Use Local Exam Results Data to Plan More Responsive GCSE and A-Level Support

For exam-prep teachers, national headlines can be useful context, but they rarely answer a practical planning question: what should this next GCSE or A-level group need from me? Ofqual’s local authority results data offers a more local view of qualification outcomes and subject uptake across England. Used carefully, it can help tutors, teachers and course creators choose where to investigate, which diagnostic questions to ask, and how to balance foundations, exam practice and feedback.

The important word is investigate. Area-level results are not a verdict on a school, a class or a learner. They cannot predict an individual’s grade, explain why a pattern exists, or replace direct evidence from learners’ work. The most responsible use of the data is as a starting point for course design: a way to form hypotheses that are then tested through enrolment information, baseline tasks, conversations and ongoing assessment.

What Ofqual’s local authority exam results data is

Ofqual has added local authority district, administrative county or unitary authority, and regional views to its interactive results maps. For GCSEs and A levels, users can explore grade outcomes and subject uptake by geography and subject. The maps cover data from 2019 to 2025, and the geography is based on the postcodes recorded for exam centres in Ofqual’s National Centre Number register. Ofqual’s announcement explains that the update is intended to provide a more detailed local and regional picture of qualification outcomes; the GCSE map and A-level map provide the interactive views.

For an exam-prep provider, this creates two useful planning lenses:

• Grade outcomes: the proportion of results at selected grades or grade thresholds in a subject and area.
• Subject uptake: the number of students taking a subject in an area.

These lenses are valuable because they are different. A subject may have substantial local uptake, suggesting a larger potential audience for support, without the data telling you what individual students find difficult. Likewise, an area-level grade pattern may prompt a question about whether learners would value earlier foundations work, but it does not establish that a particular school teaches poorly or that a new learner is behind.

What local results data can—and cannot—tell an exam-prep teacher

There is another technical caution. The map assigns results to areas using exam-centre postcodes, not students’ home addresses. A learner may travel to a school or college outside their local authority, and providers should avoid describing the figures as results for all residents of an area. Ofqual also notes that the map depends on the accuracy of centre-postcode records and that a small number of centres were excluded because their postcodes were not valid.

A five-step workflow for reviewing local trends before course planning

1. Define the planning decision first. Write one decision you need to make, such as: “Which subjects should feature in our October half-term clinics?” or “Do we need separate A-level maths foundations and stretch groups?” A clear decision stops browsing from becoming a search for dramatic-looking figures.
2. Check the source, year, qualification and geography. Record the dashboard URL, date accessed, exam series, subject, selected grade measure and area level. Keep GCSE and A-level findings separate. Check whether you are viewing a district, county, unitary authority, region or England total before comparing anything.
3. Compare, then describe rather than explain. Look at the selected local area alongside a broader geography where useful. Note only what the data visibly shows: for example, “subject uptake was higher in Area A than Area B in the selected year.” Do not leap from an outcome difference to an explanation about teaching quality, motivation or socioeconomic circumstances.
4. Turn patterns into learner-facing diagnostic questions. Convert each observation into a question that can be answered by a new learner, parent, school contact or short baseline task. This is the step that turns public data into responsible teaching evidence.
5. Plan a short cycle and review it. Build an initial module sequence, collect low-stakes evidence, and set a review date. If the diagnostic evidence disagrees with the local-data hypothesis, revise the course. Your teaching evidence should carry more weight than a broad area pattern.

From area patterns to better diagnostic questions

Suppose a tutor sees substantial local uptake for GCSE maths. That is a demand signal, not a topic diagnosis. A useful next move is to ask prospective learners questions that distinguish between confidence, knowledge and exam execution:

• Which tier and exam board are you taking, if known?
• Which recent assessment or mock paper have you completed, and what feedback did you receive?
• Which question types take you longest: multi-step problems, algebraic manipulation, ratio, geometry, statistics or interpretation?
• When you lose marks, is it more often because of a method gap, misreading, incomplete working, timing or checking?
• What grade are you currently working at according to your teacher or recent assessed work?
• What outcome are you aiming for, and what support or access arrangements should the course take into account?

For A-level subjects, add questions about prior study, confidence with prerequisite knowledge, independent practice habits and the balance between content recall, extended responses and timed papers. The goal is not to sort learners into fixed labels. It is to identify the next teachable step and choose an appropriate starting point.

Use local results data to form a question. Use learner evidence to decide what to teach.

Plan modules around foundations, practice and feedback

A data-informed course does not need to become a data-heavy course. Once you have gathered baseline evidence, a simple three-part module structure keeps the focus on teaching.

1. Foundations: secure the knowledge that later work depends on

Start with prerequisite concepts, vocabulary, methods and representations. For a mixed-attainment group, provide a short entry check and optional recap resources rather than assuming all learners need a full reteach. Make the success criteria visible: learners should know what accurate, independent performance looks like before they attempt harder questions.

2. Deliberate exam practice: practise the task, not only the topic

Use questions that resemble the decisions learners will need to make under assessment conditions: selecting a method, interpreting command words, structuring an explanation, showing working or checking a conclusion. Mix guided examples with independent attempts. Keep practice purposeful by linking each activity to a specific misconception or exam behaviour identified in diagnostics.

3. Feedback and retrieval: make adaptation routine

End each lesson or module with a brief evidence point: an exit question, one exam-style item, a self-explanation or an annotated correction. Review errors at the next session and revisit essential material after a delay. This gives the teacher evidence for adjusting pacing and grouping without relying on broad local data to make individual decisions.

When course administration grows, SubSchool can help automate repetitive teaching work while you retain authorship and the final educational decision. For example, use your worksheet, diagnostic prompts and review points to structure a course, then keep teacher judgement at the centre of grouping, feedback and lesson changes. Create your course plan in SubSchool.

Downloadable local exam-results course-planning worksheet

Use the worksheet below as a copy-ready planning sheet. Paste it into your preferred document tool, add your course details, and save or export it as a downloadable PDF for your teaching team.

Communicate data-informed decisions responsibly

Parents and learners may reasonably ask why a course includes certain topics or why groups are organised in a particular way. Keep the explanation accurate and reassuring: “We reviewed publicly available area-level outcomes alongside learner diagnostics. The course begins with core skills and adapts using participants’ own work.” This is clearer and safer than claiming that an area “struggles” with a subject or that students from a named school are likely to receive particular grades.

Be especially careful in marketing. Do not use local results data to rank schools, imply inside knowledge about a school, promise grade improvement, or target learners with deficit-based messages. Public outcome data should support informed course design, not stigma or overconfident predictions.

Common mistakes to avoid

• Treating a local authority average as an individual profile. Start with a baseline task instead.
• Ignoring subject uptake. Percentages can look striking when the number of entries is small; inspect uptake before drawing planning conclusions.
• Comparing unlike measures. Match qualification type, subject, year, grade threshold and geographic level before comparing.
• Explaining a pattern without evidence. Record observations separately from possible explanations.
• Building a fixed course from one data view. Set review points and adapt from learners’ assessed work.
• Forgetting the geography rule. The maps use exam-centre postcodes, so do not present them as a map of where all students live.

Local exam results data is most useful when it makes course planning more curious, not more certain. Use it to choose where to look, then let learner diagnostics, classroom evidence and professional judgement determine what happens next.