Mapping the Research Trends of Computational Thinking in Mathematics Education: A Bibliometric Analysis

Abstract

Computational thinking (CT) has become an important competency in mathematics education (ME), supporting students’ problem-solving, reasoning, and algorithmic thinking. However, the development of research on CT in ME, including publication trends, influential studies, collaboration patterns, and research themes, has not been comprehensively mapped. This study aims to map the research landscape of CT in ME through a descriptive bibliometric analysis. Publication data were retrieved from Google Scholar, Crossref, and Scopus using the keywords computational thinking, education, and mathematics. After relevance screening, 140 publications from 2016 to 2026 were selected for analysis. Publication trends, citation performance, collaboration networks, and keyword co-occurrence were analyzed using VOSviewer. The findings show a substantial increase in publications since 2020, with the highest output recorded in 2023 and 2024. Citation analysis identifies highly cited studies that have contributed to the conceptual development of CT in ME, while the Journal of Pedagogical Research emerged as the most productive journal. The collaboration network indicates emerging but still limited international collaboration, particularly involving researchers from Sweden, Denmark, and the United Kingdom. Keyword co-occurrence analysis reveals three interconnected research areas: CT implementation in mathematics learning, core CT processes such as decomposition, pattern recognition, abstraction, and generalization, and CT assessment and measurement. The findings show that CT research remains focused on measurement and assessment, while pedagogical approaches, creativity, teacher education, and elementary mathematics education are less explored, highlighting the need for systematic, contextual approaches that connect CT processes with meaningful mathematics learning.