Abstract
Technological advancements have transformed education, prompting innovative approaches like Computer-Based Data-Driven Learning (DDL), which leverages corpus linguistics tools for inductive grammar instruction. This study investigated the effect of DDL on secondary school students' achievement in English grammar, specifically primary auxiliary verbs (BE, HAVE, DO), in Agege, Lagos, Nigeria a context marked by persistent poor performance in national exams due to rote learning and limited technology integration. A quasi-experimental pre-test/post-test non-randomized control group design was employed. The sample comprised 92 intact SSII students (47 in the experimental group, 45 in the control) from two purposively selected public schools. The experimental group received a 3-week teacher-led DDL intervention using the Corpus Mate platform, involving concordance activities for pattern discovery, hypothesis formation, and rule verification on primary auxiliary verbs. The control group followed conventional instruction. Data were collected via the researcher-designed English Grammar Achievement in Primary Auxiliary Verbs Test (EGAPAVT), a 50-item multiple-choice instrument. Pre-test scores ensured group equivalence, and Analysis of Instruction Covariance (ANCOVA) tested the hypothesis at α = 0.05, covarying for pre-test performance.Post-test results showed the experimental group outperforming the control (M = 73.45 vs. M = 51.31), with a significant main effect for DDL: F(1, 92) = 67.515, p < 0.001, partial η² = 0.42 (large effect). These findings demonstrate DDL's potential to improve short-term achievement in grammar for secondary learners in resource-constrained settings. Recommendations include training teachers in DDL tools to enhance pedagogical efficacy, addressing gaps in Nigerian English instruction.
Keywords: Auxiliary Verbs, Computer-based, Corpus Linguistics, Data-Driven Learning, Grammar, Quasi-Experimental Design
