The influence of data-driven learning on learner autonomy and vocabulary acquisition

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Raghunath Vedantham

Abstract

This study examines the influence of Data-Driven Learning (DDL) on learner autonomy and vocabulary gain in English as a Foreign Language (EFL) classroom. Founded on corpus linguistics, DDL enables learners to handle authentic language data, fostering inductive learning and autonomous exploration. While earlier research has testified to the usefulness of corpus-based teaching in enhancing lexical awareness, few empirical studies have examined its impact on learner autonomy and vocabulary gain in combination. This study follows a quasi-experimental research design with undergraduate EFL students in India, employing integrated quantitative and qualitative data collection procedures. Learners utilised corpus tools to explore word patterns, collocations, and grammatical patterns, facilitating independent learning. The findings demonstrate that DDL enhances vocabulary retention through contextualised linguistic input and fosters autonomy via independent corpus exploration. However, corpus tool navigation and data interpretation concerns indicate the need for structured instructional support. The study contributes to the literature by offering empirical testimony on the dual benefits of DDL, underlining its potential in fostering active learning and long-term vocabulary development. Pedagogical implications of integrating corpus-based teaching in language curricula are discussed, providing insights for language teachers interested in supplementing EFL teaching through DDL.

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How to Cite
Vedantham, R. (2025). The influence of data-driven learning on learner autonomy and vocabulary acquisition . Research Studies in English Language Teaching and Learning, 3(2), 398–410. https://doi.org/10.62583/rseltl.v3i2.83
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