Redesigning mining emergency courses based on bibliometric analysis

As China’s emergency management system continues to evolve, research into mining emergencies has gained momentum, yet gaps persist—including inadequate updates to multi-hazard coupling contingency plans and a lack of diagnostics for grassroots emergency capabilities. This paper employs CiteSpace for quantitative analysis of 1 159 CNKI articles （2003-2024）, revealing three research phases: system establishment, refinement, and intelligentisation. Key frontiers include emergency capabilities, evaluation models, and intelligentisation, yet practical pathways for data-driven enhancement remain underdeveloped. Consequently, a reverse-engineering approach is proposed: ① systematically reconstructing the mining emergency management curriculum framework by introducing three core courses including “AI-Driven Contingency Plan Optimization and Dynamic Drills”; ② developing a three-dimensional practical training model integrating “VR collaborative drills + mine site investigations + corporate defense presentations”. Leveraging the virtual simulation laboratory （featuring 3D interactive, mine-level scenarios） established in 2017, this model adheres to the principle of “combining virtual and real elements, prioritizing real over virtual” to achieve interoperability between virtual exercises and field data. Practical outcomes demonstrate a rise in student rescue plan success rates from 72.3% to 85.6% （p＜0.01）. This research successfully implements metrology-driven curriculum cluster restructuring, establishing a replicable model for peer institutions.