DOI: https://doi.org/10.36347/sjet.2026.v14i06.001

Pages: 281-286

Objective: This study aims to address the structural contradiction between the rapid development of the smart logistics industry and the current talent cultivation model in higher education. It focuses on the practical dilemmas faced by traditional logistics courses, including technological disconnect, scenario lag, and capability gaps. Methods: Taking traditional logistics courses as the research subject, this study analyzes the underlying causes of rigid teaching content, static teaching models, and single-dimensional assessment methods. Based on this analysis, an innovative reform path is proposed, with artificial intelligence serving as the technical engine and project-based teaching as the organizational carrier. Results: The proposed reform framework includes AI-driven dynamic updating of course content, reconstruction of teaching processes through virtual-real integrated scenarios, and competency evaluation supported by multimodal data. These elements form a three-dimensional linkage solution covering teaching content, instructional models, and assessment systems. Conclusion: The research indicates that this reform path has significant theoretical value and practical significance for improving traditional logistics education. It provides an effective approach to cultivating interdisciplinary and application-oriented talents who can meet the demands of the smart logistics era.