STRATEGI PEMBELAJARAN MATEMATIKA UNTUK MENINGKATKAN COMPUTATIONAL THINKING SISWA: SYSTEMATIC LITERATURE REVIEW
Abstract
Twenty-first century learning demands computational thinking (CT) as a fundamental competency that must be developed through mathematics learning. However, literature synthesizing mathematics learning strategies with CT improvement comprehensively remains limited. This study aims to identify and synthesize effective mathematics learning strategies for improving students’ CT skills through a Systematic Literature Review (SLR) approach. Articles were searched across five academic databases (Scopus, Google Scholar, ERIC, ScienceDirect, and SpringerLink) using the PRISMA protocol, covering the period 2020–2025. From approximately 450 identified articles, 32 met the inclusion criteria and were analyzed using thematic analysis and narrative synthesis. Results revealed that Problem-Based Learning (PBL) is the most dominant and effective strategy, followed by STEM/STEAM and Inquiry Learning. Authentic problembased and collaborative approaches proved most capable of developing CT indicators including decomposition, abstraction, pattern recognition, algorithmic thinking, and generalization. Research trends show a significant increase since 2021, focusing on middle and high school levels. Research gaps were identified in the limited studies at elementary school level and AI-based mathematics learning integration with CT. These findings carry substantive implications for curriculum development and mathematics teacher training in the digital era
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DOI: https://doi.org/10.30601/dedikasi.v10i2.7957
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