AI赋能航天发射回收分队行动课程教学改革

Teaching Reform of Space Launch and Recovery Unit Operations Course Empowered by Artificial Intelligence

摘要: 航天发射回收分队是实施进出太空的核心力量，其行动能力直接影响着航天任务的成功率。传统的面向初级管理岗位培训的航天发射回收分队行动课程教学中，面临着教学资源不新、教学内容不精、问题研讨不深、教学评估不全面的“四不”问题。随着雨课堂与各类AI工具在教学中的推广试用，探索了综合运用多种AI工具与雨课堂的航天发射回收分队行动课程教学改革，充分运用AI的多模态资源生成、基于知识图谱的教学内容优化、基于逻辑推理的问题链研讨、基于雨课堂的教学过程评估等方法，构建了适应初级管理岗位培训的AI赋能教学新范式，并分析了“教师–AI–学生”认知交互机制、数据安全与伦理，为领域特色专业课程的教学改革提供借鉴。

Abstract: Space launch and recovery units serve as the core force for space access and re-entry missions, and their operational capabilities directly impact the success rate of space tasks. In the traditional teaching of the Space Launch and Recovery Unit Operations course for the on-job training of junior management position, there exist the “four deficiencies”, namely outdated teaching resources, unrefined teaching content, superficial problem discussions, and incomplete teaching evaluation. With the promotion and trial application of Rain Classroom and various AI tools in teaching practice, this paper explores the teaching reform of the aforesaid course by integrating multiple AI tools with Rain Classroom. By fully adopting AI-driven approaches including multimodal resource generation, teaching content optimization based on knowledge graphs, logical reasoning-oriented problem chain discussions, and teaching process evaluation supported by Rain Classroom, it constructs a new technology-empowered teaching paradigm tailored to the training of junior management position. And then analyze the cognitive interaction mechanism of “teacher-AI-student”, as well as data security and ethics, providing a valuable reference for the teaching reform of domain-specific specialized courses.