The effect of data-driven approach to teaching vocabulary on Iranian students’ learning of English vocabulary

Abstract

Corpus-based data-driven learning (DDL) is an innovation in teaching and learning new vocabulary for EFL students. Using teacher-prepared materials obtained from COCA corpus, the goal of the present study is to compare DDL and traditional methods of teaching vocabulary like consultation of dictionary or a grammar book. As such, two intact classes (N = 42) and one intact class (N = 20) who were studying English for Certificate for Advanced English (CAE) comprised the experimental and control group, respectively. Nation’s standardized vocabulary size test was administered as a pre-test to make sure that the participants were at the same level of vocabulary knowledge. During the semester, the learners were exposed to teacher-prepared corpus-based materials from COCA such as display list, synonym, keywords in context (KWICs), and collocate. Moreover, they were asked to do similar searches on their own as homework. A post-test based on the reading passages of their course book (Ready for CAE) was designed and administered at the end of the semester. The results of the study indicated that the learners in the experimental group outperformed their counterparts in the control group. The better performance of the former group can be attributed to the fact that the learners could take a more active role in the learning process in which self-discovery, inductive, and bottom-up processes were emphasized.

Keywords

• data-driven learning
• coca
• vocabulary
• corpus