<![CDATA[This study aims to systematically examine how different instructional strategies influence students’ computational thinking (CT) and mathematical abilities within mathematics education. Employing a Systematic Literature Review (SLR) guided by the PRISMA framework, this study analyzed 13 peer-reviewed articles published between 2020 and 2025 that met predefined inclusion criteria. The reviewed studies were selected using Publish or Perish software and primarily sourced from Google Scholar and Scopus-indexed journals. The analysis focused on research trends, methodological approaches, educational levels, geographical distribution, subject matter, and the effectiveness of learning strategies in fostering CT and mathematical skills. The results reveal that instructional approaches integrating CT with STEM-oriented models—such as Project-Based Learning (PjBL), the SSCS model, and technology-enhanced learning using augmented reality and digital tools—consistently improve students’ problem-solving, abstraction, and higher-order thinking skills in mathematics. The findings also indicate that learner characteristics, particularly self-efficacy and learning styles, play a significant role in CT development. Most studies were conducted at the junior high school level and were geographically concentrated in Java, highlighting an imbalance in research coverage. In conclusion, this review confirms that innovative, technology-supported, and adaptive learning strategies are effective in strengthening computational thinking within mathematics education. The contribution of this study lies in providing a comprehensive mapping of instructional strategies linked to CT outcomes, offering theoretical insights, methodological guidance, and practical implications for educators and researchers seeking to integrate computational thinking into mathematics curricula more effectively.]]>
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