Abstract:

As industries accelerate digital transformation, Institutes of Higher Learning are increasingly challenged to design learning pathways that connect technological capacity-building with sector-specific workforce needs. Building on a successful model developed within the National University of Singapore (NUS), this paper presents an extension: the adaptation of a stackable Applied Data Science (ADS) pathway for the maritime industry. The NUS model originally emerged from the university’s Data Literacy Programme (DLP) for NUS Executive & Administrative (E&A) staff and has evolved into a pathway leading from stackable micro-credentials to the Master of Science in Applied Data Science for working professionals, published in EduLearn2025 proceedings (doi: 10.21125/edulearn.2025.2078). The maritime adaptation extends this model beyond NUS’s internal workforce learning and development into an industry partnership context, demonstrating how a university can translate an educational innovation into a sector-relevant continuing education ecosystem.

Co-developed with the Singapore Maritime Foundation (SMF) and the Maritime and Port Authority of Singapore (MPA), the pathway is tailored to meet the upskilling needs of working professionals in a sector where data-informed decision making is becoming increasingly important. The programme adopts a staged, stackable structure comprising Executive Certificates, Graduate Certificates, a Graduate Diploma, and eventual progression to the Master of Science in Applied Data Science. Its modular design allows learners to enter through the Foundation Executive Certificate, accumulate credits progressively and advance at a pace aligned with work and personal commitments.

Our paper reports on the implementation of the Foundation in Data Analytics Executive Certificate for the maritime industry, which has run across three cohorts including a pilot run, attracting learners from different parts of the maritime sector. Learner feedback suggests that the programme has benefitted maritime professionals with limited prior exposure to formal data-related training while generating immense interest in advancing their data analytics skills. This has advanced the rollout of the next stage, the Executive Certificate in Intermediate Applied Data Science, which marks the first progression step beyond foundation-level participation.

Another key contribution of this paper is its account of curriculum customisation for maritime use cases. Rather than transplanting a generic data science curriculum, the pathway contextualises applied data science concepts and tools to maritime operations and business setting. The curriculum is guided by andragogical principles and approaches that, value adult learners’ needs; leverage on their prior workplace experiences; foster active, problem-centred participation in their learning journey.

This design seeks to preserve academic rigour while increasing relevance and motivation for adult learners in industry. In doing so, our paper offers a practice-based case of how education in data analytics and technology can be intentionally designed for sectoral relevance, learner progression and scalable impact.

Keywords:

Continuing education and lifelong learning, applied data science, workforce reskilling and upskilling, curriculum design and contextualisation, andragogy.