知识治理视角下高校创新人才培养体系研究：项目式、跨学科方法的协同机制与路径依赖突破

Study on the Innovative Talent Cultivation System in Universities from a Knowledge Governance Perspective: Breaking Path Dependencies through Project-Based and Interdisciplinary Synergy Mechanism

摘要: 在创新驱动发展战略背景下，培养具备复杂问题解决能力的创新复合型人才已成为高等教育的核心议题。然而，项目式、跨学科等有效教学改革在高校的系统性推广，常因其固有的组织结构、管理制度与评价体系所形成的“路径依赖”而步履维艰。本文旨在引入“知识治理”理论作为核心分析框架，系统剖析当前高校创新人才培养体系中的路径依赖困境。研究认为，突破该困境的关键在于进行一场深刻的治理体系重塑。论文构建了一个包含“顶层治理结构、过程协同机制、结果评价体系”的三维知识治理框架，并进一步提出以“增量改革与存量激活相结合、培育‘跨界者’、营造‘实践共同体’”为核心的实施策略。本研究不仅为理解高等教育改革的深层障碍提供了新的理论范式，也为高校管理者推动人才培养模式的系统性变革提供了具有操作性的行动路线图。

Abstract: Against the backdrop of the innovation-driven development strategy, cultivating innovative and compound talents capable of solving complex problems has become a core issue for higher education. However, the systemic implementation of effective pedagogical reforms, such as project-based and interdisciplinary learning, is often impeded by the “path dependence” inherent in universities’ organizational structures, management systems, and evaluation frameworks. This paper introduces “Knowledge Governance” theory as the core analytical framework to systematically analyze the path dependence dilemma within the current university system for innovative talent cultivation. The research argues that breaking this dilemma requires a profound restructuring of the governance system. The paper constructs a three-dimensional knowledge governance framework encompassing top-level governance structures, process-level coordination mechanisms, and outcome-based evaluation systems. Furthermore, it proposes key implementation strategies centered on combining incremental reform with the activation of existing assets, cultivating “boundary spanners”, and fostering “communities of practice”. This study not only offers a new theoretical paradigm for understanding the deep-seated barriers to higher education reform but also provides a systematic and actionable roadmap for university administrators to advance the systemic transformation of talent cultivation models.