Fudan University is actively exploring new pathways for the digital transformation of its quality assurance system, establishing a data-driven, holistic, and multi-dimensional framework for higher education quality assurance, thereby facilitating a transition to data-centric management of undergraduate programs. This system integrates various data sources, including student evaluations of teachers, feedback from teaching supervisors, classroom observations, student-led technological innovations, and teaching operational data, to create precise profiles for undergraduate education. It focuses on five core objectives: enhancing teacher performance, strengthening teacher training, improving course quality, boosting student success, and refining educational management. By conducting in-depth analyses of educational quality across various schools and departments, the system identifies strengths and weaknesses, enabling targeted strategies to enhance the overall quality of undergraduate education.

Furthermore, Fudan University prioritizes the development of personalized teaching profiles. Leveraging AI technology, it analyzes student feedback on teaching to uncover their learning needs and provide educators with tailored recommendations to enhance teaching methods and effectiveness. Building on this, the university has implemented a closed-loop “teaching-evaluation-support” system that customizes professional development plans for educators based on collected data and assigns mentors for personalized guidance, fostering their professional growth.

Additionally, Fudan University’s smart teaching resource platform integrates live-streaming, online education, and teaching evaluations into a single, user-friendly portal. This platform meets students’ demands for open and accessible learning while accelerating the distribution and utilization of high-quality teaching resources.