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OCR H446 2.2.2 Computational solvability and problem recognition

Part 1 of 14 · H446 2.2.2 · Computational methods

OCR H446 2.2.2 begins with a question students often skip: can this problem be solved computationally at all? Working from a rehearsal-room allocation request, the worksheet teaches them to turn a vague human aim into precise inputs, rules, stored state and testable outputs before any algorithm is chosen.

Students will:

  • identify the inputs, rules, stored state and outputs hidden inside a described need
  • rewrite an ambiguous requirement so that a program could execute and test it
  • explain why naming sequence, selection and iteration does not answer a question about computational methods
  • judge whether a loosely worded request is solvable as stated, and say what information would make part of it computable
  • recall the central distinctions from memory in a closed-book check

Inside: 7 explanation cells, 1 multiple-choice question, 2 fill-in-the-blanks cells and 2 written answers. 20 marks, about 20 to 30 minutes.

Series: H446 2.2.2 · Computational methods, part 1 of 14.

Shared by Coding PathwayVerified teacher

  • 12 cells
  • About 30 minutes
  • CC BY-SA 4.0
  • Shared 31 Aug 2026
  • Updated 3 Sept 2026

Preview

The whole resource, exactly as a class sees it. Answers and marking are held back.

Computational solvability and problem recognition

A community venue wants software to allocate rehearsal rooms. Before choosing an algorithm, a developer must decide whether the need has been described precisely enough for a computer to solve.

By the end, you will be able to

  • identify the inputs, rules, stored state and outputs of a problem;
  • judge whether a problem is computationally solvable as stated;
  • distinguish an ambiguous human aim from a computable specification;
  • explain how recognition shapes the method chosen.

Reactivate: an algorithm is a finite sequence of unambiguous steps.

From a need to a computable problem

From a real problem to a computationally solvable specificationScenarioreal need and limitsComputational description• representable inputs• unambiguous rules/calculations• data and state that can be stored• testable outputs and successfeasible?within resourcesA computer needs a precise, finite representation and a method it can carry out.

A computational problem needs data that can be represented, rules or calculations that can be stated without guesswork, any changing state that must be stored, and an output whose success can be checked. A proposed method must also finish using feasible time and storage.

A computer may support a human decision without replacing it. For example, it can rank rooms using capacity and access requirements, while a coordinator resolves a sensitive welfare judgement that has no agreed numerical rule.

Worked recognition: rehearsal-room allocation

The phrase give every group the best room is not yet precise. Refine it:

  • inputs: group size, required equipment, access need and requested time;
  • stored state: room capacity, equipment, availability and existing allocations;
  • rules: a room must be free, large enough and meet every required feature;
  • output: a room identifier or a clear no-room result;
  • success: every allocation satisfies the constraints and no room is double-booked.

The word best has been replaced by testable constraints. That change makes a computational solution possible.

Multiple choice1 mark

Which change most directly makes ‘choose the nicest available room’ computationally solvable?

  • AReplace ‘nicest’ with agreed, measurable ranking criteria
  • BStore a photograph of every room
  • CUse a faster processor
  • DAsk the computer to make a human judgement
Fill in the blanks3 marks
A computable specification identifies representable gap 1, unambiguous gap 2, any stored gap 3, and testable outputs.
  • inputs
  • rules
  • state
  • devices

Guided checkpoint: repair the statement

Draft statement: Automatically give students a fair amount of support.

Use this sequence: identify one ambiguity → propose measurable input data → state a rule the program can execute → name a testable output. Keep the human aim, but translate the part delegated to software into precise terms.

Written answer5 marks

Rewrite the draft support statement as a computationally solvable problem.

Include at least two inputs, one unambiguous rule and one measurable output.

Students type their answer here.

Common examination trap

Sequence, selection and iteration are programming constructs, not answers to ‘identify a computational method’. First recognise the character of the problem: does it involve exploring choices, extracting patterns, estimating a good next move, modelling load, overlapping stages, or making structure visible? The recognised features point towards a method.

Written answer7 marks

A festival organiser says: ‘Use a computer to create the perfect running order.’ Explain whether this problem is computationally solvable as stated, then describe the information needed to make a useful part of it computable.

Develop a judgement, not just a list. Consider ambiguity, inputs, constraints, state and success criteria.

Students type their answer here.

Closed-book checkpoint

Complete each sentence from memory. There is no answer bank and correctness is held for teacher review.

Fill in the blanks4 marks
A vague preference becomes computable when it is replaced by measurable checkpoint gap 1. Rules that every valid result must obey are checkpoint gap 2. The output can be checked against a checkpoint gap 3. A precise method that needs unreasonable time or storage may still be checkpoint gap 4.

Review your understanding

Before submitting, check that you can explain the central distinction in your own words, expose the intermediate state that supports your answer and apply the method in an unfamiliar context.