The ongoing technological revolution and industrial transformation, represented by artificial intelligence, are profoundly reshaping the global innovation landscape and industrial ecosystem, posing unprecedented systemic challenges to the connotation, model, and goals of university talent cultivation. Higher education must actively adapt to this transformation, not only imparting knowledge but also cultivating students' innovative spirit, critical thinking, high-order problem-solving abilities, and lifelong learning literacy.

In this context, the School of Engineering has launched the "New Engineering Education Frontier" series, featuring the "Bridge Engineering" course, which was recognized as a National First-Class Undergraduate Course by the Ministry of Education in 2023. Led by Professor Wu Ming from the Department of Civil and Smart Construction Engineering, with team members Professor Zhu Zhiwen and Lecturer Yan Shuang, this course emphasizes the integration of theory and practice to cultivate students' ability to solve complex bridge engineering problems through diverse teaching methods, enhancing their comprehensive quality and innovation capabilities.

"Bridge Engineering" is a highly practical, professional core course closely aligned with national design standards, covering a broad range of content essential for developing civil engineering students' engineering capabilities. It aims to cultivate students' flexible and comprehensive application of theoretical knowledge to solve complex engineering problems, with 4 credits and 64 class hours. The course is primarily delivered offline, supplemented by online self-learning. The course learning objectives are outlined in Table 1.

The teaching team has led 9 provincial and ministerial-level teaching reform and quality projects directly related to this course, published 12 teaching-research papers, and released an OBE-based textbook, establishing a comprehensive course website.

The course was recognized as a Guangdong Provincial First-Class Course in 2020, a Guangdong Provincial Ideological and Political Education Demonstration Course in 2021, and its "Bridge Development" chapter was featured as a successful ideological and political education case on Xinhua Net in 2022, with nearly 30,000 cumulative learners. In 2023, it was awarded National First-Class Course status. Team members have won national and provincial teaching competitions, and the team was selected as a Guangdong Provincial Teaching Team in 2019, achieving remarkable reform outcomes.

Through comprehensive analysis, the course identified three key student challenges: difficulty in developing high-order thinking, abstract theory comprehension, and sustained learning motivation. Based on years of teaching practice, the course's pain points are summarized as rigid course structure, outdated teaching philosophy, and singular evaluation methods.

The course has established detailed, measurable learning outcomes, integrating goal, process, and result evaluations. By analyzing past teaching experiences, content, and student feedback, the team streamlined core knowledge, adopting a "mechanical performance-structural design-calculation analysis" framework. Through reduction, adjustment, and addition, the content is better aligned with student, teaching, and course needs, dividing core knowledge into 6 modules. It integrates BIM, smart construction, prefabrication, and other interdisciplinary knowledge, embedding ideological and political elements.

The team published an OBE-oriented textbook, recorded 64 micro-lecture videos on core topics, collected 32 classic online teaching videos (e.g., "Great Engineering" and "Approaching Science"), built a database of 20 engineering case studies and 7 ideological and political case libraries ("Exemplary," "Pride," "Reference," "Warning," "Precision," "Innovation," and "Bridge Red Gene Library"). It also adopted resources from China University MOOC (Southwest Jiaotong University, Li Yadong) and integrated AI models like CivilGPT, DeepSeek, and DouBao.

Content is categorized into basic, key, difficult, practical, and extended problems, using varied teaching methods to achieve the "Two Natures and One Degree," effectively engaging students.

Adhering to "moral leadership, student-centered, industry-education integration, and continuous improvement," the course builds a teacher-student learning community, emphasizing interaction, mutual growth, collaborative innovation, and win-win outcomes. It extends learning from the "first classroom" to "second and third classrooms," creating a blended teaching mode integrating online-offline and in-class-out-of-class activities. Based on Bloom's taxonomy, the ADDIE model (Analysis, Design, Development, Implementation, Evaluation) is implemented to ensure teaching activities precisely meet students' cognitive needs, leveraging information technology to embody "student-centered" teaching.

Based on constructivist principles, the course creates problem scenarios, organizes inquiry activities, and guides students to actively participate, explore independently, reason logically, and summarize. The "Three-Stage Seven-Step" method revolutionizes 45-minute classes by:

Based on constructivist principles, the course builds a practice teaching and evaluation model integrating industry cooperation, adopting the CDIO engineering education concept. It innovates the course design with a progressive, tiered project system supported by two projects (team-based, promoting student collaboration), achieving integrated content, methods, and assessments with industry, while embedding ideological and political elements throughout complex engineering cases.

To address challenges like complex knowledge systems, frequent code updates, and traditional teaching shortcomings, the team introduced CivilGPT (developed by Tongji University for civil engineering), DeepSeek, and DouBao, building a "Teacher-Student-AI" collaborative teaching model. This digital transformation significantly improves teaching and learning efficiency, enabling personalized education.

Centered on moral education, the course explores ideological elements from seven dimensions and integrates them in five ways, creating an immersive ideological teaching framework:

The assessment consists of four modules, including two team projects, based on constructivist principles. For case analysis, scores cover six aspects: engineering analysis and design calculation, computer-aided calculation, overall project work, team collaboration, presentation and defense, and personal qualities, ensuring comprehensive evaluation of students' knowledge, skills, and qualities.

Based on student, course, and teaching analysis, the course adopts OBE teaching philosophy and constructivist teaching perspective, utilizing the ADDIE model, MOOCs, AI, practice bases, and micro-lectures to create an autonomous, cooperative, inquiry-based learning environment. It implements the "Three-Stage Seven-Step" teaching method, integrating online-offline and in-class-out-of-class activities, reflecting disciplinary frontiers, ideological and political education, and innovation strengthening. This builds a "Six Fulls" (fun, passion, interaction, wisdom, challenge, warmth) efficient classroom, enhancing course sophistication, innovation, and challenge. Diversified evaluations guide students to actively "think, discuss, question, practice, explore, and悟道," improving teaching effectiveness and achieving the trinity of knowledge exploration, ability cultivation, and value shaping.

Through six comprehensive innovations, the course successfully addresses its challenges, creating a "Six Fulls" efficient classroom where students progress from learning to thinking, enjoying, and applying knowledge, achieving its goals.