A critical review of corpus-based pedagogic perspectives on thesis writing: Specificity revisited

Thesis writing (used here as an umbrella term to cover both master's and doctoral postgraduate-level writing) is a high-stakes genre for postgraduate students. This important student genre has been well-researched from a corpus-based perspective. Corpora of theses and also research articles have been used for data-driven learning (DDL) of this key genre. The purpose of this article is to critically examine key DDL initiatives, some of which take a 'research into practice' orientation. Importantly, the discussion is framed around the notion of 'specificity' in the context of needs analysis, and whether the initiatives take a wide-angle, narrow-angle or move from a wide-angle to a narrow angle approach. Accounts which focus on DIY (do-it-yourself) mini-corpus compilation and use by students are also reviewed. The final section of the article presents a critique of current pedagogic applications, taking a closer look at the issue of 'specificity' within the wider context of needs analysis and mapping out areas for future consideration. It is suggested that an ethnographic perspective may be particularly useful for conceptualising specificity relating to students' present situation needs. The article also considers the impact of AI/ChatGPT on future corpus-based pedagogy of thesis writing. (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.