When Digitalizing Education VS Infrastructure Constraints: How School Leadership Manages AI-Based Learning?
DOI:
https://doi.org/10.17977/um065.v6.i5.2026.2Keywords:
AI In education, Contextualized leadership, Infrastructure constraints, School leadershipAbstract
Artificial intelligence (AI) is increasingly promoted in education, yet its implementation remains uneven, particularly in schools with limited infrastructure. This study examines how school principals manage AI-based learning in infrastructure-constrained settings and how leadership practices are adapted to local realities. The paper aims to analyze the contextual leadership practices of principals in managing AI-based learning in public junior high schools in Aceh Besar, Indonesia, with a focus on vision and local policy, teacher capacity building, infrastructure and resource management, and stakeholder collaboration. Used a qualitative phenomenological design, data were collected through semi-structured interviews, field notes, school documents, and limited observation, and were analyzed using six stages of thematic analysis. The findings reveal four interrelated patterns: AI was positioned as a practical tool rather than a systemic transformation; teacher capacity was developed mainly through internal, practice-based learning; infrastructure limitations shaped adaptive strategies such as offline materials and shared device use; and collaboration with teachers, parents, and school committees became an essential support mechanism. These findings showed that AI implementation in constrained environments does not follow a linear digital transformation model but evolves through incremental, context-driven adaptation. The study concludes that principal leadership in such settings is best understood as contextualized AI leadership, in which infrastructural limitations, teacher capacity, and social capital are integrated into a responsive and sustainable leadership approach.References
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