Concepts
This study delivers 1 primary concept and 1 secondary concept.
Primary concept: Algorithms (CO-KS12-C001)
Type: Knowledge | Teaching weight: 1/6An algorithm is a precise, unambiguous sequence of instructions for solving a problem or accomplishing a task. Algorithms are more general than programs: an algorithm describes what needs to be done, while a program is a specific implementation of an algorithm in a particular programming language. Algorithms must be correct (they produce the right output), precise (each step is unambiguous), and finite (they eventually reach a conclusion). At KS1 and KS2, pupils learn to write and recognise algorithms, understand their properties, and implement them as programs.
Teaching guidance: Begin with unplugged algorithm activities before moving to digital programming. Teach pupils to write step-by-step instructions for everyday tasks (making a sandwich, brushing teeth) to illustrate the precision required in algorithms. Use robot or turtle-following activities where pupils give instructions and observe the results of ambiguity or incorrect ordering. Discuss what happens when an algorithm has an error: the program does what we said, not what we meant. Introduce the idea of testing algorithms with different inputs to check they work in all cases. Key vocabulary: algorithm, instruction, sequence, step, precise, unambiguous, input, output, process, program, implement, order, correct, test, debug Common misconceptions: Pupils may think that an algorithm is the same as a program; clarifying that an algorithm is the idea or plan, while a program is the specific coded implementation, is important. Pupils may not appreciate that algorithms need to be unambiguous; activities where deliberately ambiguous instructions lead to unexpected results make this vivid. The idea that a computer does exactly what it is told, rather than what we intended, is a fundamental shift in thinking that needs explicit attention.Differentiation
| Level | What success looks like | Example task | Common errors |
| Entry | Following a set of step-by-step instructions (an algorithm) to complete a task, understanding that the order matters. | Follow these instructions to draw a house: 1. Draw a square. 2. Draw a triangle on top. 3. Draw a rectangle door. 4. Draw two square windows. Did the order matter? | Skipping steps or doing them out of order; Not understanding that algorithms must be followed precisely |
| Developing | Writing simple algorithms as a sequence of instructions for a familiar task, identifying when instructions are ambiguous or incomplete. | Write instructions for making a jam sandwich that a robot could follow exactly. Test your instructions with a partner. | Writing instructions that are too vague for a computer to follow precisely; Assuming the reader knows things that are not explicitly stated |
| Expected | Designing algorithms to solve problems, comparing different approaches and evaluating their efficiency. | Write two different algorithms for sorting five numbered cards into order. Which is more efficient? | Writing algorithms that only work for the specific example, not the general case; Not being able to trace through an algorithm step by step to check it works |
| Greater Depth | Analysing the efficiency of algorithms, predicting how they perform with larger inputs, and explaining the concepts of algorithm design to others. | If Algorithm 1 (checking pairs) takes 10 comparisons to sort 5 cards, roughly how many might it take for 10 cards? Why does it take longer? | Assuming the time doubles when the input doubles (it often grows faster); Not connecting algorithm efficiency to real-world computing problems |
Model response (Entry): I followed each step in order and drew the house. The order matters because I needed the square first to know where to put the triangle roof on top.
Model response (Developing): 1. Pick up the bread bag. 2. Take out two slices. 3. Put them on the plate. 4. Pick up the knife. 5. Open the jam jar. 6. Put the knife in the jam. 7. Spread jam on one slice. 8. Put the other slice on top. When my partner tested them, they asked 'which side up?' for step 3 — I needed to add 'flat side up'.
Model response (Expected): Algorithm 1 (Checking pairs): Compare each pair of cards from left to right. If they are in the wrong order, swap them. Repeat until no swaps are needed. Algorithm 2 (Finding smallest): Find the smallest card and put it first. Find the next smallest and put it second. Continue until all are sorted. Algorithm 2 requires fewer comparisons for this small set, making it more efficient. But Algorithm 1 is simpler to understand.
Model response (Greater Depth): For 10 cards, it could take many more comparisons — maybe around 45 or more — because each pass through the list compares 9 pairs, and you might need many passes. The number of comparisons grows much faster than the number of cards. This is why computer scientists care about efficiency — a slow algorithm that works fine for 5 items might be too slow for 1000 items.
