Using Google to Search Language Patterns in Web-Corpus: EFL Writing Pedagogy

Authors

  • Olga S. Kvashnina National Research Tomsk Polytechnic University Lenin ave, 30, 634050, Tomsk, Russia
  • Olga V. Sumtsova National Research Tomsk Polytechnic University Lenin ave, 30, 634050, Tomsk, Russia

DOI:

https://doi.org/10.3991/ijet.v13i03.7712

Keywords:

web corpus, Google, EFL writing, language patterns, linguistic corpus

Abstract


The use of the Web as a corpus of language data and Google as a concordancer has been considered as one of the promising directions in the development of the EFL pedagogy. It has been stated by several researchers that the use of the popular search engine Google to hunt and define authentic language patterns is mostly advantageous for teaching EFL writing as well as mastering learning autonomy of the EFL students. The present article focuses on the advantages and opportunities of Google as a search engine in the Web-corpus for EFL writing pedagogy in technical universities. The authors compare the results of the current investigation with the outcomes of their previous study aimed at examining the potential of traditional linguistic corpora for EFL classroom. Although there is a strong need for further in-depth study of the considered issue, the comparative results obtained at this stage reveal high potential and remarkable advantage of the global web as a corpus, and Google as a search and access tool to authentic language patterns.

Author Biographies

Olga S. Kvashnina, National Research Tomsk Polytechnic University Lenin ave, 30, 634050, Tomsk, Russia

Department of Foreign Languages, Institute of Physics and Technology

Olga V. Sumtsova, National Research Tomsk Polytechnic University Lenin ave, 30, 634050, Tomsk, Russia

Department of Foreign Languages, Institute of Physics and Technology

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Published

2018-03-05

How to Cite

Kvashnina, O. S., & Sumtsova, O. V. (2018). Using Google to Search Language Patterns in Web-Corpus: EFL Writing Pedagogy. International Journal of Emerging Technologies in Learning (iJET), 13(03), pp. 173–179. https://doi.org/10.3991/ijet.v13i03.7712

Issue

Section

Short Papers