Using Data-Driven Learning for Second Language Academic Writing Acquisition

Abstract

Corpus linguistics is a rapidly growing subfield in linguistics. Correspondingly there is more corpus data available than ever before. Existing corpora can be used to assist teachers in helping their students learn how language is used in a natural setting. While there are several studies on data-driven learning in the field, very few studies have reviewed the overall effectiveness of this teaching method concerning different language contexts and structures. To fill this gap in the literature, this synthesis paper aimed to describe the different ways corpus data is used for data-driven learning in a second-language academic setting. Additionally, this paper evaluated the effectiveness of using data-driven learning techniques for various English language contexts.