JCERJournal of Contemporary Educational Research2208-84662208-8474Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jcer.v9i11.12945ArticleApplication of AI and Digital Twin Technology in Practical Teaching of Geological Hazard Courses: Taking Earthquake Disaster as an Examplehttps://artdesignp.com/journal/JCER/9/11/10.26689/jcer.v9i11.12945YangZhiquan,GongYaping,LiuHenglin,GuoTingting,YangQiuxia,LiGen,WangQizhong20259112025-12-09In response to the three major contradictions, safety, cognition, and ability cultivation, existing in the practical teaching of geological hazard courses, this paper proposes a “virtual-real integration” teaching reform scheme, using earthquake disasters as an example. By integrating digital twin technology and artificial intelligence technology, a four-layer teaching framework consisting of data layer, model layer, platform layer, and intelligent layer is constructed. Progressive teaching segments of “cognition-simulation-decision-making” are designed to establish a comprehensive training path from seismic geological survey to disaster early warning and decision-making. This scheme shifts the traditional field practice venue to a safe virtual environment, promotes students’ understanding of geological hazards from static fragments to dynamic processes, enhances their comprehensive decision-making ability in geological disaster prevention and mitigation, and provides theoretical support and practical guidance for cultivating interdisciplinary talents in geological hazard prevention.

Wang MX, Fan AL, 2020, Research on Innovative Model of Talent Training for Geological Disaster Prevention and Management. Chemical Minerals and Processing, 49(10): 54–56.

Bai HP, 2016, Brief Discussion on Urban Geological Disasters and Prevention in China, Proceedings of the 25th Annual Conference and Academic Exchange of the Engineering Geology and Subgrade Committee of the China Railway Society Railway Engineering Society, 378–380.

Liu MM, Liao GB, 2025, Teaching Reform of “NC Training” Based on the Construction of New Engineering. Technology Wind, (19): 89–91.

Chen XH, Xu B, 2025, Practical Paths and Realistic Dilemmas of Educational Digital Transformation in the Digital Intelligence Era: Analysis Based on OECD International Experience. E-Education Research, (11): 33–40.

Wang C, Chen X, Yu T, et al., 2024, Education Reform and Change Driven by Digital Technology: A Bibliometric Study from a Global Perspective. Humanities and Social Sciences Communications, 11(1): 1–17.

Wang M, 2024, Research on the Application of Digital Twin Technology in Course Teaching. Science and Technology Economy Market, (06): 143–145.

Wang Y, Gu YC, Chen CJ, et al., 2024, Preliminary Study on the Application of Digital Twin Virtual Simulation Platform in Soil Mechanics Practice Teaching. Mechanics and Practice, 46(01): 188–193.

Li CD, Gu DM, Zhou JQ, et al., 2025, Reform and Reflection on Teaching Methods of “Geological Disaster Prevention” Course under the Background of “Double First-Class” Construction. China Geological Education, 34(04): 44–48.

Cheng SM, Wang YJ, Zhang XC, et al., 2021, Research on Virtual-Real Combined Practice Teaching Mode under the Background of Intelligent Manufacturing. Education Progress, 11(6): 2198–2204.

Sun CH, Li JB, He HZ, et al., 2025, Comprehensive Safety Risk Assessment of Field Geological Practice Teaching Routes in Mountainous Areas: A Case Study of Lianziya Practice Area. Safety and Environmental Engineering, 32(03): 79–89.

Liu HW, Fang HG, Kong XM, 2025, Model Construction and Practical Application of Digital Twin Technology Empowering Smart Learning. Teaching and Management, (21): 12–18.

Bibri SE, Huang J, Jagatheesaperumal SK, et al., 2024, The Synergistic Interplay of Artificial Intelligence and Digital Twin in Environmentally Planning Sustainable Smart Cities: A Comprehensive Systematic Review. Environmental Science and Ecotechnology, 20: 100433.

Zhao LY, Hu ZB, 2022, Digitalization: Empowering the Construction of Teacher Teams in the Intelligent Era. Educational Research, 43(04): 151–155.

Wang RJ, Li Y, 2025, Intelligent Ideological and Political Education: Digital Transformation of the Paradigm of Ideological and Political Education in the Artificial Intelligence Era. Education Theory and Practice, 45(30): 35–39.

Feng C, Neng Y, Yin W, et al., 2024, Reflections on Teaching Reform of Geological Engineering Graduate Courses Empowered by Artificial Intelligence. Science Education Guide(Electronic Edition), (20): 71–73.