Thinking on the Teaching of Geological Engineering Intelligent Monitoring and Big Data Processing
This paper provides a detailed exploration of the elective course on intelligent monitoring and big data processing in geological engineering,aimed at meeting the needs of industry transformation and upgrading. The study analyzes the main issues in the practical teaching of this course,including significant differences between big data analysis methods and traditional geological engineering courses,as well as high requirements for students'mathematical and physical knowledge. To address these issues,several improvement suggestions are put forward:integrating theory with practice to optimize teaching content;carefully selecting teaching resources with a focus on practical application;fully utilizing the Python ecosystem to strengthen practical teaching;designing practical experimental projects to enhance students'hands-on abilities;and constructing a knowledge network diagram to clarify the course logic. These measures aim to improve the teaching effectiveness of the course and help students better master the skills of intelligent monitoring and big data processing.
Geological engineeringIntelligent monitoringGeological big dataTeaching researchPractical abilityTeaching practice
NETL
NSTL
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