Research on the Framework of an Artificial Intelligence-Empowered Lifelong Learning System in the Shipping

Xia Sun () and Zhen Wang
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Xia Sun: Shanghai Maritime Academy
Zhen Wang: Shanghai Maritime Academy

A chapter in Proceedings of the 2026 4th International Conference on Digital Economy and Management Science (CDEMS 2026), 2026, pp 379-385 from Springer

Abstract: Abstract Against the backdrop of intelligent transformation in the global shipping industry, traditional education and training systems have become increasingly inadequate in meeting the dual demands of rapid technological iteration and continuous professional competency development. Grounded in lifelong learning theory, human capital theory, educational ecology theory, and intelligent education theory, this study focuses on the central proposition of how to construct an artificial intelligence-empowered lifelong learning system adapted to the shipping industry context. The study systematically examines four major application scenarios of artificial intelligence technology in maritime education and training: intelligent learning diagnosis and personalized recommendation, virtual simulation and immersive instruction, intelligent assessment and multi-dimensional competency evaluation, and big data monitoring and management of learning processes. Building upon this analysis, the study constructs a five-in-one theoretical framework comprising the Philosophical Layer, Core Layer, Support Layer, Guarantee Layer, and Evaluation Layer, and further delineates five core functional sub-modules. This research addresses the theoretical gap in the systematic integration of lifelong learning principles, artificial intelligence technology, and shipping industry characteristics, thereby providing theoretical foundations and practical references for advancing high-quality talent development in the maritime sector.

Keywords: artificial intelligence; shipping industry; lifelong learning; system framework; intelligent education (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-699-9_40

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