Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Pembelajaran, Bimbingan, dan Pengelolaan Pendidikan
Siti Rubai’ah
Universitas Pendidikan Indonesia
Education

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
When Digitalizing Education VS Infrastructure Constraints: How School Leadership Manages AI-Based Learning? Nanta Setia Budi; Hawangga Dhiyaul Fadly; Nurdin Nurdin; Siti Rubai’ah; Nanta Setia Budi; Hawangga Dhiyaul Fadly; Nurdin Nurdin; Siti Rubai’ah
Jurnal Pembelajaran, Bimbingan, dan Pengelolaan Pendidikan Vol. 6 No. 5 (2026)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um065.v6.i5.2026.2

Abstract

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.
Co-Authors Hawangga Dhiyaul Fadly Hawangga Dhiyaul Fadly Nanta Setia Budi Nanta Setia Budi Nurdin Nurdin Nurdin Nurdin Siti Rubai’ah