2025 ASEE Annual Conference & Exposition

Background: In the era of digital intelligence, generative AI, digital twins, Beidou communications, and other types of new technologies are alternately emerging, continuing to empower the construction of the modern industrial system and reshape the global economic structure. At the same time, the quality connotation of high-level engineering management talents is expanding into the realm of digital intelligence technology. However, the current engineering management talents’ cultivation concept has not yet been embedded in the digital intelligence capability, the curriculum system and content do not align with the development of digital intelligence technology, and the practical teaching sessions are significantly disconnected from the digital intelligence management application scenarios, which continues to severely limit the quality of talent cultivation. Cultivating high-level engineering management talents capable of utilizing new technologies to creatively address complex engineering problems, organize engineering technology research and development, and achieve management innovation in the digital intelligence transformation era remains a challenge.

Purpose: This study focused on the “Digital Intelligence Innovation and Management” Engineering Doctoral Program, which was jointly established by Z University based on the second-level interdisciplinary of “Digital Intelligence Innovation and Management” and a number of engineering faculties and departments. Based on the concept of “Convergence Education”, this study systematically analyzed the program’s characteristics in terms of cultivation concept, cultivation platform, and cultivation link from three dimensions of knowledge integration, technology integration and domain integration, and distilled its experience in cultivating digital engineering management talents.

Method: This study adopted a single-case study methodology by conducting semi-structured interviews with faculty members, students, and relevant administrators involved in the program, and collecting relevant information from internal channels, official websites, and mainstream media to ensure the authenticity, richness, and completeness of the qualitative data.

Results: Z University has now explored the formation of high-level engineering management talents training features embedded in the ability of digital intelligence, specifically including: firstly, the program establishes the concept of cultivating engineering management talents who possess mastery of “basic theories and knowledge” and the ability of “application of digital intelligence technology + engineering technology innovation and management”; secondly, by integrating advantageous disciplinary resources such as management, medicine, and engineering from University, it has established the “Digital Intelligence Innovation and Management Laboratories” based on a series of major national key projects; thirdly, the program implements a distinctive talent cultivation path involving “cross-discipline + cross-industry + cross-border” approaches, which includes jointly training with first-class disciplines, innovative leading enterprises, and international first-class universities.

Conclusion: This study has the following contributions. Firstly, we presented a distinctive training program of high-level digital engineering management talents. Secondly, although the selected case is from China, the cultivating model derived from the case exhibits strong generalizability and replicability, offering a valuable reference for the global cultivation of digital engineering management talents. Furthermore, this study fills the current research gap in the cross-disciplinary construction of “Digital Intelligence Innovation and Management”.