<![CDATA[This study aims to describe the relationship between computational thinking and science literacy of fifth-grade elementary school students in science learning. This study uses a qualitative descriptive approach. The subjects consisted of a fifth-grade teacher and fifth-grade students selected through purposive sampling. Data collection techniques included observation, interviews, and documentation. The research instruments used were observation sheets compiled based on computational thinking indicators decomposition, pattern recognition, abstraction, and algorithms as well as science literacy indicators including explaining scientific phenomena, using scientific information, connecting IPA concepts to everyday life, and interpreting scientific data. Data validity was ensured through source triangulation and technique triangulation. Data analysis used the Miles and Huberman model, consisting of data reduction, data presentation, and conclusion drawing. The results show that students' computational thinking skills have begun to emerge in science learning activities, particularly in decomposition and pattern recognition, while abstraction and algorithm indicators still require further development. Students' science literacy was also visible in their ability to explain simple scientific phenomena and connect science material to real-life contexts. Computational thinking and science literacy are interrelated: students who think logically and systematically tend to understand science concepts more deeply. These findings indicate that more interactive and contextual science learning is needed to optimally develop both skills.]]>
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