Mapping the Landscape of Computational Thinking on Mathematics Learning in Indonesia: A Systematic Literature Review

Abstract

Computational thinking (CT) is an essential skill of the 21st century and is increasingly relevant in mathematics education. Although many systematizations discuss CT on a global scale, empirical evidence in Indonesia is still limited. Most studies prioritize short-term digital media development (e.g., augmented reality development, e-modules, coding) with a primary focus on cognitive achievement, while the affective domain (such as motivation, attitude, and self-directed learning) is neglected. Meanwhile, the integration of CT in mathematics learning or mathematical literacy, and unplugged activities are rarely studied. This study provides a systematic review of empirical investigations regarding CT in Indonesian mathematics education to produce a comprehensive synthesis. Specifically, it analyzes: (1) theoretical and pedagogical conceptualizations of CT, (2) learning dimensions related to CT (cognitive, affective, and academic outcomes), (3) research methodologies and reported limitations, and (4) applications of plugged (digital/AR/coding) and unplugged (non-digital/game-based) activities. In accordance with the PRISMA protocol, a search was conducted on the national database Scopus. There were 22 published articles in 2018–2025 analyzed. The main findings include: (1) Most studies in Indonesia view CT as a capability with components of decomposition, abstraction, algorithm design, debugging; (2) The dimensions of learning studied are dominated by cognitive dimensions such as problem solving, while the affective dimension is still minimally studied in CT research; (3) The research design used is dominated by qualitative research, while limitations in the research are related to the relatively short research period, limited number of samples, and the absence of standardized instruments; and (4) 85% of the CT studies analyzed tend to use plugged activities by integrating technology.