Reconstructing the Teaching System of Engineering Materials for Urban Underground Space Engineering: A Systems Perspective with AI Support

Engineering Materials courses are characterized by dense conceptual content, cumulative knowledge structures, and heterogeneous student learning trajectories. Existing teaching reform studies often focus on isolated instructional techniques or digital tools, while paying limited attention to the systemic organization of learning activities, assessment, feedback, and instructional decision-making. This study proposes a system-oriented teaching framework for an undergraduate Engineering Materials course within an urban underground space engineering program. The framework conceptualizes course instruction as a closed-loop process driven by continuous learning evidence and feedback regulation. The framework was implemented in an undergraduate Engineering Materials course with 50 students over a 16-week semester using a learning management platform. Multiple sources of process data were collected, including platform access records, assignment submissions, weekly quiz performance, pre- and post-course concept assessments, instructor feedback logs, and instructional adjustment records. The results indicate that the proposed framework supported timely instructional regulation and adaptive responses to heterogeneous learning states. Observable improvements were found in student engagement patterns and assessment outcomes across the semester. Mean concept test scores increased from 55.7 to 72.2. Students with lower initial scores gained an average of 22.3 points, compared to 11.8 points for their higher-performing peers. A total of 312 feedback messages were delivered, with a median latency of three days. These improvements were observed in association with the implementation of the framework, although causal attribution is limited by the non-experimental, single-cohort design. The study provides an exploratory case showing that system-oriented teaching design may offer a coherent and practically feasible approach for enhancing engineering education in data-rich instructional environments, while also contributing to the application of systems thinking in teaching reform.