针对当前应用型本科高校网络工程专业普遍存在的产教匹配度低、技术迭代滞后、实践评价维度单一等核心问题,旨在构建“产学研用”深度协同与生成式AI技术赋能的四阶螺旋式实践教学体系,探索破解传统实践教学中技术供给脱节、创新能力培养不足、产教协同机制薄弱的系统性解决方案。通过整合政府、高校与企业三方资源,设计“基础实验—综合实训—项目实战—产业应用”四阶递进路径,形成能力培养闭环。新型实践教学体系显著提升培养质量,本研究提出生成式AI驱动的新工科实践教学范式,为同类专业提供可复制的技术方案与协同机制。

Aiming at the low degree of industry-education matching, lagging technology iteration, single dimension of practice evaluation and other core problems currently prevailing in network engineering majors of applied undergraduate colleges and universities, we aim to build a four-stage spiral practice teaching system empowered by "industry-university-research-use" in-depth synergy and generative AI technology, and to explore ways to solve the problem of disjointed technology supply in traditional practice teaching. By integrating the resources of the government, universities and enterprises, a four-stage progression path of "basic experiment, comprehensive practical training, project battle and industrial application" is designed, forming a closed loop of ability cultivation. This study proposes a new engineering practice teaching paradigm driven by generative AI, which provides a replicable technical solution and collaborative mechanism for similar specialties.