<![CDATA[This study investigates the global scholarly evolution of AI-integrated pedagogical practices in primary education and proposes strategic pathways for adapting these trends to enhance learning innovation in the Indonesian context. The urgency to align basic education with 21st-century competencies and the accelerating growth of artificial intelligence has created a significant research gap, particularly in translating global pedagogical models into localized applications. Through a bibliometric analysis of 126 peer-reviewed journal articles published between 2014 and 2024 and indexed in Scopus, this study employs the Bibliometrix R-package within RStudio to examine publication growth, source distribution, author collaboration, keyword co-occurrence, thematic mapping, and conceptual structures. Results indicate a sharp increase in research interest beginning in 2021, highlighting emerging themes such as computational thinking, adaptive learning, personalized education, generative AI, and affective computing. These patterns reveal a global pedagogical shift toward data-driven, student-centered, and emotionally intelligent instructional models. When viewed in relation to Indonesia’s Curriculum Merdeka and Society 5.0 ambitions, the findings suggest high potential for contextual integration particularly through CPD programs that enable teachers to apply AI tools like chatbots, self-regulated learning dashboards, and real-time feedback systems in culturally relevant ways. The study concludes that successful adaptation depends on multi-level collaboration, policy support, and iterative design rooted in both global evidence and local realities. By bridging bibliometric insights with educational policy transformation, this research offers a timely and scalable contribution to the discourse on AI in education. It highlights how developing countries can leverage global innovation trajectories to achieve inclusive, future-ready classroom ecosystems.]]>
Copyrights © 2025
