Corpus-Driven Task Design and Its Effectiveness in Developing Pragmatic Competence among IT English Learners
DOI:
https://doi.org/10.5281/zenodo.20808299
Abstract
This article presents a corpus-driven system of 24 pedagogical tasks designed to develop both pragmatic competence and grammatical accuracy among university-level learners of English for Information Technology (EIT) purposes. The task system draws on a diverse range of authentic corpora – including the Corpus of Contemporary American English (COCA), the British National Corpus (BNC), the Michigan Corpus of Academic Spoken English (MICASE), the Enron Email Corpus, Sketch Engine, Stack Overflow, and GitHub – to ground instruction in real-world professional communication. Task types span dialogues, scenario-based interactions, role-plays, professional email and report writing, online commenting, synchronous chat simulations with international IT specialists, inductive corpus analysis, and learner text production, all anchored in domain-specific IT terminology and grammatical structures. The theoretical framework integrates data-driven learning (DDL), task-based language teaching (TBLT), and interlanguage pragmatics. Drawing on evidence from a pre-/post-test quasi-experimental design, the study demonstrates statistically significant gains in pragmatic awareness, sociopragmatic sensitivity, and targeted grammatical accuracy following task implementation. The findings suggest that multi-corpus task architectures offer a principled and scalable approach to ESP pedagogy, with particular value in contexts where learners require intercultural communicative competence for professional collaboration.
Keywords:
Corpus-driven task design pragmatic competence data-driven learning English for IT TBLT interlanguage pragmatics Sketch Engine COCA MICASEReferences
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