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Abstract
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Writing is a fundamental skill in second and foreign language acquisition that presents unique challenges for learners, particularly in developing lexical diversity. Lexical diversity, which refers to the range and variety of vocabulary used in written or spoken language, is a key indicator of writing quality (Johnson et al., 2016; Laufer & Nation, 1995). However, traditional methods of providing feedback on writing often focus on grammar and structure, neglecting the richness and variability of vocabulary. This gap highlights the need for innovative instructional approaches to enhance lexical diversity in learners’ written narratives (Ma et al. 2022). One promising approach is corpus-driven learning, which utilizes large collections of authentic language data to inform teaching and learning practices. Corpus-driven learning involves the use of linguistic corpora—electronic databases of real-world language—to provide learners with exposure to authentic language use, including word frequency, collocations, and genre-specific features (Flowerdew, 2012). In the context of writing instruction, corpus-informed feedback refers to the application of corpus data to guide learners in improving their lexical choices. Such feedback allows learners to identify overused words, explore synonyms, and understand the contextual appropriateness of their vocabulary choices. For narrative writing, this approach can support learners in developing more varied and contextually accurate vocabulary, ultimately enhancing the quality and coherence of their texts (Yoon, 2016).
Despite the potential benefits of corpus-informed feedback, research in this area remains relatively scarce, particularly in the context of elementary English as a Foreign Language (EFL) learners. Most studies have focused on advanced learners or on other aspects of writing, such as coherence and cohesion (Boulton & Cobb, 2017). Additionally, while lexical diversity has been recognized as a critical component of writing
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