ENHANCING EFL WRITING SKILLS THROUGH CORPUS-BASED ERROR CORRECTION AND DATA-DRIVEN LEARNING: A PEDAGOGICAL APPROACH

Abstract

This paper explores the application of corpus analysis in identifying and correcting lexical errors
within second language (L2) student writing, focusing on two specific lexical errors identified in a text by an
EFL learner at a UK university. Utilizing corpus data from the British Academic Written English (BAWE)
Corpus, the paper illustrates the efficacy of corpus query techniques in rectifying lexical inaccuracies.
Furthermore, it outlines detailed Data-driven Learning (DDL) activities designed to promote learner
autonomy and enhance lexical accuracy. The paper concludes by discussing the significant pedagogical
benefits and potential challenges associated with the DDL approach, underscoring its role in improving
learners’ writing performance and fostering a cooperative learning environment.