Problem identification — OCR A-Level Computer Science
Problem identification explained
Problem identification covers 2 specification points, including (a) Describe and justify the features that… and (b) Explain why the problem is amenable to a….
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Open a point below for its explanation and revision guidance.
(a) Describe and justify the features that make the problem solvable by computational methods.
Describe means giving an accurate account of the features. Justify means explaining why each feature makes a computational solution possible, using evidence from your chosen problem. Useful features include clear inputs and outputs, decomposition into smaller parts and repeatable steps. Timetabling school lessons, for example, has defined constraints and checkable outcomes, so a computer can search for a valid timetable. Judging whether a painting is beautiful lacks an agreed success measure, so no algorithm can reliably deliver a definitive answer. Your answer should draw on your own identified problem rather than generic claims.
(b) Explain why the problem is amenable to a computational approach.
This criterion asks you to justify why a problem can be tackled with a computer, not merely to describe it. Show that the problem can be broken into clearly defined steps, which is the basis of an algorithm, and that its inputs, processes and outputs can be identified. Check that the data can be represented digitally and that the task involves repetition, large volumes or consistently applied rules, features that suit computers. Support each reason with a concrete example, such as sorting customer orders by date. Finally, acknowledge any limits, such as tasks needing human judgement, so the justification is balanced.
Your focus
- Describe features of a chosen problem that make it suitable for computational solution.
- Justify why each feature supports a computational solution using evidence from the chosen problem.
- Distinguish problems with defined inputs, steps and success criteria from problems that lack them.
Show all 6 objectives
- Explain why a given problem can be expressed as an algorithm.
- Identify the inputs, processes and outputs of a problem.
- Justify the choice of a computational approach using a specific example.
Problem identification exam tips
Marking Points
- Describes clear inputs, outputs and processing steps that the chosen problem requires.
- Identifies decomposition, showing how the problem divides into smaller sub-problems that can be solved separately.
- Justifies each named feature by linking it to specific details of the chosen problem.
- Explains repeatable or automatable steps, showing why a computer can carry them out consistently.
- Recognises that a measurable success criterion makes the outcome checkable by an algorithm.
- Explains that the problem can be decomposed into a sequence of precise, ordered steps that a computer can follow.
- Identifies the inputs, processes and outputs of the problem and shows how each is defined.
- Justifies the computational approach with a specific feature such as repetition, large data volumes or rule-based decisions.
- Shows that the data involved can be represented in digital form and stored or processed by a computer.
- Supports each reason with a concrete example drawn from the chosen problem.
- Acknowledges a limitation, such as tasks requiring human judgement, and explains why the approach still applies.
Examiner Tips
- 💡Write one feature per paragraph, followed by a justification that cites specific details of your problem.
- 💡Check the command words: describe means give an accurate account, and justify means give reasons supported by evidence.
- 💡Before answering, confirm your problem has clear inputs, outputs and a way to judge whether a solution is correct.
- 💡Write one paragraph per reason, starting with a feature of the problem and then explaining why a computer suits it.
- 💡Use the terms algorithm, decomposition, input, process and output precisely, as they show computational understanding.
- 💡Check that each claim is tied to the problem in your scenario rather than to computing in general.
- 💡Finish with a brief limitation, then check whether it weakens your justification and, if so, explain why it does not.
Common Mistakes
- Lists features without explaining them; correct this by adding a justification that links each feature to the problem.
- Gives generic features that could apply to any problem; correct this by referring to details from the learner’s chosen problem.
- Claims a problem is computable because it is large or interesting; correct this by explaining its defined inputs, steps and success test.
- Describes the problem's background without stating why a computer can solve it; state the reasoning linked to computational features.
- Gives a generic reason, such as computers being fast, without linking it to the problem; name the specific feature and explain its effect on the problem.
- Treats a problem as computable because it is important or large; show the steps, inputs and outputs that make it computable.
- Lists features of computing without an example; add a concrete example from the chosen problem to each reason.