AI赋能工科专业学位研究生实践创新能力培养——以航天特色应用型高校为例

Research on AI-Enabled Cultivation of Practical Innovation Ability of Engineering Professional Degree Postgraduates—A Case Study of Aerospace Characteristic Application-Oriented Universities

摘要: 针对航天特色应用型高校工科专业学位研究生实践培养中实体资源约束、指导覆盖不足、能力评价单一等痛点，构建“实践场景赋能–指导过程赋能–质量管控赋能–航天特色融合”四位一体的AI赋能提升路径。以某高校土木水利专业学位研究生为对象，开展为期8周的准实验研究。结果表明，AI赋能可显著提升实践成果质量与创新产出，优化导师指导时间结构，同时存在技术依赖、算法偏见等风险。研究提出相应调控策略与推广路径，可为同类高校实践教学改革提供参考。

Abstract: Aiming at the pain points such as entity resource constraints, insufficient guidance coverage and single ability evaluation in the practical training of engineering professional degree postgraduates in aerospace characteristic application-oriented universities, this paper constructs a four-in-one AI-enabled improvement path of “practice scenario empowerment, guidance process empowerment, quality control empowerment and aerospace characteristic integration”. A quasi-experimental study lasting 8 weeks is carried out with civil and hydraulic engineering professional degree postgraduates from a university as subjects. The results show that AI empowerment can significantly improve the quality of practical results and innovation output, optimize the time structure of tutor guidance, and there are also risks such as technology dependence and algorithm bias. The study puts forward corresponding regulation strategies and promotion paths, which can provide reference for practical teaching reform in similar universities.