Shantou University College of Engineering Explores a New Smart Architecture Teaching Model: “Dual-Line AI + Dual-Course Synergy”
A new round of scientific and technological revolution and industrial transformation, represented by artificial intelligence, is profoundly reshaping the global innovation landscape and industrial ecosystem, posing unprecedented systemic challenges to the connotation, models and goals of talent cultivation in universities.
University education must proactively adapt to this transformation: it should not only impart knowledge but also focus on fostering students’ innovative spirit, critical thinking, high-level problem-solving abilities and lifelong learning literacy.
Against this backdrop, the College of Engineering has launched the special series
Engineering Frontier in Emerging Engineering Education.
This issue features the new smart architecture teaching model
“Dual-Line AI + Dual-Course Synergy” developed by the team led by Teacher Zhang Cuina from the Architecture Program, Department of Civil Engineering, College of Engineering.
Currently, China’s construction industry is undergoing a profound “digital and green” transformation, creating a growing demand for innovative talents equipped with both disaster prevention awareness and digital design capabilities.
To address the teaching pain points — lack of practicality in
Architectural Disaster Prevention and Safety and insufficient implementability in the senior course
Architectural Design V — Teacher Zhang Cuina’s team responded to the needs of the times and innovatively constructed a digital-intelligent higher education teaching model for architecture (Figure 1).
By reconstructing the teaching system with cutting-edge AI technologies, the model provides strong talent support for the industrial upgrading of intelligent construction.
Breaking Barriers: Targeting Pain Points in Traditional Architecture Education
Traditional architecture education often struggles with complex projects.
On the one hand,
Architectural Disaster Prevention and Safety has long suffered from outdated cases and insufficient practical exposure, making it difficult to translate abstract codes into tangible design practice.
On the other hand, in
Architectural Design V, students frequently produce rigid, poorly implementable designs due to misunderstandings of disaster prevention standards or a lack of scientific tools.
To solve these problems, the Architecture Teaching and Research Section defined the symbiotic relationship between “disaster prevention competence” and “design competence”, aiming to bridge the gap between theory and practice and cultivate students’ digital-intelligent design ability to “apply what they learn”.
Dual-Line Integration: Building a Full-Cycle Digital-Intelligent Empowerment Matrix
The core highlight of the teaching model lies in the integrated mechanism of the AI Teaching Line and the AI Design Line.
AI Teaching Line: Tool-Based, Personalized, Dynamic
The teaching team deeply integrated general large models such as DeepSeek, Zhipu Qingyan, and ideological-political textbook Q&A GPT, together with the XuetangX AI Workbench, to build a 24-hour teaching support system.
The platform features 15 intelligent agent roles including “Digital Teacher”, “Design Client” and “Fire Safety Inspector”, as well as 47 instruction libraries, enabling personalized knowledge delivery and dynamic iteration (Figure 2).
AI Design Line: Full-Cycle Digital-Intelligent Empowerment
The courses linked vertical-domain tools such as Jianzhuxuezhang, Xiaoku AI and Stable Diffusion, reconstructing a full-process AI-assisted design closed loop for architectural scheme planning, generation, optimization and expression.
Students not only generated schemes using AI but also completed parametric disaster prevention simulations (wind environment, light environment, etc.) with Rhino and plug-ins like Butterfly and Honeybee, realizing a paradigm shift from “experience-driven” to “digital-intelligent-driven” design.
Dual-Course Synergy: Deep Integration of Theory and Practice
Supported by AI technologies, the two core courses — Architectural Disaster Prevention and Safety and Architectural Design V — achieved in-depth synergy.
Focusing on key disaster prevention pain points of high-rise public buildings, the teaching team developed a linkage list of “design tasks – disaster prevention knowledge”, realizing seamless integration of knowledge modules and teaching processes.
For instance, during scheme generation, the disaster prevention course provides key codes (fire safety, accessibility, etc.), and the design course completes the initial draft accordingly; in the optimization stage, the two courses jointly build a disaster prevention performance simulation platform for dynamic interdisciplinary parametric interaction.
Meanwhile, the traditional single assessment method was replaced by a “process + comprehensive” evaluation system, which focuses on students’ ability to translate disaster prevention knowledge into design strategies (Figures 4, 5).
Fruitful Achievements: Leading the Digital Transformation of Education
This cutting-edge exploration has greatly stimulated students’ learning enthusiasm and innovative potential.
Data show that within less than four months of operation, the AI teaching platform recorded
2,049 student visits, averaging nearly 54 times per person.
Post-course feedback indicated that students widely recognized the model for effectively saving time and significantly improving professional competence and understanding of AI applications (Figures 6, 7).
To date, the model has been promoted both on and off campus via papers, lectures and other forms (Figure 8).
Relevant courses have also been launched on the platform of the
Guangdong-Hong Kong-Macao Greater Bay Area University Alliance for Online Open Courses.
With outstanding teaching effectiveness, the related teaching innovation achievements have successively won:
Special Award, the 3rd Shantou University Teaching Innovation Competition for Teachers (January 2024)
Third Prize, Guangdong Division of the 4th National University Teaching Innovation Competition for Teachers (April 2024)
First Prize, Shantou University Undergraduate Education and Teaching Achievement Award (September 2025)
Going forward, the College of Engineering will continue to explore typical application scenarios of “AI + Higher Education”, promoting the upgrading of educational informatization from “tool application” to “model innovation”, and cultivating more top interdisciplinary talents equipped with both “disaster prevention thinking + design capability” for the national intelligent construction industry.
Text: College of Engineering
