In the context of the digital economy and industrial digital transformation, the circulation industry continues to see escalating demand for big-data–oriented, multidisciplinary talents. Consequently, the development of interdisciplinary faculty teams has become a key support for enhancing the quality of talent cultivation in new engineering programs. This paper takes the big-data education team at Beijing University of Commerce as a case study. Grounded in the university’s distinctive features in circulation-related education, and centered on the core construction philosophy of “integration of science and education with tiered collaborative efforts,” the paper analyzes the team’s organizational structure from three dimensions: personnel echelon, academic background composition, and functional positioning. It systematically elaborates on four operational mechanisms: mentorship and knowledge transfer by renowned scholars, bidirectional integration of teaching and research, co-creation of interdisciplinary courses, and the integration of industry and competitions into education. The team’s development not only empowers undergraduate talent cultivation but also supports the development of advanced graduate courses and fosters students’ innovation capabilities, thus forming an integrated undergraduate-and-graduate education framework. By drawing on practical achievements across multiple dimensions-including faculty development, curriculum design, student scientific and technological innovation, and employment and further education-this paper summarizes the construction path and experiences of big-data education teams at local universities specializing in circulation-related fields. The study shows that a well-organized age and discipline echelon is the foundation for the team’s sustainable development; the integration of science and education is crucial for enhancing the depth and quality of teaching; and industry-specific characteristics are the core driving force behind the differentiated development of local institutions. These insights can serve as practical references for similar institutions seeking to build interdisciplinary teaching teams.
Big Data Education Team; Tiered Collaboration; Integration of Science and Education; Distinctive Circulation Model; Undergraduate-Graduate Integrated Program.
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