Bridging the Gap: Infusing Natural Science Classes with Computer Science Concepts and Skills

Abstract

As we venture further into an ever-evolving digital society, it has become imperative for schools to adapt and equip future generations with the required skills. Computational Thinking (CT), specifically its algorithmic thinking aspect, plays a significant role in computer science and other sciences, such as biology, chemistry, and physics. It encourages students to reason at multiple levels of abstraction. This ability is particularly useful in natural science, as scientific experiments require critical skills like conceptualization, problem decomposition, and solving or designing structured systems. However, due to organizational and curricular restrictions, these concepts and skills are typically taught separately, leaving it to the learners to connect and apply the acquired skills in the respective context.To bridge this gap, we designed a two-day workshop that embeds CT in a physics and sustainability context, namely energy-efficient housing. In this workshop, we employ the Calliope Mini, a micro-controller explicitly designed for educational purposes, to teach essential algorithmic thinking and data processing. We carried out the workshop twice in a primary school in Germany, each with 20 children in 4th grade (ages 9–10). In this experience report, we present the multi-disciplinary workshop idea and discuss the outcome and observations from its execution. Overall, our study demonstrates the potential of such a workshop design as a practical tool for teaching CT concepts to children. Finally, we critically examine the challenges of this approach and highlight the importance of proper technical and educational prerequisites for a successful implementation.