Ayuda
Ir al contenido

Dialnet


From Klingon to Colbertian: Using Artificial Languages to Study Word Learning

  • Autores: Sayuri Hayakawa, Siqi Ning, Viorica Marian
  • Localización: Bilingualism: Language and cognition, ISSN 1366-7289, Vol. 23, Nº 1, 2020, págs. 74-80
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • 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.


Fundación Dialnet

Dialnet Plus

  • Más información sobre Dialnet Plus

Opciones de compartir

Opciones de entorno