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Conceptualizing a Novel Generative Maritime Learning Management System: G-Maritime

  • Istanbul Technical University
  • Azerbaijan State University of Economics

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The maritime industry is undergoing a transformation process along with the sustainable development goals. In this cycle, continuous maritime skill transition has become essential to ensure that seafarers and shore-based professionals remain futureready. It is clearly stated that conventional training solutions are no longer sufficient in developing the maritime workforce. This book chapter introduces G-Maritime as a novel Learning Management System (LMS) founded on Large Language Models (LLM). Conceptualizing the G-Maritime LMS, a retrieval-augmented generation (RAG) system supported with a maritime-specific LLM is provided. Moreover, the system is guided by well-established instructional design techniques (SJT, ADDIE, Bloom) that maximize the benefits of AI integration into learning and assessment environment. Therefore, G-Maritime is fundamentally capable of delivering personalized learning and assessments. In addition to conceptual proposal, the study addresses probable challenges such as compliance, certification, and accessibility. A pilot implementation roadmap is also proposed to test the system. The study offers a valuable insight for trainers, policymakers, industry professionals, and investors seeking to understand and support maritime skill transition with generative LMS solutions. By integrating domain-specific AI capabilities with personalized content delivery, G-Maritime LMS represents a scalable model for future maritime learning ecosystems. G-Maritime has potential to become an accelerator for human-centred digital transformation in global shipping.

Original languageEnglish
Title of host publicationAI, Analytics, and Assessment in Higher Education
PublisherIGI Global
Pages85-112
Number of pages28
ISBN (Electronic)9798337370590
ISBN (Print)9798337370576
DOIs
Publication statusPublished - 24 Sept 2025

Bibliographical note

Publisher Copyright:
© 2026, IGI Global Scientific Publishing. All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 4 - Quality Education
    SDG 4 Quality Education
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  3. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  4. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

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