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Research on Innovative Experimental Teaching Mode of Civil Engineering Materials for Digital and Intelligent Operation and Maintenance of Urban Infrastructure under the Background of Urban Renewal

Author(s)

Yucang Dong, Xin Wang*, Yuan Li

Affiliation(s)

School of Urban Geology and Engineering, Hebei GEO University, Shijiazhuang, Hebei, China *Corresponding Author

Abstract

Traditional experimental teaching of civil engineering materials have limitations including lack of targeted teaching systems, disjointed competence cultivation, and imperfect collaborative mechanisms. Therefore, based on the OBE engineering education concept, this paper conducts systematic research on innovative experimental teaching mode of civil engineering materials. By reconstructing a three-stage and nine-module curriculum system covering the entire process of material performance data collection-operation and maintenance decision-making, designing an open experimental project system of basic verification-comprehensive application-innovative inquiry, constructing a scenario-based collaborative mechanism featuring co-construction of projects, co-training of teachers, and sharing of achievements, and establishing a multi-dimensional dynamic evaluation system integrating process result, competence literacy, and individual team, a four-in-one innovative teaching mode of curriculum experiment collaboration evaluation is formed. This mode effectively addresses the pain points of traditional teaching, realizing the transformation of teaching content from traditional mechanical testing to interdisciplinary integration, teaching mode from cramming-style to independent inquiry, and evaluation method from single summative evaluation to multi-dimensional process evaluation. It significantly improves students’ cross field practical capabilities and engineering literacy in materials digital intelligence operation and maintenance.

Keywords

Urban Renewal; Digital and Intelligent Operation and Maintenance; Civil Engineering Materials; Experimental Teaching Reform; OBE

References

[1]Zhang, L., & Chen, J. (2024). OBE-driven innovative experimental teaching for civil engineering materials with digital twin technology. Journal of Civil Engineering Education, 150(2), 04024001-1 to 04024001-10. [2]Li, M., Wang, X., & Zhao, H. (2023). IoT-enabled data acquisition and AI-based performance prediction in civil engineering materials laboratory courses. Construction and Building Materials, 365, 130123. [3]Wang, H., Liu, S., & Zhang, Q. (2025). Industry-university-research collaboration mechanism for digital intelligent operation and maintenance talent training in urban renewal. Journal of Engineering Education, 114(1), 23-41. [4]Hang, Z. (2023). Fracture properties of a concrete-epoxy mortar interface with precoating treatment applied through image correlation technology. Construction and Building Materials, 347, 128546. [5]Jia, H., Lu, F., & Chen, G. (2025). Knowledge graph-based personalized experimental teaching mode for soil mechanics under OBE concept. Experimental Techniques, 49(3), 187-201. [6]Lu, Y., & Sun, W. (2025). Integration of solid waste recycling modules into civil engineering materials experimental courses for labor education. Education for Chemical Engineers, 20(2), 156-168. [7]Chen, W., Li, J., & Yang, S. (2024). Multi-dimensional dynamic evaluation system for experimental teaching of civil engineering materials in digital era. Assessment & Evaluation in Higher Education, 49(5), 987-1005. [8]Zhao, Y., He, M., & Zhang, L. (2023). Application of BIM and IoT in intelligent construction experimental center for civil engineering education. Automation in Construction, 152, 104987. [9]Liu, T., Wang, Y., & Chen, Z. (2024). LSTM neural network-based concrete carbonation depth prediction: A teaching practice in civil engineering materials. Computers & Education: Artificial Intelligence, 5, 100168. [10]Huang, J., Zhang, H., & Liu, P. (2025). Experimental teaching case design for old bridge bearing material degradation diagnosis under urban renewal. Case Studies in Engineering Education, 8(1), 45-62. [11]Xie, G., Wu, J., & Tang, L. (2023). Intelligent monitoring of urban tunnel lining cracks: A laboratory teaching innovation. Tunnelling and Underground Space Technology, 138, 104892. [12]Yang, C., Zhao, J., & Wang, L. (2024). Disease identification of asphalt pavement in old urban areas: Experimental teaching based on machine learning. Transportation Research Part E: Logistics and Transportation Review, 185, 103245. [13]Zhang, R., Li, H., & Chen, J. (2025). Seismic performance evaluation and reinforcement of masonry structures in old communities: Experimental teaching practice. Earthquake Engineering and Engineering Vibration, 24(2), 312-328. [14]Wang, Q., Zhu, Y., & Gao, F. (2023). Structural health monitoring of large-span old bridges: Integration into civil engineering experimental courses. Structural Health Monitoring, 22(6), 2890-2912. [15]Li, S., Guo, X., & Huang, Z. (2024). Intelligent operation and maintenance management of urban underground utility tunnels: Experimental teaching exploration. Underground Space, 9(3), 410-425. [16]Zhou, G., Liu, M., & Zhang, Y. (2025). Co-construction of experimental project library for urban renewal infrastructure digital operation and maintenance. Journal of Professional Issues in Engineering Education and Practice, 151(2), 04025001-1 to 04025001-9. [17]Xu, D., Chen, L., & Wang, H. (2023). Double-qualified teacher training for digital intelligent operation and maintenance in civil engineering education. Journal of Engineering Education Research, 18(4), 56-72. [18]Song, Y., Li, D., & Zhao, S. (2024). Open experimental teaching reform of civil engineering materials based on online-offline resource integration. European Journal of Engineering Education, 49(3), 456-473. [19]Gu, X., Yang, H., & Li, Q. (2025). Application of smart materials (self-healing concrete) in experimental teaching of civil engineering materials. Materials & Design, 229, 111876. [20]Zheng, B., Wang, J., & Chen, F. (2023). From experience-driven to data-driven: Transformation of civil engineering materials experimental teaching for infrastructure operation and maintenance. Journal of Cleaner Production, 375, 134128.