Challenges and Adaptive Solutions in Managing Artificial Intelligence-Based Learning in Elementary Schools

Abstract

Artificial Intelligence has become an important educational innovation, yet its sustainable implementation in elementary schools remains constrained by various organizational and pedagogical challenges. Existing studies have predominantly examined AI from the perspectives of technology adoption and instructional effectiveness, while limited attention has been given to how schools systematically manage implementation challenges. This study aims to explore the challenges encountered in managing AI-based learning and to examine the adaptive solutions implemented by SD Negeri Kebonsari 3 Malang. A qualitative case study design was employed using interviews, observations, and document analysis. Data were analyzed through the interactive model of Miles et al., while trustworthiness was established using Lincoln & Guba's criteria. The findings reveal five interconnected dimensions of adaptive AI-based learning management: (1) infrastructure challenges addressed through strategic resource optimization; (2) teacher readiness strengthened through collaborative professional learning within the Kedai Kosaga Program; (3) student readiness fostered through responsible AI use and continuous pedagogical guidance; (4) institutional policies that integrate leadership support, professional development, and stakeholder collaboration; and (5) adaptive school management strategies that transform implementation challenges into opportunities for continuous organizational learning. These findings contribute to the literature by proposing adaptive school management as an organizational framework that supports the sustainable implementation of AI-based learning in elementary education.