Generative Artificial Intelligence in Maritime Economic Geography Practice： from the Perspective of the "Double High" Plan's Industry-Education Integration

Abstract

Under the background of the "Double High Plan" to deepen industry-education integration, this research focuses on the teaching reform of the Maritime Economic Geography course, exploring the empowering pathways of Generative Artificial Intelligence. Addressing the pain points in traditional teaching, such as outdated content and insufficient practical experience, the study constructs a "Dual-Driven, Three-Phase Iterative" application model. This model reshapes the curriculum development and implementation process through the synergy of "AI technology" and "industry-education integration." Based on this model, a Project-Based Learning case driven by authentic corporate needs was designed. Students utilized a suite of AI data analysis tools, a domain-specific intelligent agent, and ship maneuvering simulation systems to complete a full decision-making, from route optimization analysis to high-fidelity simulation verification. Practice has shown that the deep integration of Generative AI effectively enhances students' abilities in complex problem-solving, innovative thinking, and adaptability to professional scenarios, providing a systematic solution for dynamic content updating and personalized learning. This research offers an actionable paradigm for the deep integration of artificial intelligence and vocational education teaching.