Vol. 2026 No. 1 (2026): 2026 Continuous Issue
Articles

Academic Ghost Models Under AI Scrutiny: Outdated Syllabi and Credential Misalignment in Modern Institutions

Viktor Wang
Bio

Published 2026-02-24

Keywords

  • Academic ghost models, Credential misalignment, Generative artificial intelligence, Curriculum governance, Accreditation compliance, Organizational inertia

How to Cite

Wang, V. (2026). Academic Ghost Models Under AI Scrutiny: Outdated Syllabi and Credential Misalignment in Modern Institutions. International Journal of AI in Pedagogy, Innovation, and Learning Futures, 2026(1). Retrieved from https://journals.calstate.edu/ijaipil/article/view/6951

Abstract

Across higher education, institutions face mounting pressure to demonstrate accountability, ensure regulatory compliance, and protect students from systemic harm. Beneath these demands, “academic ghost models” persist: outdated syllabi, obsolete instructional materials, and misaligned credential frameworks that remain for decades without scrutiny. This article explains how ghost models undermine institutional credibility, erode student trust, and jeopardize accreditation. Recurring patterns in credential programs include reliance on obsolete textbooks and citation standards, misrepresentation of course content and rigor, and retaliatory responses to faculty or student calls for reform. Persistence is not a minor inconvenience; it reflects organizational misconduct. Students may pay graduate-level tuition while receiving undergraduate-level instruction, and institutions risk regulatory sanctions and reputational damage. Administrative inertia, hierarchical protectionism, and suppression of dissent allow outdated structures to endure. Accountability requires proactive curriculum audits, transparent governance, and protections for those who surface deficiencies. Higher education must replace ghost models with rigorous, current, and verifiable academic frameworks. This study synthesizes governance theory and AI policy scholarship to argue that generative artificial intelligence, when responsibly deployed, functions as a structural alignment mechanism that constrains credential conflation and enhances accreditation transparency.

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