NEA: Scope, Analysis and Authenticity

Select a problem or investigation you understand or can research, with enough computational substance to demonstrate your skills. A simulation, data-processing tool or optimisation investigation can be suitable when its real requirements justify the techniques. A project title alone does not establish A-level demand.

Discuss suitability and centre requirements with the teacher early. Do not add unrelated features solely to collect technical labels. The important question is what the working solution needs and whether you can implement, explain and evaluate it independently within the available time.

Describe the problem clearly enough for a third party, identify intended users or recipients, and gather relevant evidence through dialogue or investigation. Model the data and constraints that later design depends on. Numbered objectives should be specific, appropriate and measurable.

Keep analysis focused on the actual project, not a generic essay about technology. If requirements change during prototyping, record the evidence and rationale. A real user’s difficulty or an investigation’s research question should connect to the behaviour you later build and test.

The specification allocates 75 marks: analysis 9, documented design 12, technical solution 42, testing 8 and evaluation 4. The technical solution is substantial, but the other sections provide evidence of what was intended and achieved. These allocations are not an automatic checklist of marks for including a feature.

The submission must reflect the student’s own work and thinking under current AQA, JCQ and centre rules. Acknowledge external sources, libraries and any permitted assistance as required, including relevant AI use. Acknowledgement does not transform someone else’s assessed work into independent achievement. These lessons teach preparation through generic examples, not a ready-made project to submit.

Attempt the task before opening its worked response. Record each change of state, explain the rule used, and check the result against the original requirements. Code examples labelled Python 3 use that language’s conventions; pseudocode states its own assumptions.