<![CDATA[Learning evaluation is a crucial component of the educational process for measuring students’ learning outcomes and the effectiveness of teachers’ instructional strategies. However, conventional learning evaluation still faces various challenges, including teachers’ limited time, potential subjectivity in assessment, and delayed feedback for students. This study aims to develop and implement an Artificial Intelligence (AI)–based learning evaluation system at UPT SDN 2 Panggungrejo to improve the efficiency, objectivity, and quality of learning evaluation. This research employs a Research and Development (R&D) method, which includes needs analysis, system design, implementation, and evaluation of system effectiveness. The theoretical framework is grounded in Constructivist Learning and Adaptive Learning theories, which emphasize conceptual understanding and the adaptation of learning processes to individual students’ needs. The results indicate that the AI-based evaluation system is capable of automatically analyzing students’ learning outcomes, providing faster and more accurate feedback, and assisting teachers in designing more adaptive and data-driven instructional strategies. Therefore, this system has strong potential to enhance the quality of learning evaluation and overall instructional processes in elementary schools.]]>
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