AI-EMPOWERED TEACHING REFORM AND PRACTICAL PATH EXPLORATION FOR THE “GEOLOGY” COURSE

Abstract

In response to the prevalent issues in traditional geology instruction—namely, the abstract nature of theoretical content, the limited relevance to safety engineering practices, and the insufficient alignment with the talent development demands of intelligent mining engineering—this study focuses on the emerging trends of intelligent mining and geological digitization. It investigates the reform of geology course teaching empowered by artificial intelligence. The proposed reform restructures the course content system, integrates AI technologies to innovate pedagogical models, introduces AI-based intelligent mineral generation techniques, and implements virtual mineral cognition experiments, thereby addressing the deficiencies in traditional experimental teaching resources. By establishing an intelligent teaching system and innovative experimental projects, the conventional rote-teaching model has been effectively transformed, resulting in notable improvements in classroom teaching quality and students’ knowledge internalization efficiency. Students’ competencies in intelligent geological analysis, accurate disaster assessment, and innovative mining engineering practices have been strengthened, alongside enhanced innovative thinking and overall professional proficiency. This reform aligns with the objectives of intelligent mining talent cultivation and offers valuable reference and insights for the intelligent teaching reform of geology courses in mining-related disciplines.