Maritime operations commonly involve multinational crews operating in safety-critical and time-constrained environments. Differences in professional background, training pathways, and prior learning experiences increase the need for training ap-proaches that can accommodate learner heterogeneity while remaining operationally efficient. Learner profiling plays a central role in enabling such adaptive training, but lengthy assessment instruments can increase profiling time and reduce response qual-ity, limiting their practical applicability in maritime contexts. In this study, we intro-duce a data-driven method to develop a 20-item short form of the Felder–Silverman Index of Learning Styles (ILS) tailored for maritime trainees. The responses of 155 experienced seafarers were analysed using the full 44-item ILS questionnaire, and the most descriptive five questions within each dimension were identified using ANOVA F statistics. The resulting 20-item form was evaluated on an independent test set. Across all four dimensions, the short form achieved balanced accuracies of 0.84–0.89 and F1 scores of 0.83–0.96, with the Input dimension performing best (accuracy = 0.89, F1 = 0.96). The proposed short form substantially reduces respondent bur-den while preserving predictive performance, enabling efficient learner profiling and supporting the design of adaptive maritime training.
Tornacı et al. (2026) studied this question.