Computing KS2 Y5Y6 Convention

Micro:bit Physical Computing

6 lessons

Subject
Computing
Key Stage
KS2
Year group
Y5, Y6
Statutory reference
design, write and debug programs that accomplish specific goals, including controlling or simulating physical systems
Source document
Computing (KS1/KS2) - National Curriculum Programme of Study
Estimated duration
6 lessons
Status
Convention
Coverage: 7/11 expected capabilities surfaced
Curriculum anchorConcept modelDifferentiation dataThinking lensLesson structurePrior knowledge linksLearner scaffolding
Cross-curricular linksVocabulary definitionsSuccess criteriaAccess and inclusion

Concepts

This study delivers 1 primary concept and 1 secondary concept.

Primary concept: Programming: Sequence, Selection and Repetition (CO-KS12-C002)

Type: Skill | Teaching weight: 2/6

All programs are built from three fundamental control structures: sequence (instructions executed in order, one after another), selection (conditional branches where different instructions execute depending on a condition - if/then/else) and repetition (loops where instructions repeat a specified number of times or while a condition holds). These three structures are sufficient to express any computable algorithm, and mastery of them is the core of programming competence. At KS2, pupils learn to use all three structures in their programs, developing increasingly sophisticated and efficient code.

Teaching guidance: Introduce each control structure separately before combining them. Use visual block-based programming environments (Scratch, Blockly) initially to reduce syntax barriers. Progress to text-based languages at upper KS2 to develop more precise understanding of programming syntax. Always connect programming tasks to a genuine purpose: a game, an animation, a simulation. Teach debugging systematically: read the code line by line, trace the execution, identify where actual behaviour diverges from expected behaviour. Celebrate debugging success as much as successful first attempts. Key vocabulary: sequence, selection, repetition, loop, conditional, if, then, else, while, for, variable, input, output, debug, program, code, execute, trace Common misconceptions: Pupils often use loops incorrectly, either not using them when repetition is present (writing the same instruction multiple times) or using them in inappropriate contexts. Explicit comparison of repetitive code versus loop code makes the efficiency benefit clear. Selection (if/then/else) is conceptually more demanding; pupils may write conditions that cannot be true, or miss the else case. Tracing through conditional code step by step makes the logic visible.

Differentiation

LevelWhat success looks likeExample taskCommon errors

EntryCreating a simple program using sequence — a series of instructions executed in order — using a block-based programming environment.Program the sprite to walk forward 100 steps, say 'Hello!' and then turn around.Putting blocks in the wrong order so the sprite turns before walking; Not connecting blocks together so only the first one runs
DevelopingUsing selection (if/then) and repetition (loops) in programs to create more complex behaviour.Program a character that walks forward and turns when it reaches the edge of the screen. Use a loop and an if statement.Putting the if-statement outside the loop so it only checks once; Creating an infinite loop without any stopping condition
ExpectedCombining sequence, selection and repetition to create programs that solve problems or meet a design brief, using variables to store and change data.Create a quiz program that asks three questions, uses a variable to keep score, and gives a different message depending on the final score.Not initialising the variable at the start (score starts at a random value); Using the wrong comparison operator (= vs >) in the selection
Greater DepthDesigning modular programs using procedures or functions, explaining how abstraction makes programs easier to understand and maintain.Refactor your quiz program so each question is handled by a reusable procedure. Why is this better?Creating procedures that are too specific and not genuinely reusable; Not understanding how parameters pass information into procedures

Model response (Entry): I used three blocks: 'move 100 steps', 'say Hello! for 2 seconds', 'turn 180 degrees'. The sprite walked, spoke and turned around.
Model response (Developing): I used a 'forever' loop containing: 'move 10 steps', then 'if touching edge then turn 180 degrees'. The character bounces back and forth across the screen without stopping. The loop repeats the instructions and the if-statement checks for the edge each time.
Model response (Expected): I created a variable called 'score' set to 0. For each question, I used 'ask' and checked the answer with an if-statement. If correct, I increased score by 1. At the end, I used selection: if score = 3, say 'Perfect!'; if score >= 1, say 'Well done!'; else say 'Try again!'. The program uses sequence (question order), selection (checking answers) and repetition (I could put questions in a loop).
Model response (Greater Depth): I created a procedure called 'ask_question' that takes a question and correct answer as inputs. It asks the question, checks the answer, and updates the score. My main program just calls this procedure three times with different questions. This is better because if I want to change how questions work, I only change the procedure once instead of changing code in three places. It is also easier to add more questions.

