Computational and Corpus Approaches to Chinese Language Learning

  • Xiaofei Lu
  • Berlin Chen

Part of the Chinese Language Learning Sciences book series (CLLS)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Introduction

  3. Tools, Resources and General Applications

    1. Front Matter
      Pages 55-55
    2. Howard Ho-Jan Chen, Hongyin Tao
      Pages 57-79
  4. Specific Applications

    1. Front Matter
      Pages 119-119
    2. Liang-Chih Yu, Wei-Nan Chien, Kai-Hsiang Hsu
      Pages 121-143
  5. Learner Language Analysis and Assessment

About this book


This book presents a collection of original research articles that showcase the state of the art of research in corpus and computational linguistic approaches to Chinese language teaching, learning and assessment. It offers a comprehensive set of corpus resources and natural language processing tools that are useful for teaching, learning and assessing Chinese as a second or foreign language; methods for implementing such resources and techniques in Chinese pedagogy and assessment; as well as research findings on the effectiveness of using such resources and techniques in various aspects of Chinese pedagogy and assessment.


Chinese language acquisition Chinese language assessment Chinese language learning Chinese language teaching computational linguistics computer-assisted language learning corpus linguistics natural language processing Chinese as a second language China’s New Media

Editors and affiliations

  • Xiaofei Lu
    • 1
  • Berlin Chen
    • 2
  1. 1.Department of Applied LinguisticsThe Pennsylvania State UniversityUniversity ParkUSA
  2. 2.Department of Computer Science and Information EngineeringNational Taiwan Normal UniversityTaipeiTaiwan

Bibliographic information

  • DOI
  • Copyright Information Springer Nature Singapore Pte Ltd. 2019
  • Publisher Name Springer, Singapore
  • eBook Packages Education Education (R0)
  • Print ISBN 978-981-13-3569-3
  • Online ISBN 978-981-13-3570-9
  • Series Print ISSN 2520-1719
  • Series Online ISSN 2520-1727
  • Buy this book on publisher's site