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Using Corpus-Aided Data-Driven Learning to Improve Chinese EFL Learners’ Analytical Reading Ability

  • Manfei XuEmail author
  • Xiao Chen
  • Xiaobin LiuEmail author
  • Xiaoyue Lin
  • Qiaoxin Zhou
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1048)

Abstract

Data-driven learning (DDL) has been proved successful in improving learners’ English language skills (Chen and Flowerdew 2018; Larsen-Walker 2017; Gui et al. 2010; He 2010). This study investigates a relatively under researched aspect, i.e., whether corpus-aided DDL can help learners improve their analytical reading ability. In a 6-week teaching experiment with a class of 31 advanced Chinese EFL learners, different corpus processed materials such as keywordlists and concordances were used to assist the subjects towards a deeper and quicker understanding of the texts. A post-study questionnaire survey and interviews obtained positive comments by the subjects. Based on the students’ feedback, a reading-writing experiment was further conducted to three more classes (135 students in total) using three different instructional modes, i.e., sheer teacher instruction, sheer corpus processed input, and teacher instruction plus corpus processed input. The study found corpus-aided DDL targeted at learner needs effective in improving the subjects’ reading capacity.

Keywords

Corpus-aided input DDL Analytical reading 

Notes

Acknowledgements

This paper is the result of the following funds: Guangdong Higher Education Teaching Reform Project 2016 (No. 236); Guangdong “13th Five Year” Plan Co-funded Project of Philosophy & Social Science (GD16XWW25). The corresponding author of this paper is Xiaobin Liu.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Foreign StudiesSouth China Normal UniversityGuangzhouChina

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