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Continue reading →: Beyond Fluency: How AI Is Reconfiguring the Epistemic Foundations of Writing in Education
The integration of Large Language Models (LLMs) into education is often discussed through the familiar language of disruption, efficiency, productivity, academic integrity, and institutional adaptation. Yet this vocabulary remains inadequate because it treats generative AI primarily as an operational technology rather than as an epistemic force. The deeper issue is…
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Continue reading →: Using Learner Corpora to Audit AI Feedback
The accelerating integration of Large Language Models (LLMs) into writing instruction has produced a methodological paradox that educational linguistics has not yet adequately resolved. While generative systems are increasingly capable of producing fluent, immediate, and rhetorically polished feedback, the empirical foundations upon which such feedback operates remain largely opaque. Most…
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Continue reading →: From Fluency to Fidelity: Reassessing Validity in AI-Mediated Writing Feedback
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…
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Continue reading →: Using Learner Corpora to Audit AI Feedback
Toward an Empirical Criterion for Pedagogical Alignment in AI-Mediated Writing 1.Replacing Plausibility with Evidence The rapid normalisation of generative feedback in writing pedagogy has produced a quiet but consequential shift in evaluative standards. Correctness is increasingly inferred from fluency; pedagogical value is tacitly equated with stylistic polish. Yet neither fluency…
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Continue reading →: LLMs and Corpus Linguistics: Simulation or Distribution?
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…
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Continue reading →: Revision Logs, Prompt Histories, and Process-Based Assessment
Redesigning Writing Evaluation Around Traceable Thinking 1. Introduction: From Product Authenticity to Process Legibility The proliferation of generative AI in writing contexts has rendered traditional product-based assessment epistemically unstable. When fluent texts can be algorithmically generated, the central concern shifts from authorship detection to construct defensibility. Attempts to police AI…
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Continue reading →: Operationalising AI Literacy in Teacher Education:
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…
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Continue reading →: Construct Validity in the Age of Fluent Machines
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…
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Continue reading →: Algorithmic Normativity and the Standardisation of Voice
Do Large Language Models Flatten Rhetorical Diversity in EFL Writing? 1. From Fluency to Norm Production The rapid adoption of large language models (LLMs) in L2 writing pedagogy has largely been framed as a technological enhancement of feedback efficiency and linguistic precision. Yet such framings underestimate the epistemic function of…
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Continue reading →: From Scaffolding to Substitution: When Mediation Collapses in AI-Supported Writing
Reinterpreting the Zone of Proximal Development Under Algorithmic Conditions 1. The Problem of Invisible Replacement The incorporation of generative artificial intelligence into L2 writing instruction is typically articulated through a discourse of pedagogical enhancement: AI is said to assist, augment, scaffold, and optimise. Such terminology, while reassuring, may obscure a…

