Supporting EFL Writing during the Pandemic: The Effectiveness of Data-Driven Learning in Error Correction

Abstract

The COVID-19 pandemic continues to pose challenges to the teaching and learning of English as a foreign language (EFL) around the globe, including China. Through online instruction, data-driven learning (DDL), a pedagogical tool that extracts concordances of authentic language examples from specific corpora, can be seen as a powerful resource for helping learners deal with their EFL writing errors during the lockdown. This paper examines the effects of DDL on students’ EFL writing accuracy considering four specific error types and shows how students, as well as teachers, perceive this learning method. Four students and their English teacher in a Chinese university participated in this study. Students were required to complete six writing tasks electronically, which were later revised for four most frequent lexico-grammatical errors under the conditions of using (a) typical referencing resources, (b) DDL material only and (c) the combination of two. Online error correction spreadsheets and stimulated recall were used to investigate students’ error correction preferences and processes, while the online questionnaire and interview were used to retrieve students’ and their teacher’s perceptions of DDL-mediated error correction. The qualitative data analysis revealed that DDL material supported activation of students’ prior knowledge and helped them learn appropriate language use by utilising a series of cognitive strategies. Participants highly appreciated the advantages of DDL-mediated writing activities, although some reservations were made about their practices which warrant further investigation.