Category: Artificial Intelligence in Education (AIEd)
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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.
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Beyond the Monolith: Why the Future of AI Tutors Requires Specialized Ensembles (And a Pedagogical OS)
The era of the single, monolithic AI tutor is failing. Discover how Ensembles of Specialized LLMs (ES-LLMs) and the newly evolved LearnAdapt platform are creating the safe, governed ecosystems required for the next wave of machine pedagogical intelligence.
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Formalizing Machine Pedagogical Intelligence: Announcing AIED 2026 Acceptance of our “ES-LLMs” Architecture
We are thrilled to announce the acceptance of our latest paper at AIED 2026. This research introduces the ES-LLMs architecture, providing the technical validation for “Machine Pedagogical Intelligence” by replacing monolithic “Black Box” models with a rule-governed, highly efficient team of specialized AI tutors.
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The Architect’s Dilemma: Rethinking Assessment When AI Does the Heavy Lifting
In an hour, I built a production-grade ML app with full documentation—without writing a single line of code. If AI is the mason, students must become the Architects. Here’s why we need to stop grading the product and start assessing the process.