The Polemics of Ethical AI Usage in Higher Education – A Case Study Investigating the Axiological Expectations Mismatch

Abstract Book of the 9th International Academic Conference on Education, Teaching and Learning

Year: 2026

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The Polemics of Ethical AI Usage in Higher Education – A Case Study Investigating the Axiological Expectations Mismatch

Mohini Grobler

ABSTRACT:

The philosophical interpretation of institutional expectations in relation to the emerging AI reality poses an axiological expectations‑mismatch problem. This study examines the nature of academic integrity, particularly in the use of AI, in the light of this axiological dissonance. As higher education systems adopt policies and codes of conduct grounded in pre‑AI value structures, students and educators increasingly encounter tensions between traditional conceptions of originality and the practical realities of AI‑augmented learning. This paper argues that current integrity frameworks rely on epistemic and moral assumptions that no longer align with the technological, cognitive, and pedagogical shifts brought about by generative AI. Through a conceptual analysis grounded in value theory, the study interrogates how institutional expectations of authorship, independence, and intellectual labour conflict with emerging student norms of AI‑supported knowledge construction.
Building on literature in ethics, educational philosophy, and digital pedagogy, the paper introduces an axiological expectations‑mismatch model to explain why compliance, interpretation, and enforcement challenges persist despite the proliferation of AI policies. The model highlights three fault lines: (1) divergent value interpretations between institutions and students, (2) inconsistencies between policy rhetoric and practical teaching realities, and (3) unresolved tensions between innovation and regulation. The study concludes by proposing a reconceptualisation of academic integrity that integrates AI literacy, transparent value alignment, and context‑sensitive pedagogical design. Rather than treating AI as a threat to integrity, the paper advocates for a shift toward value‑coherent integrity ecosystems that preserve ethical principles while embracing technological evolution in learning.

Keywords: Axiology; Academic Integrity; Artificial Intelligence; Value Mismatch; Ethics in Education