生成式AI与交通教育的融合创新路径研究

Research on Innovative Pathways for Integrating Generative AI with Traffic Education

摘要: 生成式人工智能技术的突破性发展为交通教育变革提供了全新动能。通过分析交通教育数字化转型的痛点，构建了生成式AI赋能交通教育的三维应用模型，提出“课程设计–教学实施–评价反馈”全流程创新框架。研究发现，生成式AI通过智能内容生成、虚拟场景构建、个性学习引导等核心功能，在特定试点教学情境下，生成式AI辅助教学在课程参与度、复杂场景训练效率和教学资源配置效率方面分别呈现约32%、45%和60%的改善趋势，体现出其在交通教育数字化转型中的应用潜力。最终构建“知识传授–能力训练–价值塑造”三位一体的智慧教学闭环，推动交通教育向“人机协同、知行合一”范式跃迁，为交通强国建设培养兼具实践能力与家国情怀的新型人才。

Abstract: The breakthrough development of generative artificial intelligence (GenAI) technology provides new momentum for the transformation of traffic education. By analyzing the pain points in the digital transformation of traffic education, this paper constructs a three-dimensional application framework for GenAI-empowered traffic education and proposes an innovative full-process framework covering “curriculum design - teaching implementation - evaluation & feedback”. The study finds that, under the specific pilot teaching context of this study, GenAI-assisted teaching showed approximate improvement trends of 32%, 45%, and 60% in course engagement, complex scenario training efficiency, and teaching resource allocation efficiency, respectively, through core functions such as intelligent content generation, virtual scenario construction, and personalized learning guidance. The ultimate goal is to build a “knowledge transmission-ability training-value shaping” integrated smart teaching closed loop, driving traffic education toward a “human-AI collaboration and practice-knowledge integration” paradigm, and cultivating new types of talents with both practical abilities and patriotism for the construction of a strong transportation nation.