Unpacking research on computational thinking in mathematics education: A systematic literature review - Cut Morina Zubainur; Cut Rina Rossalina; Muhammad Subianto; Dwi Fadhiliani (Jurnal Elemen)
Computational Thinking (CT) is an essential 21st-century skill to prepare students for higher education and future careers. However, comprehensive insights into how CT is effectively implemented in mathematics learning regarding strategies, suitable topics, and integration trends are still limited. This systematic review explores empirical studies on CT in mathematics education from December 2019 to November 2024, sourced from Emerald, EBSCO, and ProQuest databases. Following PRISMA guidelines, 22 articles were selected from an initial 8,518 based on defined inclusion and exclusion criteria. The findings show that CT strongly supports students’ problem-solving skills, particularly through Project-Based Learning (PjBL), which fosters engagement, collaboration, and algorithmic thinking. Geometry and statistics emerged as the most effective topics for developing CT, as they promote decomposition, pattern recognition, and abstraction skills aligned with junior high school cognitive development. Although CT-related research varies in focus, integrating CT into mathematics remains vital, especially with the rise of digital tools and interdisciplinary learning. This review provides insight into current research trends, key strategies, and appropriate mathematical content for CT development. Recommendations include providing CT training for teachers, embedding CT into the curriculum, and encouraging interdisciplinary collaboration to equip students with the digital-age competencies needed for real-world problem-solving and conceptual understanding.