Data Driven Learning Approach: Does it Really Augment EFL Learners’ Speaking Performance?

Abstract

The application of corpus to language instruction encouraged the use of data-driven learning (DDL) approach. Data driven learning approach 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 data-driven learning approach on EFL learners’ speaking skills development. The study employed a pre-test post-test control group quasi experimental research design.  The participants were fourth-year EFL major undergraduate students at Mekdela Amba University who were assigned into experimental group (N= 26) and comparison group (N= 24). In the intervention, which lasted for eight weeks, the participants in the experimental group were taught target language features for speaking via data-driven learning approach, and the non DDL approach or the conventional approach was employed for the comparison group. Tests, questionnaires, and the students' reflective journals were used to collect the data. An independent samples t-test, paired samples t-test and a one-sample t-test were used to analyze the quantitative data, while a qualitative analysis was employed for the students' reflective journals. Consequently, the declarative knowledge test and speaking test results indicated that participants who were instructed via the data-driven learning approach performed better than those who were taught by means of the conventional approach. Additionally, participants in the experimental group 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, in light of the results, it was recommended that data-driven learning approach should be included into EFL speaking instruction.