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Chinese Language Learning Sciences

Computational and Corpus Approaches to Chinese Language Learning

Editors: Lu, Xiaofei, Chen, Berlin (Eds.)

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  • Introduces corpora and natural language processing techniques for teaching, learning and assessing Chinese as a second or foreign language
  • Provides corpus resources and automated tools that are useful for Chinese language teaching, learning and assessment
  • Helps understand learners’ acquisition of Chinese through an analysis of large-scale learner Chinese corpora
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eBook $109.00
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Hardcover $139.99
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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.

About the authors

Xiaofei Lu is an Associate Professor of Applied Linguistics and Asian Studies at The Pennsylvania State University, where he directs the graduate programs in the Department of Applied Linguistics. His research interests include corpus linguistics, computational linguistics, intelligent computer-assisted language learning, English for academic purposes, and second language writing. He is the author of Computational Methods for Corpus Annotation and Analysis (Springer, 2014), and his work has been published in the American Educational Research Journal, Applied Linguistics, Educational Researcher, English for Specific Purposes, International Journal of Corpus Linguistics, Journal of Pragmatics, Journal of Second Language Writing, Language Learning and Technology, Language Resources and Evaluation, Language Testing, ReCALL, TESOL Quarterly, and The Modern Language Journal.
Berlin Chen is a Professor and Chair of the Computer Science and Information Engineering Department at National Taiwan Normal University. He received his Ph.D. in Computer Science and Information Engineering from National Taiwan University in June 2001, and joined NTNU as an Assistant Professor in August 2002. He became an Associate Professor in August 2006 and was promoted to the rank of Professor in February 2010. His research interests lie in the general areas of speech and natural language processing, multimedia information retrieval, and computer-assisted language learning. He is the author/coauthor of over 150 academic publications. Prof. Chen is a member of IEEE, ISCA and ACLCLP.

Table of contents (13 chapters)

Table of contents (13 chapters)
  • Computational and Corpus Approaches to Chinese Language Learning: An Introduction

    Lu, Xiaofei (et al.)

    Pages 3-11

  • Corpus and Computational Methods for Usage-Based Chinese Language Learning: Toward a Professional Multilingualism

    Jing-Schmidt, Zhuo

    Pages 13-31

  • The Corpus Approach to the Teaching and Learning of Chinese as an L1 and an L2 in Retrospect

    Xu, Jiajin

    Pages 33-53

  • Academic Chinese: From Corpora to Language Teaching

    Chen, Howard Ho-Jan (et al.)

    Pages 57-79

  • Pedagogical Applications of Chinese Parallel Corpora

    Bluemel, Brody

    Pages 81-98

Buy this book

eBook $109.00
price for USA in USD (gross)
  • ISBN 978-981-13-3570-9
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.99
price for USA in USD
  • ISBN 978-981-13-3569-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Computational and Corpus Approaches to Chinese Language Learning
Editors
  • Xiaofei Lu
  • Berlin Chen
Series Title
Chinese Language Learning Sciences
Copyright
2019
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-13-3570-9
DOI
10.1007/978-981-13-3570-9
Hardcover ISBN
978-981-13-3569-3
Series ISSN
2520-1719
Edition Number
1
Number of Pages
VIII, 269
Number of Illustrations
77 b/w illustrations, 30 illustrations in colour
Topics