Innovation in Language Learning

Edition 18

Accepted Abstracts

Corpus Linguistics and the Identification of Linguistic Patterns and Meanings: Insights from Learners’ Practices

Joana Aguiar, Centro de Investigação Transdisciplinar em Educação e Desenvolvimento (CITeD) -Instituto Politécnico de Bragança (Portugal)

Abstract

This paper explores the potential applications of corpus linguistics in English Language Teaching (ELT), specifically in resolving collocations and identifying instances of semantic change. The application of corpus linguistics to language learning has been proven to be successful and to have a positive impact on L2 students [1]. Corpus analysis also brings to their attention words or phrases that students might not have accessed via intuition or direct grammatical transposition from L1 [2]. Prior research has identified the use of collocations as a strong indicator of L2 proficiency [3]. To assess which online resource best suits students’ needs when using a specific structure and simultaneously helping them write and speak English more naturally. By integrating activities involving corpus linguistics, students get familiar with useful resources in English language learning. Furthermore, these activities are student-centred and thus have a positive impact on language learning. Students also evaluated which platform was more efficient in problem resolution. The five online resources/platforms used were an online dictionary – Cambridge Learner’s Dictionary, OZDIC, SKELL, UrbanDictionary, and the British National Corpus website. Results show that students evaluate activities involving corpus linguistics very positively, as they are allowed to explore online resources autonomously and integrate explicit knowledge through this process.

Back to the list

REGISTER NOW

Reserved area


Indexed in


Media Partners:

Click BrownWalker Press logo for the International Academic and Industry Conference Event Calendar announcing scientific, academic and industry gatherings, online events, call for papers and journal articles
Pixel - Via Luigi Lanzi 12 - 50134 Firenze (FI) - VAT IT 05118710481
    Copyright © 2025 - All rights reserved

Privacy Policy

Webmaster: Pinzani.it