Abstract:

During the last three decades the application of corpora and concordancers in the English language studies and acquisition has noticeably expanded (Boulton, 2021) due to open access corpora management systems (e.g. BNCweb, English Corpora.org) and concordancers (e.g. AntConc, LexTutor). Even if they contribute to the progressing of data-driven language learning (DDL) and research activities heading students towards digital humanities, there is also caution (Williams, 2020) as to the complexity of their affordances and therefore the familiar technology for students might be preferred. Meanwhile, contemporary updated affordances of open access concordancers can provide insightful data by uncovering linguistic characteristics of corpora texts. Taking this into account, the goal of the present in-process study is to unfold the case of a gentle approach to AntConc application practice for linguistic research by undergraduate students of English studies, who are without the previous experience of the using concordancers in data extraction. The case study comprised 70 students who participated in AntConc-based text mining practice and discussion seminars within the framework of the course Introduction to Applied Linguistics and Digital Humanities. An additional challenge was the online mode of practice sessions because of COVID-19 caused lockdown in November and December of 2021. The seminars comprised four sequenced sets of activities: firstly, the introductory activities – the discussion of the examples and the basic functions of AntConc; secondly, the creation of micro corpus for the subsequent data extraction activities and finally, data extraction and discussion activities focusing on the implications of the acquired data and submission of portfolios that comprised the completed tasks. The analysis of students’ portfolios revealed that they had familiarised with the practiced AntConc affordances and relevantly applied them for linguistic data extraction. Although most of the students had discussed the implications of what the extracted data revealed about the texts of their micro corpora, the detailing of the implications varied. The post-questionnaires that the students filled in showed that they acknowledged the usefulness of the activities for the acquisition of the previously unexperienced data extraction skills, simultaneously noting the role of activity explicitness.

References:
[1] Boulton, A. (2021) Thirty years of data-driven learning: Taking stock and charting new directions over time. Language Learning & Technology ISSN 1094-3501, October 2021, Volume 25, Issue 3, pp. 66–89.
[2] Williams, J. (2020) An innovative (and easy) approach to corpus analysis. TESL Ontario. Contact. March 2020, pp. 14- 25.

Keywords:

Concordancer, AntConc, DDL, corpus.