Category: Responsible AI
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Introducing RankCert: When Is Simulation Evidence Strong Enough to Select an AI Tutor?
RankCert tests when simulated learners support selecting one AI tutoring policy—and when structural uncertainty makes abstention the more defensible result.
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Two New Preprints on Auditable Control for Educational AI
Two new preprints connect executable assurance for AI-generated educational plugins with authorisation-aware release control for LLM tutors.
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Now Available: Co-Designing Educational AI — From Purpose to Stewardship
My new book is now available: an evidence-based handbook and practical lifecycle for building educational AI with teachers, students, leaders, administrators, and the wider communities whose learning, work, rights, and institutions it affects.
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Correct Is Not the Same as Learned
AI tutors can help students reach the right answer faster, but correctness alone does not prove durable understanding. As AI becomes more embedded in education, we need to ask whether learners are truly building mastery, or simply performing well with assistance. The future of educational AI should not just optimise for immediate success, but for…
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LearnAdapt PedOS Plugins: From Prompt to Production in a Safe Educational AI Ecosystem
The LearnAdapt PedOS Plugin Lifecycle shows how educational AI plugins can move safely from prompt to production through artefact generation, human review, automated security checks, sandboxed previews, telemetry gating, and versioned publishing. It is a step towards a trusted Pedagogical Operating System where educators, researchers, and developers can co-create AI-powered learning tools without compromising safety,…