Secondary concept: Decomposition and Computational Thinking (CO-KS12-C006)

Type: Skill | Teaching weight: 2/6

Computational thinking is a set of problem-solving approaches that involve breaking problems down (decomposition), identifying patterns (pattern recognition), focusing on the most relevant information (abstraction) and developing step-by-step solutions (algorithm design). Decomposition - breaking a complex problem into smaller, manageable sub-problems - is particularly important in programming, as it enables pupils to tackle problems that would otherwise be too large to address as a whole. At KS2, pupils apply decomposition to design programs and to plan complex digital projects.

Differentiation

LevelWhat success looks likeCommon errors

EntryBreaking a simple problem into smaller, more manageable parts (decomposition).Making the parts too big (still complex problems rather than simple tasks); Not being able to separate the problem into independent parts
DevelopingApplying decomposition, pattern recognition and abstraction to solve problems: identifying repeated patterns and focusing on the most important information.Grouping by superficial features (colour, size) rather than meaningful patterns; Not understanding what 'abstraction' means in computing — removing unnecessary detail
ExpectedApplying all aspects of computational thinking (decomposition, pattern recognition, abstraction, algorithm design) to solve a complex problem systematically.Jumping straight to the algorithm without decomposing and abstracting first; Not recognising that computational thinking is a general problem-solving approach, not just programming
Greater DepthEvaluating the effectiveness of computational thinking solutions, identifying limitations and suggesting improvements, and explaining how these approaches are used in real-world computing.Thinking the first algorithm is the final answer without considering limitations; Not connecting the abstract solution to real-world applications


Thinking lens: Cause and Effect (primary)

Key question: What caused this to happen, and how do we know? Why this lens fits: Writing and debugging programs with sequence, selection and repetition demands that pupils predict the effect of each control structure — tracing how changing a condition in a selection statement changes what the program does is a direct cause-and-effect analysis. Question stems for KS2:
  • What caused this to happen?
  • How could we check if that is the reason?
  • Is there more than one reason?
  • What would happen if we changed just one thing?
  • Secondary lens: Systems and System Models — Decomposition requires pupils to model a complex problem as a system of smaller interacting parts — understanding that the whole can be broken into components that each perform a defined function is a systems-thinking act.

    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.

    contextskill_rehearsaldesignmake_or_solveevaluate Assessment: Practical outcome (solution, product, program) evaluated against defined success criteria, with written or verbal explanation of the process and decisions made. Teacher note: Use the PRACTICAL APPLICATION template: set a real-world context or problem that requires pupils to apply knowledge and skills. Rehearse the key skills needed through guided practice. Support pupils in designing their approach, carrying out the practical task, and evaluating their outcome. Encourage them to explain what worked well and what they would improve. KS2 question stems:
  • What skills will you need to solve this problem?
  • What is your plan, and why did you choose this approach?
  • How well did your solution work?
  • What would you change if you did it again?

  • Computing focus

    Programming paradigm: Block Based Software/tool: Micro:bit Computational concepts: sequence, selection, input output Abstraction level: Visual Themes: physical computing, sensors, programming

    Why this study matters

    The micro:bit bridges digital programming and the physical world. Pupils program the micro:bit to respond to sensor inputs (button press, tilt, light level, temperature) and produce outputs (LED display, sound). This physical computing connects to DT (control in products) and Science (sensors measuring the environment). The block-based editor makes it accessible while the physical output makes it tangible.


