Developing Computational Thinking in Science Education: A Systematic Review of Instructional Approaches, Learning Outcomes, and Implementation Challenges

Abstract

This systematic review identifies approaches, CT dimensions, outcomes and challenges for the implementation of computational thinking (CT) in science education. A systematic review of a curated Scopus dataset of 248 journal articles on CT in science education published between 2016 and 2025 was conducted. 44 studies were selected for the qualitative study, following the PRISMA 2020 guidelines. The findings of this review were obtained by means of a descriptive and inductive thematic synthesis of the selected studies. The results show that in science education, instead of a focus on programming and coding, CT is used as a pedagogical tool for the scientific practices and models of science and for inquiry-based learning of science. A conceptual and functional shift is identified from the four dimensions of CT and from systems thinking and modeling as learning objectives to scientific competences that are used as learning resources for understanding science. The more CT is used as an educational source for experiences of science, the more it can bring about transformations. However, the sustainable implementation of CT is obstructed by the aspect of teacher readiness, the assessment of CT, the curriculum and the capabilities of students. More research is needed that focuses on system support for learning CT in order to ensure sustainable implementation of CT in science education.