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When it’s harder to ignorar than to ignore: Evidence of greater attentional capture from a non-dominant language ...
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When it’s harder to ignorar than to ignore: Evidence of greater attentional capture from a non-dominant language ...
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Supplemental_table – Supplemental material for When it’s harder to ignorar than to ignore: Evidence of greater attentional capture from a non-dominant language ...
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Supplemental_table – Supplemental material for When it’s harder to ignorar than to ignore: Evidence of greater attentional capture from a non-dominant language ...
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On Language and Thought: Bilingual Experience Influences Semantic Associations
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In: J Neurolinguistics (2020)
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Maternal scaffolding styles and children’s developing narrative skills: A cross-cultural comparison of autobiographical conversations in the US and Thailand
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In: Learn Cult Soc Interact (2020)
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Cognitive and Linguistic Predictors of Bilingual Single-Word Translation
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In: J Cult Cogn Sci (2020)
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Native Language Similarity during Foreign Language Learning: Effects of Cognitive Strategies and Affective States
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In: Appl Linguist (2020)
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When It’s Harder to Ignorar than to Ignore: Evidence of Greater Attentional Capture from a Non-Dominant Language
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In: Int J Billing (2020)
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Measuring Bilingualism: The Quest for a “Bilingualism Quotient”
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In: Appl Psycholinguist (2020)
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Listening to Speech and Non-speech Sounds Activates Phonological and Semantic Knowledge Differently
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In: Q J Exp Psychol (Hove) (2020)
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The case for measuring and reporting bilingualism in developmental research
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From Klingon to Colbertian: Using Artificial Languages to Study Word Learning
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In: Biling (Camb Engl) (2019)
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Abstract:
Vocabulary acquisition is a critical part of learning a new language. Yet, due to structural, historical, and individual variability associated with natural languages, isolating the impact of specific factors on word learning can be challenging. Artificial languages are versatile tools for addressing this problem, allowing researchers to systematically manipulate properties of the language and control for learners’ past experiences. Here, we review how artificial languages have been used to study bilingual word learning, with a particular focus on the influences of language input (e.g., word properties) and language experience (e.g., bilingualism). We additionally discuss the advantages and limitations of artificial languages for bilingual research and suggest resources for researchers considering the use of artificial languages. Used and interpreted properly, artificial language studies can inform our understanding of a wide range of factors relevant to word learning.
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Article
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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953750/
https://doi.org/10.1017/S1366728919000592
http://www.ncbi.nlm.nih.gov/pubmed/31929721
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| 35 |
Language Difficulty and Prior Learning Influence Foreign Vocabulary Acquisition
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The Language Experience and Proficiency Questionnaire (LEAP-Q): Ten years later
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In: Biling (Camb Engl) (2019)
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The Case for Measuring and Reporting Bilingualism in Developmental Research
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Learning and processing of orthography-to-phonology mappings in a third language
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In: Int J Multiling (2018)
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