Back

"Foreign" language aptitude predicts individual differences in native grammatical proficiency.

  • Published In: Linguistics, 2023, v. 61, n. 5. P. 1165 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Llompart, Miquel; Dąbrowska, Ewa 3 of 3

Abstract

Language aptitude is known to be a strong predictor of success in late second-language (L2) learning in instructional settings but is generally assumed to be irrelevant for native language (L1) acquisition. We investigated the relationship between language aptitude and L1 grammatical proficiency in the two studies reported here. Language aptitude was measured by means of a newly-developed test of grammatical sensitivity (Studies 1 and 2) and the Language Analysis subtest of the Pimsleur Language Aptitude Battery (Study 1), whereas grammatical proficiency was assessed by a grammaticality judgment task in Study 1 and a picture selection task in Study 2. The results of the two studies reveal a robust relationship between language aptitude and L1 grammatical proficiency that is remarkably consistent across different measures for both variables and appears to hold across the board for a variety of grammatical structures. These results fit well with the proposal that explicit learning may play an important role not only in adult L2 learning but also in L1 acquisition and raises questions about the validity of arguments for a fundamental difference between L1 and L2 acquisition based on the premise that only the latter is related to aptitude. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Linguistics. 2023/09, Vol. 61, Issue 5, p1165
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:0024-3949
  • DOI:10.1515/ling-2022-0009
  • Accession Number:171926218
  • Copyright Statement:Copyright of Linguistics 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.