Customized maritime education and training path (C-path) for aspiring and current ship navigators
Abstract
This study investigates the design and implementation of a Customized Maritime Education and Training Path (C-Path) for aspiring and current ship navigators by focusing on defining strategies to tailor learning paths to individual needs. Six customization strategies are compared and explored including 1) experience-based approaches that adapt training to students’ self-reported prior knowledge and 2) assessment-driven methods that use diagnostic tools to identify skill gaps and guide targeted instruction, 3) Interest-based customization allows students to align their training with personal career aspirations, while 4) pace-based strategies assumes all learners begin with the same foundational content but progress adaptively according to their individual learning speed. Additional two methods include 5) dynamic-performance customization, which uses real-time monitoring and adaptive algorithms to adjust training content based on learner ongoing performance, and 6) scenario-based customization which tailors learning through simulated real-world challenges. This study evaluates these approaches in terms of their effectiveness, feasibility and alignment with STCW and maritime industry standards, and we hope to present a customized learning path for modernizing maritime education to optimize skill acquisition, enhance safety and support professional growth in an evolving industry.
Keywords: Maritime human factors, maritime safety, maritime education and training
DOI: 10.54941/ahfe1006547
Cite this paper
More from this volume
- Investigating Relationships Between First Solo Hours and Overall Flight Training Performance for Part 141 Flight Students
- Some of our CVR data are missing: 92 airline accidents & incidents 2014–2024
- Mayday, Mayday! - Is Heart Rate Variability a Suitable Objective Indicator to Detect Pilot’s Increased Mental Workload in Emergency Situations?
- Investigating the Acceptance of Vertiport Construction Near Residence Using Technology Acceptance Model (TAM)
- Digital Assistant Concept for Enroute Air Traffic Management
- Triggers and Consequences: A Multidimensional Analysis of the Rebound Effect in Sustainable Design
- User-Driven Strategies to Enhance Cockpit Comfort in New Energy Vehicles
- Flexible Human-Machine Collaboration: The Concept and Case Study of Lunar Surface Exploration Task
- Flight Safety - Alcohol Detection assisted by AI Facial Recognition Technology
- Safety and Human Factors Challenges of Aircraft Berths: Problem Analysis and Optimization Approaches
- Exploring the Impact of Factors on Upper Limb Functional Space and Operational Efficiency: A Theoretical Analysis
- The Implementation of AI in Aviation Accidents Investigations


AHFE Open Access