<![CDATA[This community service program aimed to address the gap between conceptual knowledge and practical implementation ability of elementary school (SD) teachers in coding and artificial intelligence (AI) instruction in Medan City and Deli Serdang Regency. Initial needs analysis revealed that while many teachers possessed basic familiarity with coding and AI terminology, the majority had not independently designed lesson plans incorporating coding activities nor systematically used coding platforms in classroom settings. Partner schools also faced uneven device availability and internet connectivity, alongside weak post-training support structures that hindered the transfer of learning to classroom practice. The intervention applied the IN-ON-IN model with contextual coaching: In Service Training 1 (conceptual and practical workshops using Scratch 3.0, Code.org, and Teachable Machine), On-the-Job Training (classroom implementation with field coaching and telementoring), and In Service Training 2 (reflection and consolidation). The program involved 175 elementary school teachers from both regions, implemented October 2025 through February 2026. Evaluation used an explanatory sequential mixed-methods design: pretest–posttest, classroom observation rubrics, learning artifact analysis, and in-depth interviews and focus groups. Results showed knowledge score improvement from 81% to 95% with reduced standard deviation (3.11 to 1.09), alongside qualitative findings confirming gains in lesson plan design competency and project-based coding instruction for the majority of participants. Persistent barriers included limited devices, intermittent internet access, and time constraints for lesson planning. Recommendations emphasize low-resource module development, expansion of telementoring, and cross-stakeholder collaboration to strengthen school infrastructure.]]>
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