DATA-DRIVEN LEARNING FOR COLLOCATION DEVELOPMENT IN SECONDARY EFL CLASSROOMS: THEORETICAL FOUNDATIONS AND PRACTICAL IMPLICATIONS

Abstract

Collocations – conventional word combinations such as make a decision or heavy rain – are a key to accurate and natural use of English, yet secondary school learners rarely receive systematic instruction in them. This article reviews the theoretical foundations of data-driven learning (DDL) and examines its suitability for developing collocational competence of upper-grade (grades 8–9) EFL learners. Drawing on research in corpus linguistics, the lexical approach and the noticing hypothesis, the paper identifies the mechanisms through which corpus consultation supports collocation learning and discusses the constraints of using DDL with younger, lower-proficiency learners. It concludes that DDL becomes effective at secondary level when corpus tools are learner-friendly, tasks are guided and closely linked to the textbook, and the teacher acts as a facilitator.