    Pitfalls to avoid

  • Too many features at once -- start with one input and one output
  • Not downloading the program to the micro:bit -- test on the simulator first, then download
  • USB connection issues -- teach the download-and-transfer process explicitly

  • Computational thinking skills (KS2)

    These disciplinary skills should be woven through teaching, not taught in isolation:

  • Algorithm design (KS3) — Design, implement and analyse algorithms for non-trivial computational problems including sorting and searching; understand that multiple algorithms can solve the same problem with different efficiency characteristics; use logical reasoning and formal comparison techniques to assess the relative utility of alternative algorithms; implement algorithms in at least two programming languages, at least one text-based.
  • Pattern recognition (KS2) — Identify patterns and regularities in data sets and program behaviours; use pattern recognition to select appropriate control structures (repetition for repeated actions, selection for conditional branching); generalise from specific examples to produce reusable solutions; recognise when an existing algorithm or program component can be reused to solve a new problem.
  • Abstraction (KS1) — Focus on the most important features of a problem or task while ignoring unnecessary detail; represent real-world actions as simple step-by-step instructions that capture the essential logic without irrelevant specifics.
  • Decomposition (KS2) — Decompose a complex programming problem or digital project into distinct, manageable sub-problems that can be developed and tested independently; plan program structure using top-down design before coding; use procedures and functions as the coded expression of decomposed sub-problems.
  • Decomposition (KS1) — Break a familiar task or problem into a sequence of smaller, ordered steps; understand that a complex instruction can be split into simpler sub-instructions that together achieve the same goal; apply this thinking when giving instructions to a programmable toy or creating a simple program.
  • Abstraction (KS3) — Design and evaluate computational abstractions that model the state and behaviour of real-world problems and physical systems; select appropriate levels of abstraction for a given problem context; use abstract data types, classes and interfaces to hide implementation detail; understand the layered abstractions present in computing systems from hardware to application.

  • Vocabulary word mat

    TermMeaning

    abstraction
    algorithm
    code
    computational thinking
    conditional
    debug
    decomposition
    design
    else
    execute
    flowchart
    for
    function
    if
    input
    loop
    modular
    output
    pattern recognition
    plan
    problem-solving
    procedure
    program
    pseudocode
    repetition
    selection
    sequence
    sub-problem
    then
    trace
    variable
    while
    microcontroller
    sensor
    LED
    button
    accelerometer
    download

    Prior knowledge (retrieval plan)

    Pupils should already know the following from earlier units:

    Prior knowledge neededFor conceptDescription

    AlgorithmsProgramming: Sequence, Selection and RepetitionAn algorithm is a precise, unambiguous sequence of instructions for solving a problem or accompli...


    Scaffolding and inclusion (Y5)

    GuidelineDetail

    Reading levelFluent Reader (Lexile 450–650)
    Text-to-speechAvailable
    Max sentence length22 words
    VocabularyAcademic vocabulary expected. Technical domain vocabulary accessible with in-context clues. Figurative language (metaphor, personification) appropriate.
    Scaffolding levelLight To Moderate
    Hint tiers4 tiers
    Session length20–30 minutes
    Worked examplesRequired — Text-based. Child completes partial worked examples (fading). Not fully narrated.
    Feedback tonePeer Like Respectful
    Normalize struggleYes
    Example correct feedbackYou recognised that 1/2 is larger than 2/5, and used the common denominator method correctly. The visualiser confirms it — the bar for 1/2 is noticeably longer.
    Example error feedbackThe reasoning does not quite hold: you said both fractions are the same because the numerator in 2/5 is double the numerator in 1/2. But the denominator changed too — the pieces got smaller. Converting to tenths: 1/2 = 5/10 and 2/5 = 4/10. Which is larger now?


    Knowledge organiser

    Key terms:
  • microcontroller
  • sensor
  • input
  • output
  • LED
  • button
  • accelerometer
  • program
  • download
  • Core facts (expected standard):
  • Programming: Sequence, Selection and Repetition: Combining sequence, selection and repetition to create programs that solve problems or meet a design brief, using variables to store and change data.

  • Graph context

    Node type: ComputingTopicSuggestion | Study ID: TS-CO-KS2-008 Concept IDs:
  • CO-KS12-C002: Programming: Sequence, Selection and Repetition (primary)
  • CO-KS12-C006: Decomposition and Computational Thinking
  • Cypher query:

    ``cypher

    MATCH (ts:ComputingTopicSuggestion {suggestion_id: 'TS-CO-KS2-008'})

    -[: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.