<![CDATA[Researchers systematically examine the profile and characteristics of students' computational thinking abilities when they tackle math problems in algebra and geometry, as computational thinking counts as one of the key competencies in 21st-century math learning that bolsters students' problem-solving skills. This study uses a Systematic Literature Review (SLR) and reviews articles published between 2015 and 2025, so researchers search those articles in databases like Google Scholar, Scopus, ERIC, SpringerLink, and DOAJ with keywords linked to computational thinking and math learning. They base the selection process on inclusion and exclusion criteria, which leads to 12 relevant articles ready for analysis. The results show students' computational thinking skills marked by four main aspects decomposition, pattern recognition, abstraction, and algorithmic thinking and its use in algebra and geometry learning happens via problem-based approaches, algorithmic representations, as well as visualization and simulation activities. Decomposition and algorithmic thinking emerge as the dominant aspects students use, whereas abstraction and pattern recognition pose the biggest challenges, particularly in geometry, and these insights point to the need for more systematic design in blending computational thinking into math learning to strengthen abstraction and pattern recognition so students improve their math problem solving quality.]]>
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