Computational thinking integrated in school subjects – A cross-case analysis of students’ experiences

Abstract

The integration of computational thinking (CT) into K-12 education offers substantial potential to improve digital literacy and deepen students’ understanding across various subject areas. By embedding computational procedures and solution-oriented approaches into traditional curricula, students can develop essential skills that are critical for thriving in an increasingly digital world. However, the effective integration of CT into subject-specific learning poses challenges for educators, largely due to a lack of training and experience in implementing interdisciplinary instructional strategies. This study explores the impact of integrating CT into K-12 education through diverse instructional approaches, including modelling, storytelling, and unplugged activities. The research examines how students' subject knowledge, CT concepts, and practices evolved under each CT integration practice, as well as their acceptance toward CT integrated lessons. The study was conducted in different subjects, including language arts, biology, and physics, and at different grade levels. The technology acceptance model was used as a theoretical framework to understand students' adoption towards the different integration practices. The study revealed that different CT integration practices yield varying impacts on students' attitudes, particularly in relation to their prior programming experiences. Namely, primary school students with prior programming experience display a higher behavioural intention due to a lack of early biases toward programming. Conversely, secondary school students, less familiar with interdisciplinary approaches, initially show less enthusiasm for future engagement. These insights underscore the need for tailored instructional strategies that consider students' prior experiences and the broader goal of preparing them to contribute to a technologically driven society.