Tag: AI in Education
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LearnAdapt Agentic Studio Selected for Showcase at AIED 2026
LearnAdapt Agentic Studio and PedOS 1.1 Lumina have been accepted to the AIED 2026 Interactive Events Track and selected to be showcased at the 27th International Conference on Artificial Intelligence in Education. This milestone recognises our work on no-code pedagogical plugin authoring, enabling teachers to move from classroom problems to AI teammates they can build,…
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Critsly Selected for Showcase at AIED 2026
We are excited to share that Critsly has been accepted to the AIED 2026 Interactive Events Track and selected to be showcased at the 27th International Conference on Artificial Intelligence in Education. Our submission, “Critsly: An Artefact-Aware AI Critique Teammate for Design Education and Project-Based Learning”, will be featured as part of the interactive programme,…
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The Future of Agentic AI in Education: Co‑designing with Teachers
Agentic AI refers to autonomous systems capable of setting goals, planning and executing multi‑step workflows across educational tools. A 2026 review of 28 studies found that most teacher‑AI collaboration involves AI supporting lesson planning and content generation rather than true co‑design. With analysts predicting that 40 % of enterprise applications will embed specialised AI agents by…
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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,…
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The ES-LLMs Public Sandbox Is Now Live: From Untamed Black Box to Interpretable Pedagogical Orchestration
The ES-LLMs public sandbox is now live. This architecture moves beyond black-box LLM tutors by introducing a deterministic, multi-agent orchestration layer that enforces pedagogical constraints, improves interpretability, and enhances learning outcomes. Discover how structured AI systems can transform adaptive tutoring from opaque responses into auditable, trustworthy educational experiences.