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The critical roles of errors and individual differences in bilingual translation

Published online by Cambridge University Press:  04 July 2018

NATASHA TOKOWICZ
NATASHA TOKOWICZ*
Affiliation:
University of Pittsburgh
*
Address for correspondence: Natasha Tokowicz, LRDC Room 634, 3939 O'Hara St., University of Pittsburgh, Pittsburgh, PA 15260-5169 tokowicz@pitt.edu
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Extract

Multilink moves the field a step forward in being able to make clear predictions about how a bilingual's languages interact in a variety of tasks. It addresses some shortcomings of the BIA (Dijkstra, van Heuven & Grainger, 1998) and BIA+ (Dijkstra & van Heuven, 2002) models, which did not explain performance from bilinguals of varied proficiency levels or on translation tasks. However, there are still gains that can be made – Dijkstra, Wahl, Buytenhuijs, van Halem, Al-jibouri, de Korte, and Rekké (2018) themselves point out that there are additional ways in which they plan to expand the model.

Type
Peer Commentaries
Information
Bilingualism: Language and Cognition , Volume 22 , Issue 4 , August 2019 , pp. 697 - 698
Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

*The writing of this commentary was supported by NIH R01 HD075800. The author thanks Caitlin Rice for comments on this manuscript.

References

Dijkstra, T., & van Heuven, W. J. B. (2002). The architecture of the bilingual word recognition system: From identification to decision. Bilingualism: Language and Cognition, 5 (3), 175–197.Google Scholar
Dijkstra, A., van Heuven, W. J. B., & Grainger, J. (1998). Simulating competitor effects with the Bilingual Interactive Activation Model. Psychologica Belgica, 38, 177–196.Google Scholar
Dijkstra, A., Wahl, A., Buytenhuijs, F., van Halem, N., Al-jibouri, Z., de Korte, M., & Rekké, S. (2018). Multilink: a computational model for bilingual word recognition and word translation. Bilingualism: Language and Cognition, doi:10.1017/S1366728918000287.Google Scholar
Kaushanskaya, M. (2018). What can errors tell us about differences between monolingual and bilingual vocabulary learning? International Journal of Bilingual Education and Bilingualism, 21 (4), 389–404.Google Scholar
Linck, J.A., Osthus, P., Koeth, J.T., & Bunting, M. F. (2014). Working memory and second language comprehension and production: A meta-analysis. Psychonomic Bulletin & Review, 21 (4), 861–883.Google Scholar
Miller, N. A., & Kroll, J. F. (2002). Stroop effects in bilingual translation. Memory & Cognition, 30, 614–628.Google Scholar
Tokowicz, N., Michael, E. B., & Kroll, J. F. (2004). The roles of study-abroad experience and working-memory capacity in the types of errors made during translation. Bilingualism: Language and Cognition, 7 (3), 255–272.Google Scholar
Tseng, A. M., Chang, L.-Y., & Tokowicz, N. (2014). Translation ambiguity between English and Mandarin Chinese: The roles of proficiency and word characteristics. In Schwieter, J. and Ferreira, A. (eds.), The development of translation competence: Theories and methodologies from psycholinguistics and cognitive science (pp. 107–165). Cambridge: Cambridge Scholars Publishing.Google Scholar