A Corpus-based Approach to Language Learning
A Case Study in Higher Education at the University of Calabria
DOI:
https://doi.org/10.13136/2281-4582/2023.i21.1196Keywords:
corpus linguistics, environmental studies, framing theory, social media communication studies, data-driven approachAbstract
The use of corpus linguistics (CL) tools and methods has been shown to be of great help in fostering language learning. As argued by Aston (2000), language pedagogy has started to plan and create corpora to fit its own principles and address its own needs. Most studies focus on classroom activities based on concordances and lexical/grammatical analyses carried out on corpora (McEnery et al. 2006). To date, CL has often been combined with teaching specific topics to carry out text and discourse analyses, and data-driven learning (Friginal 2018). Therefore, it is important to further investigate the use of corpora as a valuable resource for language education.
This work is testimony to the usefulness of corpus linguistics and corpus-based analyses for pedagogical purposes, while encouraging students to explore language autonomously and draw their own conclusions and considerations. Indeed, this paper outlines how CL can help learners, with different levels of language proficiency, approach English for Specific Purposes using authentic and concrete examples, and simultaneously lead them to develop new skills which may be integrated within their field of study.
The case study occurred in a distance learning context with first-year students majoring in Data Science and Business Analytics at the University of Calabria. The main objective was to enhance students’ motivation while improving their English competences using statistical analyses and corpus tools to investigate data retrieved from the social network Instagram and related to the topic of climate change. In particular, hands-on activities allowed students to create their own corpora, analyze language use through the corpus analysis toolkit AntConc (3.5.8), and carry out topic framing. Students’ final projects were then discussed at the oral exam.
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