Toward personalised maritime training: seafarer perceptions of AI-based and traditional feedback

As maritime operations become increasingly dynamic and safety-critical, supporting effective learning and decision-making remains a central challenge in maritime education. Within such training contexts, feedback plays a central role in helping seafarers reflect on their weaknesses. Building on this, this study examines seafarers' perceptions of artificial intelligence (AI)-based feedback in maritime training by comparing three feedback formats following a COLREGs assessment: traditional feedback, AI-generated global performance summaries, and AI-generated personalised feedback at the question level. Forty-nine seafarers evaluated each feedback format across six instructional dimensions: correctness, sufficiency, usefulness, clarity, adaptiveness, and motivational impact.Statistical analysis confirmed that both AI-based feedback approaches significantly outperformed the traditional method by providing more relevant guidance, better addressing individual learning needs, and enhancing the overall instructional value. Participants expressed a clear preference for AI-generated feedback tailored to individual questions, which they described as more motivating, clearer, more informative, and more learner-centred. These findings highlight the potential of AI to deliver scalable, faster, and more cost-efficient feedback to support engagement and learning in maritime training.