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The monolingual problem of computer-assisted language learning

Published online by Cambridge University Press:  20 March 2020

Judith Buendgens-Kosten*
Affiliation:
Goethe University Frankfurt, Germany (buendgens-kosten@em.uni-frankfurt.de)

Abstract

This paper sets out to discuss the monolingual problem within computer-assisted language learning (CALL) research and CALL product development, namely a lack of knowledge about how CALL products and projects can support learners in using all their linguistic resources to achieve language-learning- and language-using-related goals, and a lack of CALL products and projects that realize this potential, or that support specific plurilingual skill development. It uses an analysis of CALL-related papers to demonstrate how far CALL is impacted by a monolingual bias that it inherited from language learning pedagogy. An analysis of articles from four CALL journals across 10 years shows that although the words bilingual and multilingual appear in these journals fairly regularly, terms such as plurilingual, third language, tertiary language, L3, translanguaging, and translingual are extremely rare. Also, only eight articles could be identified that use any of these eight keywords in their title. Trends across those papers are identified. In a discussion of existing CALL products and projects that incorporate more than one language, it is argued that while commercial products often include more than one language, this is frequently in a behaviorist or grammar-translation tradition, while innovative plurilingual products and projects tend to be non-commercial and often EU/EC-funded initiatives. The article argues that CALL research and product development can not only avoid this monolingual bias, but also actively contribute to our knowledge of how all linguistic resources can be used for language learning. It makes suggestions for relevant future research areas related to multilingual computer-assisted language learning (MCALL).

Type
Regular papers
Copyright
© European Association for Computer Assisted Language Learning 2020

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