Embedding Generative AI in Curriculum: The SAGE Framework and Evidence-Based Implementation Guide

Live version available on sage-framework.comThe Structured AI-Guided Education (SAGE) framework provides a research-informed, discipline-agnostic method for integrating generative AI responsibly into higher education curricula whilst preserving academic standards, integrity, and critical thinking. This implementation guide is grounded in empirical evidence from seven research studies involving 800+ students across multiple Australian university campuses, with a formative research foundation spanning 1,000+ students. SAGE moves students from passive AI consumption to critical AI orchestration through a six-step cycle (Generate, Evaluate, Refine, AI Critic, Reflect, Defend) and a two-stage pedagogical progression: (1) tutorial-based scaffolded learning with formative assessment, and (2) assessment-driven independent application with supervised assurance. The framework produces graduates who can deploy generative AI as a professional tool within the constraints of their discipline — evaluating its outputs against industry standards, regulatory requirements, and domain-specific evidence. Key Features Evidence-based assessment redesign validated across cybersecurity, systems analysis, data analytics, and additional disciplines Six-step SAGE cycle aligned to Bloom's revised taxonomy, progressing from Apply through to Create with a supervised assurance layer The Defend step: format-agnostic supervised verification of individual competency, with discipline implementation examples across seven fields Student orchestration competency framework with four measurable levels (Passive Acceptor → Selective Adapter → Balanced Integrator → Critical Synthesiser) Supported by 30 references spanning seven core SAGE publications, 15 extended research portfolio studies, and eight foundational frameworks Companion student-facing GenAI literacy module: SAGE 101 — Generative AI Foundations (10 lessons) Target Audience Unit coordinators, course designers, learning designers, academic integrity leads, and educational developers implementing AI-enhanced pedagogy in higher education. The SAGE Ecosystem This guide is part of a growing programme of research, teaching resources, and community infrastructure: Version 1 — Full evidence base, worked discipline examples, rubrics, marking guides, and tutorial templates SAGE 101 — Ready-to-deploy 10-lesson student module on responsible generative AI use SAGE 2026 International Symposium on AI-Guided Education — Q4 2026, hybrid format. Free registration and presentation. Proceedings published in STEM Education SAGE Community of Practice — Launching 2026. Contact m.elkhodr@cqu.edu.au to participate Reuse and Adaptation:This work is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). If you adapt assessment templates or rubrics from this guide, please include the following attribution:"This [assessment/rubric/template] is adapted from the SAGE Framework by Elkhodr & Gide (Central Queensland University, 2026). Original available at https://doi.org/10.5281/zenodo.19479980" SAGE Framework — Official site: sage-framework.com