Tracing the diachronic effects of data-driven learning on lexical complexity in EFL learners’ argumentative writing

Abstract This study investigates the effectiveness of data-driven learning (DDL) in promoting lexical complexity in Chinese English as a foreign language (EFL) learners’ argumentative writing, tracks developmental trajectories, and examines learners’ perceptions. Adopting a quasi-experimental design, one class ( n = 26) received DDL instruction, and the other ( n = 22) received non-DDL instruction. Data were collected using triangulation, including argumentative writing samples from five time points, pre- and post-instruction questionnaires and semi-structured interviews. Results showed that learners in the DDL class significantly improved their lexical complexity, while the non-DDL class experienced declines. Across the five time points, nonlinear trajectories were observed in lexical complexity at the individual learner level. Learners reported positive attitudes toward DDL, though some challenges in corpus use remained. These findings provide empirical support for the effectiveness of DDL in promoting lexical complexity development in Chinese EFL learners’ argumentative writing and provide pedagogical implications for corpus-based writing instruction.