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THE ROLE OF L1 PHONOLOGY IN L2 MORPHOLOGICAL PRODUCTION

L2 ENGLISH PAST TENSE PRODUCTION BY L1 SPANISH, MANDARIN, AND JAPANESE SPEAKERS

Published online by Cambridge University Press:  04 July 2017

Jennifer Cabrelli Amaro ,
Gonzalo Campos-Dintrans  and
Jason Rothman
Jennifer Cabrelli Amaro*
Affiliation:
University of Illinois at Chicago
Gonzalo Campos-Dintrans
Affiliation:
University of Mary Washington
Jason Rothman
Affiliation:
University of Reading/UiT The Arctic University of Norway
*
*Correspondence concerning this article should be addressed to Jennifer Cabrelli Amaro, 601 S Morgan St., 1722 University Hall (M/C 315), Chicago, IL 60607, USA. E-mail: cabrelli@uic.edu
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Abstract

This study considers the role of L1 phonological influence in L2 English past tense morphology production by native speakers of Spanish, Mandarin, and Japanese. While these L1s share similar phonological restrictions on consonant cluster formation needed for English past tense morphology, differences arise in L1 syntax (only Mandarin lacks syntactic past) and L1 prosodic structure (only Japanese has English-equivalent structure). Aggregate analyses indicate that an L1 English control group outperforms all L2 groups in oral suppliance of past tense morphology. Results therefore reveal that having the syntactic feature for past in the L1 does not translate into targetlike performance and that L1 phonological restrictions alone cannot fully explain nontargetlike performance. Considering previous and the current data sets, we argue that evidence from production of L2 English past tense cannot be used to adjudicate between representational deficit approaches and full access approaches, contrary to what has been argued previously.

Type
Research Article
Information
Studies in Second Language Acquisition , Volume 40 , Issue 3 , September 2018 , pp. 503 - 527
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

The authors would like to thank the anonymous reviewers for their valuable comments, and Bill Davies, Roger Hawkins, Roumyana Slabakova, and Amanda Van Horne for their support in the development of this project. Special thanks go to Heather Goad for extensive feedback on an earlier version of this paper and to Jeffrey Renaud for his assistance with data analysis. This material is based upon work supported by the National Science Foundation under Grant No. BCS#1024256. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

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