Acquisition of the Chinese Particle le by L2 Learners: A Corpus-Based Approach

Hai Xu, Xiaofei Lu, Vaclav Brezina

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The Chinese particle le (了) has proven to be challenging for L2 learners to acquire, both because it may function as either a perfective aspect marker or a sentence-final modal particle and because its usage is subject to various semantic, syntactic, prosodic, and discourse constraints. Previous research into the development of knowledge of the uses of le and the order of acquisition of its functions and meanings has yieldedinconsistent results. Furthermore, due to the limited data available, previous studies have usually employed written corpus data produced by a small number of learners from a specific L1 background. Utilizing the spoken subcorpus of the large-scale Guangwai-Lancaster Chinese Learner Corpus, this study closely examines the uses of le by learners of Chinese from diverse L1 backgrounds as well as the developmental pattern of their acquisition of this particle. Results demonstrate that learners generally use le in speech with a low frequency and a high degree of accuracy. Significant increase in frequency of use is observed between beginner and intermediate learners, while that in accuracy is observed between intermediate and advanced learners. Evidence from the current study does not support a specific acquisition order for the basic functions of le. Learner errors primarily involve overuse of the particle in conjunction with statives and may be largely attributed to learners’ deficient knowledge of the constraints of its usage. Findings of our investigation have useful implications for the instruction of the particle le.

Original languageEnglish (US)
Title of host publicationChinese Language Learning Sciences
PublisherSpringer Nature
Pages197-216
Number of pages20
DOIs
StatePublished - 2019

Publication series

NameChinese Language Learning Sciences
ISSN (Print)2520-1719
ISSN (Electronic)2520-1727

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language
  • Education
  • Computer Science Applications

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