Navigating Artificial Intelligence (AI) in Online Learning: Teachers’ Readiness in Focus - Lu'mu Taris; Ruslan; Meili Yanti (Indonesian Journal of Educational Science (IJES), 2026)
The study investigated teachers' readiness to integrate Artificial Intelligence (AI) into online learning environments, with a particular focus on addressing the limited empirical evidence regarding AI readiness among teachers in semi-rural and developing educational environments. While previous research has primarily examined AI literacy and perception in urban or pre-tenured teacher environments, there is still a lack of context-specific understanding of teacher readiness in office, especially in areas with limited technology infrastructure such as Majene Regency, Indonesia. This study examines readiness through three dimensions: conceptual knowledge, technical competence, and professional attitudes towards AI. Using a qualitative descriptive approach, data was collected from fifty high school teachers through document analysis, reflective narratives, and observations to ensure methodological triangulation. These findings suggest that even though teachers show a positive attitude towards AI and recognize its pedagogical potential, their conceptual understanding and technical competence remain. Teachers face challenges in configuring AI tools, interpreting learning analytics, and aligning AI applications with instructional objectives. The study contributes to the literature by providing context-specific empirical evidence on AI readiness in semi-rural educational settings and highlighting the gap between positive attitudes and actual competencies. These findings emphasize the need for practice-oriented professional development, the integration of AI literacy into teacher education programs, and policy support to ensure effective and ethical implementation of AI in online learning.