Supporting the Transfer of Computational Thinking in Primary School

In today's digital age, children are not just learning to interact with technology—they're learning to create with it. Whether it's designing a game, building a website, or crafting an animation, primary school students are increasingly engaged in programming activities that hone their ability to solve complex (digital) problems. Central to these activities is the development of computational thinking (CT) , which include breaking down problems, recognizing patterns, and creating step-by-step solutions. Computational thinking has now been included as a formal part of the new Dutch primary school curriculum, reflecting a belief that it can be applied beyond programming contexts to foster problem-solving skills in different subjects, like in mathematics.

But the question remains : Can computational thinking truly be transferred to other subjects, like mathematics? While many educators and researchers believe in the potential for this transfer, there is currently limited evidence to support this claim. This project seeks to address this paucity in the research by exploring the following research question: How can the transfer of CT to untrained programming tasks (near transfer) and mathematics (far transfer) be promoted at the primary school level? To understand this, we will investigate the role of individual differences in the spontaneous transfer of CT and explore how various instructional strategies, such as self-explanation (i.e., where students articulate their thinking process) and analogy-based learning (i.e., where students draw parallels between similar problems) can be used to promote CT transfer. Understanding the individual differences, conditions, and instructional strategies that facilitate CT transfer is crucial for maximizing the potential of CT education for both students and their teachers.

This collaborative project engages closely with schools and educational organizations, ensuring that research findings are not just theoretical but practical and actionable. Through this team effort, we aim to unravel whether CT extends beyond programming. If validated, by the end of this project, we will have identified optimal strategies for teaching CT in a way that supports transfer to mathematics. Educators and policymakers can use these insights for designing effective CT instruction, ensuring students gain valuable cognitive tools for their education and beyond.