Interactive visual text analysis for corpus-based language learning

Ying Zhu, Eric Friginal

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

A corpus is a large collection of texts that can be automatically analyzed for linguistic patterns and structures using interactive tools. Corpus-based language learning has gained prominence in recent years thanks to the advances in computing technologies, such as text mining, searching, and natural language processing. The size and variety of corpora have also grown significantly in recent years. However, most of the corpus tools currently available are designed for linguistic research, not for classroom teaching and learning. In this paper, we present a new corpus tool called Text X-Ray that features visual text analysis and supports corpus-based language learning. This program helps students analyze their own writing and compare their writing with a corpus. This tool has been tested in real classroom settings and has received several positive feedback from a range of instructors and students.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 1st International Conference on Big Data Computing Service and Applications, BigDataService 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages462-467
Number of pages6
ISBN (Electronic)9781479981281
DOIs
Publication statusPublished - 10 Aug 2015
Event1st IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2015 - San Francisco, United States
Duration: 30 Mar 20153 Apr 2015

Publication series

NameProceedings - 2015 IEEE 1st International Conference on Big Data Computing Service and Applications, BigDataService 2015

Conference

Conference1st IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2015
Country/TerritoryUnited States
CitySan Francisco
Period30/03/153/04/15

Keywords

  • language teaching and learning
  • text corpus
  • text visualization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

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