Teach-Primary-Issue-20.1

distance from the full coding environment. This helps children reason logically without being distracted by symbols, colours, or familiar interfaces. This encourages scientific habits; children are encouraged to predict, test, evaluate, and adjust their explanation, and they are engaged in controlled thinking rather than trial-and-error. Cross-curricular thinking When we treat coding as a form of reasoning, children begin to notice patterns that link across the curriculum. They recognise that decomposition in computing mirrors breaking down a multi-step calculation in maths, or isolating variables in a science experiment. They see how abstraction involves focusing on important information and removing unnecessary detail, much like particle models or simplified maps in geography. They begin to appreciate that algorithmic thinking underpins the step-by-step approach they take in practical science or long division.These parallels make computing feel purposeful rather than isolated. When children realise that the thinking they develop in computing strengthens their reasoning in other subjects, confidence grows and misconceptions reduce. Computing unplugged A strong coding sequence often begins away from the computer. In the same way that multiplication and division provide a strong foundation for long division, unplugged tasks reduce cognitive load and develop a clear conceptual foundation before adding the features of a coding environment. When we combine this with the PRIMM approach, we encourage children to form a complete understanding of the concept before moving on to a device. For example: Stage 1: paper-based reasoning Give children three versions of the same code (this could be for any purpose – pick something they’ve encountered before, such as an if/then sequence). Then ask them to compare the three versions, identify the correct one, and explain their reasoning. They might work with abstract diagrams such as the hexagon flow representing network systems. They might predict outcomes using a printed program. Each task slows children down and foregrounds the thinking process. Stage 2: structured prediction tasks After developing a conceptual model, children move to a controlled on-screen environment. A simple program with a variable or loop (such as Scratch or MakeCode) becomes a vehicle for exploring sequence, selection, and repetition. Prediction questions guide their attention. Reflection questions encourage them to refine their explanation. Stage 3: transition to physical computing Once children can explain behaviour in a virtual environment, they move to micro:bit projects such as the stop:bit. This encourages them to think about real-world inputs and outputs. They examine the effect of buttons, sensors, and timing. Their reasoning from earlier tasks becomes a scaffold for handling more complex systems. This progression supports inclusive and accessible computing. It respects the cognitive journey and builds confidence at each stage. TP Karl McGrath is a Year 6 teacher, curriculum task design lead, and computing lead with a passion for blending digital tools into learning. Paper-based debugging Give children three versions of the same code and ask which one will work. Encourage them to justify their choice and identify errors using precise vocabulary. Prediction cards Provide small cards showing short programs. Children predict the output, swap their cards with a partner, and compare their explanations. Scratch investigation Use a simple program where one sprite changes a count. Ask children to explain what would happen if a certain block were removed. Reasoning prompt Use the question, “Which is correct and how do you know?”. Apply it to code, flow diagrams, or unplugged models. This keeps the emphasis on explanation rather than activity. Research insight CAS highlights the importance of conceptual understanding for later problem-solving. EEF guidance notes that structured talk and precise vocabulary strengthen reasoning across disciplines. Tasks that build explanation and prediction support both strands of research. ACT I V I T I ES FOR PRACT I CE 42 | www.teachwire.net