Enhancing Maritime Meteorology Education: Integrating Knowledge Graphs and Learning Analytics in a Professional Course

Maritime Education and Training (MET) faces persistent challenges in structuring complex domain knowledge and integrating fragmented learning resources. This study proposes a systematic approach integrating a domain-specific Knowledge Graph (KG) with learning analytics in the professional course Meteorology and Oceanography for Mariners. The KG, structured according to maritime content logic and cognitive principles, comprises 325 knowledge nodes and is semantically linked to over 1,800 assessment items and 30 instructional videos. Analysis of behavioural data and academic achievement data from 91 undergraduate university students identified correlations between engagement with KG-linked resources and learning proficiency, which enables precise diagnosis of knowledge gaps and data-driven interventions. The findings demonstrate that the KG serves as a central framework transforming traditional assessment into a multi-dimensional, competency-oriented evaluation, effectively interlinking concepts, resources, and learning activities to support personalised feedback and instructional decision-making. The study concludes that the integration of KGs and learning analytics offers a novel and effective methodology for enhancing pedagogical precision and supporting the digital transformation of MET.