Data-driven learning (DDL), introduced by Tim Johns (1991), is an inductive approach where learners analyze concordance lines to discover language patterns and rules. It involves corpus-designed activities that provide hands-on experience in working with real data (Bennett, 2010). DDL is grounded in authenticity and autonomy, offering learners access to authentic language data and promoting independent discovery (Timmis, 2015; Liu, 2013). Learners can benefit from this discovery-based approach, enhancing vocabulary retention and promoting autonomy (Gilmore, 2015). DDL also fosters metalinguistic and metacognitive awareness (Aston, 2001; Corino & Onesti, 2019). Notably, teachers act as facilitators, guiding learners in the discovery process and boosting their own confidence (Cobb & Bolton, 2015). Various DDL approaches exist, including identifying, classifying, and generalizing (Johns, 1991); illustration, interaction, and induction (Flowerdew, 2009); Chujo and Oghigan’s (2012) four-stage approach; and Kennedy and Miceli’s pattern hunting and pattern refining (2010).
Corpora’s application in L2 writing instruction includes material development by teachers and direct student use in the classroom (Römer, 2008). DDL can be introduced at different writing stages, benefiting students’ understanding of conjunctions, connectors, and reporting verbs (Tseng & Liou, 2006; Bloch, 2009). More importantly, DDL aligns with the noticing hypothesis, enhancing learners’ lexico-grammatical awareness and inductive language learning (Coxhead & Byrd, 2007; Fauzanz et al., 2022; Yoon, 2011; Yoon & Hirvela, 2004). Recent studies support DDL’s positive effects on writing fluency, accuracy, and error correction (Ahsanuddin et al., 2022; Boone et al., 2023; Samoudi & Modirkhamene, 2020; Luo, 2016; Tono, Satake & Miura, 2014; Eak-in, 2015). Learners become more self-confident and proficient in the learning process (Johns, 1991; Gaskell & Cobb, 2004; Yoon, 2008). Moreover, DDL empowers learners to explore language independently, enhancing their writing skills and promoting lifelong learning (Eak-in, 2015; Gaskell & Cobb, 2004; Yoon, 2008).
2.4 Complexity, Accuracy, and Fluency (CAF) in L2 Writing
Wolfe-Quintero, Inagaki, and Kim (1998) explored the link between second language (L2) writing and CAF measures: complexity, accuracy, and fluency. These measures have become central to L2 writing research (Biber, Gray, & Poonpon, 2011; Khushik & Huhta, 2019; Kyle & Crossley, 2018), reflecting writing quality. CAF is considered a valid indicator of L2 performance (Lu, 2011).