The Study of Error Types of Chinese Learners’ Written Texts: A Chinese Written Corpus-Based Study

Jia Fei Hong*, Hsin Tzu Jen, Yao Ting Sung

*此作品的通信作者

研究成果: 書貢獻/報告類型篇章

摘要

The present study aims to tackle the issue of error in written texts by Chinese learners from a macro perspective. Although previous research has demonstrated the significance of positive feedback and effective correction in the realm of Second Language Acquisition (SLA) (Fathman and Whalley, 1990; Ashwell, 2000; Ferris and Robers, 2001; Chandler, 2003), little consensus has been reached regarding its practical implementation in pedagogy. In particular, writing holds a crucial role among the four basic language skills for its complex construction and meaning in written language. However, with the rise of corpus linguistics, new approaches and perspectives have been added to the study of Chinese as a Second Language (CSL) writing (Chang et al., 2015; Hong et al., 2018). In hopes of improving the teaching of writing in an integrated way, this study adopts methodologies from SLA and corpus linguistics to broaden the scale of interdisciplinary research. Through the lens of error analysis, this study examines data from learners with diverse backgrounds in Chinese Written Corpus and analyzes learners’ error types with reference to the categorization proposed by Dulay et al. (1982). The results of this analysis identify possible contributing factors of various types of errors, such as native language and level, which can then be further analyzed and may account for learners’ error patterns. The present study’s findings yield significant insights in outlining the distribution of errors in CSL writing and provide teachers and future researchers with practical advice on the study of teaching strategy, instructional setting, and teaching sequence.

原文英語
主出版物標題Chinese Language Learning Sciences
發行者Springer
頁面155-184
頁數30
DOIs
出版狀態已發佈 - 2023

出版系列

名字Chinese Language Learning Sciences
ISSN(列印)2520-1719
ISSN(電子)2520-1727

ASJC Scopus subject areas

  • 語言與語言學
  • 教育
  • 語言和語言學
  • 電腦科學應用

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