Task Design and Intervention Model for Integrating Computational Thinking into Primary Mathematics

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.

Authors

Publication Details

Journal
Informatics in Education
Published
2026-06-16
DOI
https://doi.org/10.15388/infedu.2604.023
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
0.00

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article

Task Design and Intervention Model for Integrating Computational Thinking into Primary Mathematics

Marika Parviainen
Informatics in Education
Teaching and Learning Programming
article

Task Design and Intervention Model for Integrating Computational Thinking into Primary Mathematics

Marika Parviainen
article en

Abstract

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.

Informatics in Education
European Commission, Lietuvos Mokslo Taryba
Quality Education
Openalex Percentile: Top 4%
Teaching and Learning Programming
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