An Agentic AI-Enhanced Curriculum Framework for Rare Earth Elements from K-12 to Veteran Training for Educators and Policy Makers

Satyadhar Joshi

Abstract: This paper presents a comprehensive framework for AI-enhanced curriculum development in rare earth elements (REE) education, addressing critical workforce gaps across K-12, higher education, and veteran transition programs. As global demand for critical minerals escalates amid geopolitical tensions and supply chain vulnerabilities, we propose an integrated educational approach that bridges artificial intelligence with traditional geosciences. Our research analyzes current initiatives, identifies curriculum gaps, and develops scalable AI-enhanced learning models that combine theoretical knowledge with practical applications. The framework encompasses personalized learning systems, virtual reality simulations, and adaptive assessment tools to prepare diverse learner populations for careers in the critical minerals sector. We introduce multiple architectures including an integrated AI platform for the REE value chain, multi-agent systems for mineral exploration, circular economy models for sustainability, and supply chain resilience frameworks. Quantitative analysis demonstrates significant improvements in exploration efficiency, materials discovery timelines, and educational outcomes through AI implementation. The paper also addresses implementation challenges, ethical considerations, and provides strategic recommendations for policy support and investment. This educational framework supports national security objectives while creating sustainable career pathways in an increasingly vital industry, ultimately contributing to domestic workforce development and supply chain resilience in the critical minerals sector.

External IDs:doi:10.20944/preprints202510.1990.v1