Mini Pinyin: A modified miniature language for studying language learning and incremental sentence processing
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Mini Pinyin: A modified miniature language for studying language learning and incremental sentence processing Zachariah R. Cross 1 & Lena Zou-Williams 1 & Erica M. Wilkinson 1,2 & Matthias Schlesewsky 1 & Ina Bornkessel-Schlesewsky 1
# The Psychonomic Society, Inc. 2020
Abstract Artificial grammar learning (AGL) paradigms are used extensively to characterise (neuro)cognitive bases of language learning. However, despite their effectiveness in characterising the capacity to learn complex structured sequences, AGL paradigms lack ecological validity and typically do not account for cross-linguistic differences in sentence comprehension. Here, we describe a new modified miniature language paradigm – Mini Pinyin – that mimics natural language as it is based on an existing language (Mandarin Chinese) and includes both structure and meaning. Mini Pinyin contains a number of cross-linguistic elements, including varying word orders and classifier-noun rules. To evaluate the effectiveness of Mini Pinyin, 76 (mean age = 24.9; 26 female) monolingual native English speakers completed a learning phase followed by a sentence acceptability judgement task. Generalised mixed effects modelling revealed that participants attained a moderate degree of accuracy on the judgement task, with performance scores ranging from 25% to 100% accuracy depending on the word order of the sentence. Further, sentences compatible with the canonical English word order were learned more efficiently than non-canonical word orders. We controlled for inter-individual differences in statistical learning ability, which accounted for ~20% of the variance in performance on the sentence judgement task. We provide stimuli and statistical analysis scripts as open-source resources and discuss how future research can utilise this paradigm to study the neurobiological basis of language learning. Mini Pinyin affords a convenient tool for improving the future of language learning research by building on the parameters of traditional AGL or existing miniature language paradigms. Keywords Modified miniature language . Artificial grammar learning . Language learning . Sentence processing . Mini Pinyin
Introduction Language learning is a dynamic process that involves the extraction of meaning from linguistic elements spanning multiple scales of complexity (de Diego-Balaguer, Fuentemilla, & Rodriguez-Fornells, 2010). While the neural mechanisms subserving language learning at the syllable and word levels have been well characterised (for a review, see Davis & Electronic supplementary material The online version of this article (https://doi.org/10.3758/s13428-020-01473-6) contains supplementary material, which is available to authorized users. * Zachariah R. Cross [email protected] 1
Cognitive and Systems Neuroscience Research Hub, University of South Australia, Adelaide, Australia
2
Body in Mind Research Group, The Sansom Institute for Health Research, University of South Australia, Adelaide, Australia
Gaskell, 2009), uncovering the mechanisms of higher-ord
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