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Applied Linguistics Review

Editor-in-Chief: Wei, Li

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IMPACT FACTOR 2017: 1.286

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1868-6311
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A corpus linguistic investigation into online peer feedback practices in CALL teacher education

Olcay SertORCID iD: http://orcid.org/0000-0001-7513-2399 / Asuman Aşık
Published Online: 2018-10-12 | DOI: https://doi.org/10.1515/applirev-2017-0054

Abstract

This study investigates the online peer feedback practices of teacher trainees who are engaged in designing CALL materials. The participants are 111 pre-service English language teachers enrolled in a teacher education programme in Turkey, who post the materials they produce to an online course blog and then evaluate each other’s materials. The data come from the compilation of blog posts produced to provide online peer feedback, forming the Corpus of Online Peer Feedback in Teaching. The data are analysed using corpus linguistics, drawing on frequency, collocation, concordance, and keyword analyses. Our findings show that the participants highlight particular features of CALL materials such as student-centeredness, learner interest, and visual aspects by using constructive peer feedback with hedged evaluations, which brings data-based evidence for their knowledge on and beliefs about CALL materials. This research makes a methodological contribution to the study of online data in the field of language teacher education by employing the analytical lense of corpus linguistics. More importantly, the findings reveal that such an analytic approach can bring new insights into understanding the technological and pedagogical knowledge and beliefs of teachers in relation to language teaching materials design and development. The implications of the findings for research on CALL teacher education as well as on feedback and reflection practices are discussed.

Keywords: corpus linguistics; peer feedback; CALL; blogs; language teacher education

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About the article

Published Online: 2018-10-12


Citation Information: Applied Linguistics Review, ISSN (Online) 1868-6311, ISSN (Print) 1868-6303, DOI: https://doi.org/10.1515/applirev-2017-0054.

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