Pilot Research of AI-Generated Scenarios in Nautical Simulator Training Using ChatGPT Plus

This study presents a pilot research into the use of artificial intelligence (AI) for generating training scenarios in nautical simulators, focusing on their potential to support competency-based maritime training. AI-generated scenarios were created using ChatGPT Plus, following the guidelines of IMO Model Course 1.22 and STCW Convention A-II/1. These scenarios were developed by three scenarists with different levels of maritime expertise and subsequently evaluated by five MET experts. The evaluation process incorporated Multi-Criteria Analysis (MCA) and Intraclass Correlation Coefficient (ICC) to assess scenario complexity, assessment methodology, and compliance with maritime training standards. The study explores the strengths and limitations of AI-generated scenarios and considers the role of expert feedback in refining AI-assisted content. The findings contribute to the ongoing discussion on the applicability of AI in maritime education and highlight directions for further research, particularly in validating AI-generated training scenarios in real-world simulator environments.

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Publication Details

Journal
TransNav the International Journal on Marine Navigation and Safety of Sea Transportation
Published
2025-01-01
DOI
https://doi.org/10.12716/1001.19.01.36
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

Pilot Research of AI-Generated Scenarios in Nautical Simulator Training Using ChatGPT Plus

Ivan Petrović, Igor Stanovčić, Ivan Mrakovic, Vera Kapetanovic et al.
TransNav the International Journal on Marine Navigation and Safety of Sea Transportation
Human-Automation Interaction and Safety
article

Pilot Research of AI-Generated Scenarios in Nautical Simulator Training Using ChatGPT Plus

Ivan Petrović, Igor Stanovčić, Ivan Mrakovic, Vera Kapetanovic, Dejana Pudar
article en

Abstract

This study presents a pilot research into the use of artificial intelligence (AI) for generating training scenarios in nautical simulators, focusing on their potential to support competency-based maritime training. AI-generated scenarios were created using ChatGPT Plus, following the guidelines of IMO Model Course 1.22 and STCW Convention A-II/1. These scenarios were developed by three scenarists with different levels of maritime expertise and subsequently evaluated by five MET experts. The evaluation process incorporated Multi-Criteria Analysis (MCA) and Intraclass Correlation Coefficient (ICC) to assess scenario complexity, assessment methodology, and compliance with maritime training standards. The study explores the strengths and limitations of AI-generated scenarios and considers the role of expert feedback in refining AI-assisted content. The findings contribute to the ongoing discussion on the applicability of AI in maritime education and highlight directions for further research, particularly in validating AI-generated training scenarios in real-world simulator environments.

TransNav the International Journal on Marine Navigation and Safety of Sea TransportationVol. 19(1)
University of Montenegro (ME)
Openalex Percentile: Top 82%
Human-Automation Interaction and Safety
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Pilot Research of AI-Generated Scenarios in Nautical Simulator Training Using ChatGPT Plus — Ivan Petrović, Igor Stanovčić, et al. · TransNav the International Journal on Marine Navigation and Safety of Sea Transportation (2025) | TGRS Research Map | TGRS