From Permission to Pedagogy

The Structured AI-Guided Education Assessment Policy (Sage-AP) for Generative AI in Higher Education

Bibliographic Data

ID22045502
AuthorsMahmoud Elkhodr (0000-0001-9904-7551, Central Queensland University, corresponding author), Ergun Gide (0000-0003-2258-1910, Central Queensland University)
Year2026
Volume16
Issue6
Pages986
Publication date2026-06-22
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci16060986
OpenAlexW7166358635
LanguageEN
References cited24

Higher education policy on generative artificial intelligence has developed rapidly, yet much of this development remains stronger on governance, permission, disclosure, and assurance than on pedagogy. However, publicly visible institutional approaches appear less developed in providing structured, student-facing workflows that guide responsible AI engagement during assessment completion. This article, informed by a bounded qualitative document analysis, uses the term pedagogical middle layer to describe the process guidance needed between institutional permission settings and academic-integrity or misconduct procedures. Drawing on recent literature and a purposive scan of selected publicly available university policy and guidance documents, the paper argues that current public-facing models are often effective at defining boundaries but less explicit in guiding disciplined, transparent, and defensible forms of human–AI collaboration. In response, the paper presents the Structured AI-Guided Education Assessment Policy (SAGE-AP) as a theoretically grounded policy proposal for AI-assisted assessment, rather than as an empirically validated policy intervention. SAGE-AP frames assessment as a staged process in which students begin from their own understanding, engage with AI critically, document evaluative decisions, refine outputs responsibly, and defend the reasoning represented in the final submission. The paper contributes to institutional policy development by clarifying how permission settings may be complemented by pedagogical process guidance in the generative AI era

Accountability · Acknowledgement · Formative assessment · Generative grammar · Higher education · Permission · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI · Online Learning and Analytics