<![CDATA[Despite the increasing emphasis on Computational Thinking (CT) in primary education, limited research has examined how CT can be systematically developed through mathematics learning trajectories situated in authentic sustainability contexts. This study aimed to design and validated a Computational Thinking Learning Trajectory (CTLT) that integrates four CT practices—Data Practices, Modeling and Simulation, Computational Problem-Solving, and Systems Thinking—through renewable energy optimization projects in primary mathematics classrooms. Using a design research approach, the study was conducted in three phases: preliminary design, teaching experiment, and retrospective analysis. Participants were 30 fourth-grade students (aged 9–10 years) from an primary school in Madiun, Indonesia. Quantitative and qualitative data were collected through observations, interviews, student artifacts, and assessment rubrics to investigate the emergence of CT practices during learning activities. The results, derived from rubric attainment scores and supported by qualitative evidence, showed that all CT practices emerged during learning activities, with Modeling and Simulation (93.3%), Computational Problem-Solving (83.3%), Data Practices (80%), and Systems Thinking (70%) demonstrating substantial levels of attainment. Students demonstrated a progression from arithmetic reasoning toward algorithmic and systems-oriented thinking as they analyzed data, constructed models, evaluated alternative renewable energy solutions, and optimized decision-making processes. The validated learning trajectory provides empirical evidence of how sustainability-based mathematical projects can support the development of CT in primary education. These findings contribute to the growing body of research on CT integration in mathematics curricula and offer practical guidance for implementing project-based learning within the Indonesian Merdeka Curriculum.]]>
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