A research-backed guide for faculty — covering AI-resilient frameworks, practical activity redesigns, and institutional policy across disciplines.
What's Inside
Everything is organized so you can jump straight to what you need — whether that's a quick framework reference, assignment redesign ideas, or institutional policy context.
Section 01
The 7 consensus principles every faculty member should know. Start here.
Section 02
AIAS, TACE, Bloom's AI-update, SOLO, Defence in Depth, and Mollick's Jagged Frontier.
Section 03
Redesigned assignments by discipline — Writing, STEM, Social Sciences, Arts & Humanities.
Section 04
CSU, UC, QM, QLT, TEQSA, UNESCO — what the major bodies actually say.
Section 05
The 7 cross-cutting themes that appear across every framework and organization.
Section 06
All 15 frameworks in a single table. Author, type, and best use case at a glance.
Section 07
12 prioritized actions — from immediate syllabus changes to institutional strategy.
Section 08
15 curated links to the tools, frameworks, and organizations cited throughout.
Why It Matters
The global consensus is clear: AI detection tools are unreliable, inequitable, and a losing long-term strategy. The path forward is assessment redesign — and this guide gives you the frameworks to do it.
Authentic, process-visible tasks are more effective and more equitable than any detector.
The learning journey — drafts, reflections, oral defense — is where integrity lives.
Detection tools disproportionately flag non-native English speakers. Redesign is fairer.
Critical, ethical AI use is a graduate competency. Build it into your courses now.
Ready to explore?
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Open Resource Guide