Randomized trial explores the integration of computational thinking in primary mathematics, enhancing problem-solving skills.
The integration of computational thinking (CT) into mathematics education has attracted increasing attention; however, there is limited methodological clarity about how CT can be systematically embedded in primary mathematics instruction. In particular, empirical research linking CT to multi-step mathematical problem-solving remains scarce. This paper presents the design and implementation of a task-based intervention model developed within the DigiMaths4All project. The model incorporates CT into primary mathematics through a structured framework for task selection and design, combined with implementation in a technology-enhanced learning environment (ViLLE). Mathematical tasks focus on arithmetic fluency and multi-step problem solving, while CT tasks are tailored to operationalize key processes such as decomposition, abstraction, algorithmic thinking, and debugging. The intervention was carried out through a class-based randomized controlled trial in primary education, comparing traditional instruction with technology-supported approaches, including an integrated mathematics CT model. The study uses a mixed-methods approach, incorporating assessments and learning analytics data to examine implementation processes. The main contribution of this paper is methodological. It offers a replicable framework for (1) designing interventions that incorporate CT into mathematics, (2) selecting and constructing aligned task sets, and (3) implementing these tasks within an analytics-driven digital environment. The findings enhance understanding of how CT can be operationalized to support mathematical problem solving in primary education.
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Marika Parviainen (2026) studied this question.
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