生成式人工智能驱动的智能建造跨学科教育模式创新探索—以武汉大学为例
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武汉大学土木建筑工程学院智能建造系

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国家自然科学基金面上项目


Exploration of the Innovation of Interdisciplinary Education Model for Intelligent Construction Driven by Generative Artificial Intelligence—Taking Wuhan University as an Example
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School of Civil Engineering,Wuhan University

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72171182

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    摘要:

    面对智能建造领域技术迭代加速的现实,传统工程教育体系暴露出诸多短板,难以满足行业对复合型人才的迫切需求。生成式人工智能(GAI)凭借其强大的数据挖掘与分析能力、高度灵活的内容生成能力以及卓越的智能交互特性,为高校教育模式变革提供了新的可能性。以武汉大学智能建造教育改革实践为例,结合大模型技术支撑的学科交叉生态,系统探讨了GAI重塑教育模式的创新途径,分析了GAI在应用过程中可能引发的潜在风险与挑战,并有针对性地提出了相应的应对策略。旨在推动智能建造教育领域的范式转换,促进建筑工程教育向智能化、高效化的方向深入发展。

    Abstract:

    With the rapid development of Generative Artificial Intelligence (GAI) in engineering fields, intelligent construction talent cultivation faces an urgent need for educational transformation. The research constructs a three-dimensional educational innovation system of "technology empowerment-curriculum reconstruction-faculty collaboration" for intelligent construction education from the perspective of GAI empowering engineering education. In the technology empowerment dimension, GAI upgrades the entire teaching process to a human-machine co-creation model through design innovation, virtual-real integrated training, and personalized learning paths. In the curriculum reconstruction dimension, GAI achieves semantic reconstruction of interdisciplinary knowledge elements, technology chain coupling, and dynamic evolution of knowledge ecosystems. In the faculty collaboration dimension, a "double helix" teaching community is established, forming interdisciplinary teaching teams, AI-empowered faculty platforms, and teaching resource regeneration mechanisms. Using Wuhan University's intelligent construction education practice as a case study, implementation paths based on technological maturity adaptability, industry-university-research collaborative closed-loop, digital educational infrastructure, and software supply ecosystems are analyzed. The research also identifies potential risks including technical application boundary ambiguity, faculty transformation resistance, and ethical deficiencies, proposing systematic response strategies from policy regulations, educational resource optimization, and faculty ethics construction. The research results provide theoretical frameworks and practical references for engineering education to address technological changes and cultivate compound talents in intelligent construction.

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  • 收稿日期:2025-03-23
  • 最后修改日期:2025-06-26
  • 录用日期:2025-09-04
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