Data-driven Learning for Collocation Development in Secondary Efl Classrooms: Theoretical Foundations and Practical Implications
Year: 2026
Type: article
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.
Author: Bahronov Nodirbek Aliyevich
Institution: Bukhara State University
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7224979582