Artificial Intelligence-Based Learning Management to Improve the Effectiveness of the Independent Curriculum - Yusman Haris; Jenny Fransiska; Didi Kosmanto; Repi Arianto; Lukman Asha; Sutarto; Fakhruddin; Destriani (Al-Qalam Institue, 2026)
This study aims to examine the contribution of Artificial Intelligence (AI)-based learning management to improving the effectiveness of the Independent Curriculum, which emphasizes flexibility, differentiated instruction, and continuous assessment in authentic educational contexts. Employing a qualitative case study design, data were collected from school leaders, teachers, and academic coordinators involved in curriculum implementation through semi-structured interviews, non-participant observations, and document analysis to explore AI-supported instructional planning, learning implementation, and assessment practices. The findings reveal that AI-based learning management enhances instructional effectiveness by facilitating differentiated learning, enabling real-time monitoring of student progress, supporting evidence-based decision-making, and reducing teachers’ administrative workload. These results demonstrate that AI functions not merely as a pedagogical tool but as an integrated learning management system that strengthens curriculum implementation. The study implies that the strategic integration of AI into learning management practices can support the sustainability and effectiveness of the Independent Curriculum, provided that institutional readiness, clear management strategies, and continuous professional capacity development are adequately addressed