Operationalising critical thinking in postgraduate disciplinary writing: insights from corpus and cluster analyses of lecturer feedback

Research has revealed that critical thinking (CT) can predict undergraduate academic performance well. It is essential for nurturing students’ unique voice and creativity, especially in the era of Large Language Models (LLMs). LLMs can generate linguistically complex texts, potentially overshadowing students’ authorial voices—particularly those still developing language skills and domain-specific knowledge. Despite this, research on CT within subject education contexts remains scarce, leaving disciplinary lecturers’ expectations of CT in disciplinary writing largely unexplored. Our study analysed a 160,527-word corpus of lecturer feedback on 230 assignments from three education-related postgraduate programs to reveal their shared expectations of CT in disciplinary writing. We identified nine CT constructs, each illustrated with relevant feedback examples. Their intricate interrelationships were revealed through hierarchical cluster analyses. Drawing inspiration from Bloom’s Taxonomy, we established a CT taxonomy to guide effective and consistent assessment of CT. Further studies and practical applications of the CT taxonomy within local educational contexts are needed to develop students’ CT skills and empower them to retain their voice and creativity in an AI-empowered era.