JOURNAL ARTICLE

Language transfer in tense acquisition: new evidence from English learning Chinese adolescents.

  • Published In: IRAL: International Review of Applied Linguistics in Language Teaching, 2025, v. 63, n. 3. P. 2101 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Huang, Haiquan; Qian, Lina; Chen, Yixiong 3 of 3

Abstract

Distinct from English, Mandarin verbs are not inflected to encode Past Tense, but perfective aspect is typically marked by aspectual markers -le and -guo. Moreover, resultative verb compounds are often viewed as accomplishment verbs, denoting telicity of an event. This study attempts to examine whether such linguistic properties transfer to the acquisition of English. We tested 22 English learning Chinese adolescents in two experiments, respectively using a Story Restatements Task and an Elicited Production Task. Overall, the experiments generated three major findings. First, the participants marked irregular verbs 13 % higher than regular ones. Second, the participants used bare verbs to express English Past Tense 12 % of the situations. Third, the participants adopted Mandarin-like RVCs to denote English Past Tense 10 % of the cases. Taken together, the findings indicate that besides morphophonological transfer, English learning Chinese adolescents adopt Mandarin word-formation rules to encode English Past Tense, which is new evidence of cross-linguistic transfer. We discuss the implications of our findings. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:IRAL: International Review of Applied Linguistics in Language Teaching. 2025/09, Vol. 63, Issue 3, p2101
  • Document Type:Article
  • Subject Area:Language and Linguistics
  • Publication Date:2025
  • ISSN:0019-042X
  • DOI:10.1515/iral-2023-0191
  • Accession Number:188028653
  • Copyright Statement:Copyright of IRAL: International Review of Applied Linguistics in Language Teaching is the property of De Gruyter and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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