Secondary concept: Debugging and Logical Reasoning (CO-KS12-C003)
Type: Skill | Teaching weight: 2/6Debugging is the process of finding and fixing errors in programs. It requires logical reasoning: the ability to read code, mentally execute it step by step, identify where the actual behaviour diverges from the expected behaviour, and determine what change will fix the error. Logical reasoning about programs is also required to predict what a program will do before running it. At KS1 and KS2, developing debugging skills and the habit of logical, systematic thinking about code is as important as learning to write new code.
Differentiation
| Level | What success looks like | Common errors |
| Entry | Identifying that a program is not working as expected and finding an obvious error by comparing the output with the intended result. | Rewriting the whole program instead of finding and fixing the specific error; Not being able to describe what the program should do versus what it actually does |
| Developing | Using logical reasoning to trace through a program step by step, predicting the output and identifying where it goes wrong. | Not updating the variable value between iterations; Tracing through only the first iteration and guessing the rest |
| Expected | Systematically debugging programs by testing, identifying errors, hypothesising causes, making changes and retesting. | Fixing one bug without retesting to check it doesn't cause another; Changing multiple things at once and not knowing which change fixed the problem |
| Greater Depth | Applying debugging strategies systematically, including using test data, print statements for tracing, and explaining why certain types of bugs are harder to find. | Only testing with one type of input data; Not testing edge cases (empty lists, duplicates, already-sorted data) |
Thinking lens: Cause and Effect (primary)
Key question: What caused this to happen, and how do we know? Why this lens fits: Debugging requires pupils to trace how each instruction in a program causes a specific change in output — identifying which instruction is the cause of the unexpected behaviour is the core cognitive act. Question stems for KS1:Session structure: Practical Application
Practical Application
A hands-on sequence where pupils apply knowledge and skills to solve a practical problem or create a functional outcome. Begins with a real-world context, builds skills through rehearsal, guides design or planning, supports making or problem-solving, and concludes with evaluation against success criteria.
context → skill_rehearsal → design → make_or_solve → evaluate
Assessment: Practical outcome (solution, product, program) evaluated against defined success criteria, with written or verbal explanation of the process and decisions made.
Computing focus
Programming paradigm: Unplugged Computational concepts: algorithm, sequence, debugging Abstraction level: Physical Themes: algorithms, computational thinkingWhy this study matters
Unplugged activities (no computers) are the most effective introduction to algorithms because they make the abstract concrete. Writing step-by-step instructions for everyday tasks (making a sandwich, brushing teeth, navigating a maze) reveals the need for precision and unambiguity. Pupils discover through classmate-following exercises that computers do exactly what you say, not what you mean.
Pitfalls to avoid
Computational thinking skills (KS1)
These disciplinary skills should be woven through teaching, not taught in isolation:
Vocabulary word mat
| Term | Meaning |
| actual |
| algorithm |
| bug |
| check |
| correct |
| debug |
| error |
| execute |
| expected |
| fix |
| implement |
| input |
| instruction |
| logic error |
| order |
| output |
| precise |
| predict |
| process |
| program |
| reasoning |
| sequence |
| step |
| syntax error |
| test |
| trace |
| unambiguous |
Scaffolding and inclusion (Y1)
| Guideline | Detail |
| Reading level | Pre-reader / Emergent |
| Text-to-speech | Required |
| Max sentence length | 8 words |
| Vocabulary | Concrete nouns and action verbs only. No abstract concepts without physical anchor. Examples: dog, apple, jump, big, one more. |
| Scaffolding level | Maximum |
| Hint tiers | 2 tiers |
| Session length | 5–12 minutes |
| Worked examples | Required — Animated, narrated walkthrough with no text. Character models the thinking aloud. |
| Feedback tone | Warm Nurturing |
| Normalize struggle | Yes |
| Example correct feedback | The frog jumped exactly four spaces — you counted perfectly! |
| Example error feedback | Oh, let us count again together! [animation demonstrates] |
Knowledge organiser
Key terms:Graph context
Node type:ComputingTopicSuggestion | Study ID: TS-CO-KS1-001
Concept IDs:
CO-KS12-C001: Algorithms (primary)CO-KS12-C003: Debugging and Logical Reasoning``cypher
MATCH (ts:ComputingTopicSuggestion {suggestion_id: 'TS-CO-KS1-001'})
-[:DELIVERS_VIA]->(c:Concept)
-[:HAS_DIFFICULTY_LEVEL]->(dl)
RETURN c.name, dl.label, dl.description
``
Generated from the UK Curriculum Knowledge Graph — zero LLM generation.