilities needed to perform the 2-AFC task appropriately (e.g., see van Witteloostuijn et al (2019) , Arnon (2020) , Lukics and Lukács (2021) , Lukács et al (2021) ).…”

“… Batterink L.J. et al, 2015 found evidence for explicit knowledge during aSL, even when no explicit instructions were provided to the participants to perform the task (see also Jiménez et al (2020) and Soares et al (2021d) for recent evidence with the artificial grammar learning paradigm). Further support for the involvement of explicit learning mechanisms in SL comes from neuroimaging studies, showing that responses to statistical regularities are observed in areas generally associated with implicit (e.g., basal ganglia) and explicit (e.g., medial-temporal areas, including hippocampus) structures ( Turk-Browne et al, 2009 ; Karuza et al, 2013 ), in accordance with the two-memory learning systems (procedural vs. declarative) model in the brain (see Batterink et al (2019) for a review).…”

Explicit Instructions Do Not Enhance Auditory Statistical Learning in Children With Developmental Language Disorder: Evidence From Event-Related Potentials

“…Moreover, it is also important to point out that we have resorted to the use of an aSL task modeled from Saffran et al (1996) instead of another implicit learning task (e.g., artificial grammar learning) for several reasons. Firstly, the aSL task allows testing SL skills at a simpler language level of processing (words level), which seems to be particularly appropriate when studying children with language impairments (see also Soares et al, 2018 , 2021c ; Jiménez et al, 2020 for other arguments justifying why artificial grammar learning tasks were not used). Secondly, recent neuroimaging studies using functional MRI (fMRI) showed that responses to the statistical regularities (TPs) embedded in the input recruit brain areas associated both with procedural and declarative systems, although the reliance on one or another seems also to depend on the type of instructions (implicit vs. explicit) provided to the participants to perform the task (e.g., Karuza et al, 2013 ; for a review, see Batterink et al, 2019 ).…”

Age-Related Differences in Auditory Statistical Learning of Complex Speech Streams: Evidence From ERPs

“…The absence of reliable signs of SL in the group of 5-years old children is not new. In Raviv and Arnon 5 , and also Shufaniya and Arnon's 6 works, the authors did not found evidence of SL for children under 6 years of age, which led them to exclude these children from the analyses to avoid the age differences that simply re ected the move from a chance to an above-chance 2-AFC performance [see also 17 ] for similar ndings with the arti cial grammar learning paradigm). In our case, the absence of reliable signs of aSL in the 2-AFC tasks performed by children might also stem from the complexity of the speech stream used, which entailed not only a higher number of 'words' (eight) than used in previous works (typically from four to six 'words'), but also 'words' that were more diverse on their composition.…”

“…However, a growing body of research conducted in the last decade has challenged this view by showing that SL/IL improves with age [see 15,16 for reviews]. Moreover, recent works suggest that the developmental trajectory of this ability might not be the same across sensory modalities and types of stimuli [e.g., 5,6,17 ]. For instance, Raviv and Arnon 5 , using auditory syllables and visual gures in visual and auditory SL tasks (vSL and aSL, respectively) modeled from Saffran et al's.…”