Pengembangan Kompetensi AI Guru Madrasah Tsanawiyah dalam Perspektif Manajemen SDM: Studi Multisitus tentang Belajar Mandiri dan Dukungan Organisasi

Abstract

Digital transformation requires Islamic Junior High School (MTs) teachers to master artificial intelligence (AI) competencies despite significant infrastructure and support gaps. This study analyzes MTs teachers' AI competency development from a Human Resource Management perspective, focusing on the interaction between self-directed learning (SDL) and organizational support. A qualitative multisite study was conducted across four purposively selected MTs based on administrative status and geographic location. Data from interviews, observations, and documents were analyzed using the Miles, Huberman, and Saldaña model. Findings reveal four interaction patterns: structured SDL with comprehensive support yields optimal development (MTs A); reactive SDL with transactional support causes uneven achievements (MTs B); collective SDL with collaborative support proves effective despite limited resources (MTs C); and underdeveloped SDL with minimal support leads to stagnation (MTs D). Crucially, visionary leadership, collaborative culture, formal policies, and dedicated learning time are more decisive than mere infrastructure. The study concludes that developing AI competencies requires synergy across individual (SDL), organizational (support), and policy levels. The proposed model posits that SDL without support risks burnout, while support without SDL remains underutilized. Interventions must prioritize reinforcing teachers' metacognitive skills, strengthening principals' roles, cultivating communities of practice, and formulating context-adaptive national policies.