EFL Teachers’ Perceptions of Data-Driven Learning (DDL) in L2 Grammar Teaching

Abstract

Data-Driven Learning (DDL) has been shown to have pedagogical advantages in English language education due to its ability to promote learner autonomy through inductive learning based on corpus data. This study aimed to investigate in-service English teachers’ and university lecturers’ perceptions of learning English conditionals through DDL materials in a computer-based environment in which learners interact with naturally-occurring L2 data from the Corpus of Contemporary American English (COCA) for six weeks. Four main themes arising from the interview results showed mixed opinions regarding the benefits of DDL, with positive responses outweighing the negative. DDL helps expand learners’ grammatical knowledge, allowing them to notice authentic mixed-types of conditionals existing in English and encourages students to learn L2 grammar rules through self-discovery. However, some participants viewed DDL as a challenge as both teachers and learners require ICT skills and specialized knowledge to work with corpus data effectively. Furthermore, school policies and budget concerns are obstacles to DDL implementation as learners need technical support from schools.