Developmental Evaluation for Strengthening Digital Ecosystem Readiness: A Policy Analysis of Coding and Artificial Intelligence Implementation in Vocational Schools in Bangka Belitung Province, Indonesia

Abstract

The integration of coding and Artificial Intelligence (AI) into vocational education is essential for equipping students with 21st-century digital competencies, yet implementation in remote and island regions like Bangka Belitung archipelago province remains fragmented and unsustainable. This study employs Developmental Evaluation (DE) a real-time, adaptive, and participatory evaluation approach (Patton, 2011) to analyze policy readiness and strengthen the digital ecosystem for coding and AI instruction across vocational schools in the province. Using qualitative methods, including in- depth interviews (n = 26), focus group discussions, classroom observations, and policy document analysis, the research assesses readiness across five core dimensions: (1) policy & governance, (2) human capacity, (3) digital infrastructure, (4) curriculum relevance, and (5) industry–academia partnerships. Findings reveal a critical policy–practice gap: while national frameworks such as the Grand Design for Vocational School Revitalization and Kurikulum Merdeka promote digital literacy, local implementation lacks binding regional regulations, standardized teacher competency pathways, equitable infrastructure distribution, and context-based curricula. Only 24% of ICT teachers had received AI-related training, and AI concepts were rarely taught in practice. Through DE cycles of exploration, collective sense-making, and prototyping, stakeholders co-designed adaptive solutions including a provincial roadmap for digital vocational education, offline AI learning modules via WhatsApp, and micro-innovation grants for teacher-led experimentation. The study demonstrates DE’s effectiveness in fostering adaptive capacity, surfacing systemic barriers, and enabling locally owned, sustainable digital transformation strategies.