The practical dilemmas and solutions of Generative AI empowered undergraduate graduation design
生成式人工智能赋能本科高校毕业设计的现实困境与纾解路径

摘要

生成式人工智能（AIGC）的快速渗透，正重塑着本科毕业设计的写作生态与育人逻辑，也使得这一本科培养体系中的“总关口”面临失范风险。AIGC的嵌入通过赋能前沿性选题、体系化指导、深度性分析和敏捷化反馈，将提升毕业设计的创新性、规范性、学理性与实效性。然而，因传统教学管理评价模式与人机协同新生态之间存在着明显的错位与偏差，AIGC赋能毕业设计的过程中仍面临着能力替代、素养不足、制度滞后、工具失灵等现实挑战。据此，本文分别从理念重塑、制度供给、过程重构、评价革新、保障强化提出针对性的对策建议，力促毕业设计实现从“防止AI”到“善用AI”转变，推动智慧教育科技向善发展。

Abstract

The rapid integration of generative artificial intelligence (AIGC) is reshaping the writing ecosystem and educational logic of graduation design, placing this pivotal component of undergraduate education at risk of losing its standards. By enabling cutting-edge topic selection, systematic guidance, in-depth analysis, and agile feedback, AIGC can enhance the innovation, rigor, academic depth, and practical effectiveness of undergraduate theses. However, due to a significant misalignment between traditional teaching, management, and evaluation models and the emerging human-machine collaborative ecosystem, challenges such as capability displacement, insufficient digital literacy, institutional lag, and tool malfunction persist during the process of AIGC integration. In response, this paper proposes targeted strategies from five dimensions—conceptual reorientation, institutional support, process reconstruction, evaluation innovation, and safeguard enhancement—to promote a shift from “preventing AI” to “leveraging AI effectively”, thereby advancing the ethical development of intelligent education technologies.