The Construction of Collaborative Mechanisms for Generative Artificial Intelligence Driving the Leapfrog Development of Private College Teachers' Research Capacity
Yuli Yu Zhenzu Li
（Zhuhai College of Science and Technology, Zhuhai Guangdong, 519041)
Abstract: The leapfrog development of the scientific research capabilities of teachers in private universities is generally constrained by three practical shackles: fragmented research time, monotonous research methods, and limited academic resources. Meanwhile, compounded by the dual institutional shortcomings of an imperfect scientific research incentive system and a weak organizational support system, the technological innovation and scenario implementation of generative artificial intelligence provide a brand-new technological path for breaking through this structural scientific research dilemma. However, the full release of technological potential does not simply rely on tool application; instead, it is in urgent need of constructing amulti-dimensional, systematic, and coupled collaborative operation mechanism. Based on the real-world dilemmas in the scientific research development of teachers in private universities, this paper systematically deconstructs the application scenarios and enabling logics of integrating generative artificial intelligence into the entire scientific research process, and constructs a four-dimensional collaborative theoretical model covering technological embedding and enabling, subject capacity advancement, organizational system transformation, and ethical norm governance. The aim is to achieve multi-dimensional process enabling of scientific research activities in private universities by generative artificial intelligence, and to provide theoretical support and practical inspiration for the leapfrog development of scientific research capabilities in private universities.
Keywords: Generative artificial intelligence; Private college faculty; Research capacity; Collaborative mechanism
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