Integrating computational thinking into secondary school mathematics teaching: A literature review

Abstract Computational thinking (CT) has established itself as a fundamental skill for the 21st century, driving its integration into various disciplines, especially mathematics. This systematic review of the literature aimed to analyse how the integration of CT has been conceptualized and implemented in mathematics teaching in the context of secondary education. Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) protocol guidelines, a search of scientific databases was conducted, resulting in the selection of 30 relevant articles, coded with high inter‐rater reliability (Fleiss's Kappa = 0.88). The results present a synthesis of the methodological approaches, technological tools and variables evaluated in the articles analysed, revealing a consensus on the positive impact of CT on problem‐solving and algorithmic thinking. However, the analysis shows that this success is not only attributed to technological tools, but to their implementation within active pedagogical frameworks, mainly problem‐based learning. This brings us to draw a key conclusion: the need for a transition in research towards a more holistic approach, such that the effective implementation of CT depends on the synergy between active pedagogy, the intentional and studied choice of tools, and explicit consideration of the socio‐emotional dimension of learning. Context and implications Rationale for this study: This review identifies the key characteristics of research on computational thinking and mathematics learning in K‐12 education. Its primary goal is to support researchers in developing empirical work on computer‐related skills—such as algorithms, decomposition and pattern recognition—within the context of mathematical thinking. Why the new findings matter: Nowadays, it is possible to find bibliographic references to reviews on computational thinking in K‐12, on computational thinking and specific methodologies such as problem‐based learning in K‐12, about computational thinking enhancing STEAM and engineering education, teaching and assessing abstraction in K‐12 computational thinking education or computational thinking in higher education. However, no review has focused on analysing works that address general mathematics learning with the development of computational thinking skills in K‐12 education. Therefore, this work represents an important contribution to the current paradigm of including these skills in the development and learning of students in K‐12 education. Implication: This review highlights the research requirements of the current computational thinking paradigm for its effective inclusion in K‐12 education and the potential it may offer for enhancing mathematics learning. Thus, the discussions and conclusions reached in this literature review may be of great interest to researchers in this field who wish to carry out empirical experiences to connect the development of computational thinking skills and mathematics learning in K‐12 education. It may also be an interesting argument for policy decisions that seek to promote the development of this educational field in order to support investment related to educational innovation in this field.