You are currently viewing a new version of our website. To view the old version click .
Electronics
  • This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
  • Article
  • Open Access

17 December 2025

Curriculum to Immersion: A Conceptual Framework of Artificial Intelligence-Assisted Scenario Generation in Extended Reality for Primary and Secondary Education

and
1
Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
2
Faculty of Engineering in Foreign Languages, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
*
Authors to whom correspondence should be addressed.
This article belongs to the Special Issue Artificial Intelligence for Extended Reality (AI4XR): Advancing Immersive Technologies

Abstract

In this paper, we present a conceptual design framework for developing immersive learning experiences at scale with generative AI and extended reality (XR) for primary and secondary education. Based on the synthesis of current literature, our framework asserts a practical five-step pipeline: curriculum ingestion, AI-powered blueprinting, asset assembly, educator review, and classroom deployment with formative assessment. The model is designed to be flexible, focusing on narrative and gamification for primary students, moving on to sophisticated simulations and analytical activities for secondary students. We place this framework into the context of recent developments in generative 3D models, bridging fundamental technical and ethical gaps between concept and classroom practice. Finally, we summarize a prioritized research agenda around evaluation, access, and teacher workflows to enable near-term pilot studies. This work is intended to inform educators, researchers, and stakeholders who are interested in implementing effective AI-XR solutions in schools in a pedagogically sound way.

Article Metrics

Citations

Article Access Statistics

Article metric data becomes available approximately 24 hours after publication online.