A Multi-Agent Framework for Democratizing XR Content Creation in K-12 Classrooms
This addresses the problem of limited XR adoption in K-12 education due to technical and safety challenges, offering a practical solution for teachers, though it appears incremental as it builds on existing multi-agent and XR concepts.
The paper tackles the high technical barrier and safety risks of using generative AI for XR content creation in K-12 classrooms by presenting a multi-agent framework that coordinates specialized agents for pedagogical design, content assembly, safety validation, and educational enrichment, resulting in a teacher-facing system that requires no technical expertise and works on commodity devices.
Generative AI (GenAI) combined with Extended Reality (XR) offers potential for K-12 education, yet classroom adoption remains limited by the high technical barrier of XR content authoring. Moreover, the probabilistic nature of GenAI introduces risks of hallucination that may cause severe consequences in K-12 education settings. In this work, we present a multi-agent XR authoring framework. Our prototype system coordinates four specialized agents: a Pedagogical Agent outlining grade-appropriate content specifications with learning objectives; an Execution Agent assembling 3D assets and XR contents; a Safeguard Agent validating generated content against five safety criteria; and a Tutor Agent embedding educational notes and quiz questions within the scene. Our teacher-facing system combines pedagogical intent, safety validation, and educational enrichment. It does not require technical expertise and targets commodity devices.