EduPluginBench provides a staged assurance pipeline that catches self-constructed plugin violations conventional checks miss, while fresh model generations and real Moodle fixes reveal sharp transfer limits.
From Tools to Teacher-Built Teammates: No-Code Pedagogical Plugin Authoring with LearnAdapt Agentic Studio and PedOS 1.1 Lumina
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abstract
Teachers and researchers need to adapt educational AI to local goals, but most systems remain difficult to customize or study without coding expertise. We present LearnAdapt Agentic Studio on PedOS 1.1 Lumina, a no-code authoring and governed runtime environment for educational AI plugins. A non-coder describes a desired learning interaction in plain English; the system prepares a previewable plugin artifact, runs safety checks, and supports submission for review. PedOS then deploys approved plugins into a directory for installation. Crucially, telemetry is strictly gated to authenticated users running approved plugins. The demo shows the complete lifecycle from prompt to governed evidence capture, shifting from fixed tools to teacher-built teammates.
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EduPluginBench: Executable Assurance for AI-Generated Educational Plugins
EduPluginBench provides a staged assurance pipeline that catches self-constructed plugin violations conventional checks miss, while fresh model generations and real Moodle fixes reveal sharp transfer limits.