The Meta Linguist

The Emerging Invisibility of Language Development Few concepts have occupied a more central position in language education than error. For more than half a century, errors have functioned as the primary empirical window through which language development becomes visible. Teachers diagnose errors to identify emerging difficulties, learners engage with errors…

By Joanne Nifli-Sakali The accelerated incorporation of large language models (LLMs) into writing pedagogy has unsettled long-standing assumptions about what constitutes proficiency, how feedback functions, and on what grounds assessment claims can be considered valid. While the apparent fluency, coherence, and immediacy of AI-generated feedback have been widely celebrated, such…

Are Generative Models Corpus-Informed — or Corpus-Simulated? 1. Introduction: The Illusion of Corpus Continuity Large language models (LLMs) are frequently described as “trained on vast corpora” and therefore implicitly positioned as extensions of corpus linguistics. In pedagogical discourse, this has led to claims that LLMs provide corpus-informed feedback, corpus-based collocational…

Re-Theorising Professional Competence Under Conditions of Algorithmic Mediation 1. Introduction: Beyond Instrumental AI Literacy Calls for “AI literacy” in teacher education have proliferated rapidly following the emergence of generative large language models (LLMs). However, much of the discourse remains instrumentally framed: teacher trainees are expected to learn how to use…

Re-Theorising Writing Ability Under Conditions of Algorithmic Co-Production 1. The Destabilisation of the Writing Construct The rapid diffusion of large language models (LLMs) into educational contexts has generated widespread discussion about academic integrity, authorship, and pedagogy. Yet beneath these surface concerns lies a more foundational epistemic disruption: the destabilisation of…