Course teaching reform of Principles of Urban Planning driven by competition and empowered by intelligence—A case study of digital renovation of wooden houses

Journal: Region - Educational Research and Reviews DOI: 10.32629/rerr.v8i7.5602

Zhihui SHEN1, Xuanyi CHEN2, Shuchang LIU2, Longbo JIANG3, Daopu JIANG2

1. Fujian Agriculture and Forestry University
2. Fuzhou University of International Studies and Trade
3. Quanzhou Vocational and Technical University

Abstract

Against the backdrop of urban-rural built-stock regeneration and digital transformation, traditional Principles of Urban Planning teaching suffers from theory-practice separation, inadequate engineering training, lagging digital tools and simplistic evaluation. Taking the intelligent construction competition and the wooden house renovation project at Fujian Agriculture and Forestry University as a case, this paper integrates 3D scanning, point cloud modeling, BIM reverse modeling, performance simulation and digital twin into teaching, creating a workflow consisting of project introduction, data acquisition, model construction, problem diagnosis, scheme design, competition defense. It transforms spatial cognition, adaptive renewal, low-carbon decision-making and planning implementation into practical tasks, forming a competition-driven, project-centered, intelligence-assisted, performance-oriented teaching mode. Practice shows it shifts students from rote memorization to problem analysis and from single-scale to multi-scale thinking, improving their digital- modeling, teamwork, decision-making and presentation skills. This approach provides insights for interdisciplinary talent training for urban-rural planning.

Keywords

urban planning; intelligent construction; artificial intelligence; renovation; digital twin

Funding

Fujian Agriculture and Forestry University 2026 AI‑Empowered Teaching Project (No.11426ZK036); Fujian Sci‑Tech Dept Guidance Project (2025Y0037); Fujian Vocational Education Research Project (No.ZJGB2024009

References

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Copyright © 2026 Zhihui SHEN, Xuanyi CHEN, Shuchang LIU, Longbo JIANG, Daopu JIANG

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