A Multi-Agent Framework for Democratizing XR Content Creation in K-12 Classrooms

TL;DR

This paper introduces a multi-agent XR authoring framework that simplifies K-12 content creation using GenAI, ensuring safety and pedagogical quality without requiring technical skills.

Contribution

It presents a novel multi-agent system that coordinates content generation, safety validation, and educational enrichment for accessible XR content creation in classrooms.

Findings

Prototype system demonstrates ease of use for teachers.

Content validation ensures safety and pedagogical alignment.

System operates on commodity devices without technical expertise.

Abstract

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.