TL;DR
It is argued that higher education should respond through critical AI literacy, process-oriented assessment, preservation of critical time, and institutional governance of epistemic delegation through critical AI literacy, process-oriented assessment, and institutional governance of epistemic delegation.
The analysis argues that AI-generated outputs should not be positioned directly as scientific evidence or verified knowledge, but rather as provisional knowledge claims that require verification that require verification.
It is argued that the solution lies not in more sophisticated surveillance, but in redesigning assessment and evaluation to re-anchor, which erodes human responsibility and epistemic authority by assigning both production and judgment to closely related algorithmic systems.
Generative artificial intelligence (GenAI) is rapidly reshaping engineering education, yet prevailing debates frame its impact narrowly as either pedagogical innovation or epistemic threat. In this article, we argue that such framings misdiagnose the problem by treating GenAI as a tool rather than as a sociotechnical...
This critical-integrative review argues that the central educational question is not whether learners rely on AI, but whether that reliance preserves or displaces the epistemic work through which judgement develops, and proposes relational epistemic agency as the normative aim.
This paper argues that the core problem extends beyond academic dishonesty to a deeper misalignment between assessment practices and the learning outcomes they are intended to measure, and highlights the need for alternative assessment models that emphasize process over product.
This article proposes the Human–AI Pedagogical Agency Framework (HAPAF), composed of five interacting layers: epistemic positioning, learner agency, interaction design, verification, and governance, which reframes effective GenAI integration as an agency-preserving pedagogical design problem rather than a tool-adoption...
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