Using data-driven learning approach to enhance EFL learners’ academic speaking skills

Abstract

The application of corpus to language instruction encouraged the use of data-driven learning (DDL). It is assisted by computer technology, and uses authentic language data as the basis for language instruction. Previously conducted studies have paid little attention to the use of corpus tools in speaking instruction. Thus, this study aimed to examine the effects of datadriven learning approach on EFL learners’ speaking skills development. A quasi-experimental research design that employed an interrupted time series design with single group participants was used. The participants were fourth-year EFL major undergraduate students at Mekdela Amba University, Ethiopia. In the intervention, which lasted for six weeks, the participants were taught target language features for speaking via data-driven learning approach. Tests, questionnaires, and the students’ reflective journals were used to collect the data. ANOVA and a one-sample t-test were used to analyze the quantitative data, while a qualitative analysis was employed for the students’ reflective journals. The findings indicated that the data-driven learning approach improved the speaking skills of EFL students. Additionally, participants felt that data-driven learning was beneficial to their speaking skill development and had positive attitudes on the utilization of DDL approach in speaking instruction. Finally, considering the results, it was recommended that data-driven learning approach ought to be included into EFL speaking instruction.