Cloud-Based Learning Infrastructure Readiness at a Maritime Academy: A Cross-Group Readiness Index Assessment

Abstract

Cloud-based learning infrastructure constitutes an increasingly non-negotiable component of post-pandemic maritime vocational education, yet maritime academies present distinctive infrastructure readiness challenges — including simulation-heavy physical training requirements, high-bandwidth synchronous learning demands, and the need for cloud-accessible content across vessel operations, navigation, and engineering domains — not anticipated by generic higher-education cloud-readiness frameworks. This study develops and validates a maritime-academy-specific Cloud Readiness Index (CRI) and applies it to assess cloud-based learning infrastructure readiness across cadets and lecturers at Sekolah Tinggi Ilmu Pelayaran (STIP) Jakarta. The CRI integrates three dimensions: Infrastructure Access, Digital Cloud Skill, and Institutional Support Perception. Applying the CRI across 60 participants — 30 cadets and 30 lecturers across Port and Shipping Management (PSM), Deck Nautical (DN), and Marine Engineering (ENG) programs — the study documents an overall moderate readiness level (Grand Mean CRI = 3.25/5.00), with Institutional Support Perception as the consistently lowest dimension across all groups (Cadets M = 3.20; Lecturers M = 2.80). Cadets score significantly higher than lecturers on composite CRI (t(58) = 2.14, p = .037, Cohen's d = 0.55), with the lecturer-cadet gap most pronounced on Institutional Support Perception. Between-major ANOVA reveals significant differences (F(2,57) = 3.82, p = .028) with DN recording lowest readiness across both respondent groups. The study contributes a validated, maritime-academy-specific cloud readiness instrument and institutional diagnostic directly informing STIP Jakarta's hybrid learning infrastructure investment priorities.