<![CDATA[Computational thinking (CT) is a crucial 21st-century skill that enables individuals to think logically, creatively, and structurally. In mathematics, CT plays a vital role in problem-solving and conceptual understanding. This study examines students' mathematical computational thinking abilities in the context of two-variable linear equation systems. This research employs a descriptive qualitative approach involving 32 eighth-grade students. Data collection includes a test comprising four items aligned with CT indicators: decomposition, pattern recognition, abstraction, and algorithms. Additionally, four students were interviewed based on their performance to gain deeper insights into their CT processes. Findings indicate that students' computational thinking abilities significantly improved following the Problem-Based Learning (PBL) approach. High-performing students successfully demonstrated all CT indicators, effectively analyzing problems, identifying patterns, and applying structured solutions. However, students with lower competency levels struggled with problem identification, pattern recognition, and algorithmic implementation, indicating a need for targeted instructional support. The results underscore the importance of integrating CT into mathematics curricula to enhance logical reasoning and problem-solving skills. The challenges faced by some students highlight the necessity of differentiated instruction and scaffolding strategies to support CT development. This study emphasizes the role of PBL in fostering computational thinking in mathematics education. The findings provide valuable insights for educators and policymakers in designing curriculum strategies that align with 21st-century learning demands.]]>
