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How to analyse SEND equality without reducing pupils to labels

Analyse SEND equality data across attendance, behaviour and attainment while keeping denominators, missingness, context, privacy and human review visible.

Founder, Student Radar

Sources last checked .

  • SEND equality
  • Public Sector Equality Duty
  • Connected pupil data
  • Data interpretation

Analyse SEND equality by starting with a school decision, then testing whether a group difference survives seven checks: population, characteristic, measure, denominator, source coverage, connected evidence and an owned response. Keep SEND and Pupil Premium as analytical lenses, not explanations. Keep disability separate from SEN status. Stop or restrict the view when a small group could identify children or the evidence cannot support the comparison.

This focused guide is for SENCos, school leaders and data leads in England. It is accurate on 14 August 2026, supports professional review and is not legal advice.

Start with the decision, not the label

For state schools, the Public Sector Equality Duty requires decision-makers to have due regard to eliminating unlawful discrimination, advancing equality of opportunity and fostering good relations. Government guidance says equality evidence should be considered before and while a decision is made, recorded proportionately and reviewed against actual outcomes.

That does not mean feeding every available characteristic into one chart. The same guidance warns against indiscriminate data collection. It asks decision-makers to identify relevant gaps, use proportionate evidence and keep the decision under review.

Name the distinction you are making. Disability, race and sex are protected characteristics under the Equality Act 2010. SEN status and Pupil Premium eligibility are not protected characteristics, although they may reveal disadvantage and may overlap with protected groups. A pupil can have SEN without meeting the Act's disability definition, and a disabled pupil may not have identified SEN.

The question is therefore not “What are SEND pupils like?” It is “Does this school decision, practice or pattern appear to affect pupils differently, what evidence could explain the difference, and what is within the school's control?” Labels sort records. They have yet to acquire the power of biography.

Write one equality finding card

Keep the analysis to one decision and seven visible lines. If a line is missing, the gap is part of the finding.

  1. Decision: state the policy, provision, routine or resource decision that the evidence may change.
  2. Population: define the school, phase, year group, period, joiners, leavers and any lawful exclusions from the analysis.
  3. Characteristic or lens: preserve the recorded field, extraction date, unknowns and changes over time. Do not substitute SEN status for disability.
  4. Measure: name what is counted. Attendance sessions, behaviour incidents, praise, removals, assessment records and provision delivery answer different questions.
  5. Denominator and coverage: show pupil counts, exposure or opportunities, missing records and source failures beside percentages or rates.
  6. Evidence trail: connect only the records needed to test access, delivery and interpretation, then hear pupil and family views through an accessible route.
  7. Response and review: record the decision-maker, action, date, intended evidence and what would cause the decision to change.
Paper cohort tokens pass through separate blank evidence layers before a human review marker
Editorial illustration: separate the group signal into its population, measure, missingness and evidence layers before it reaches a decision.

Let the finding change as evidence arrives

These invented details are combined solely to demonstrate the analysis. They are not a school result, pupil story or customer case.

A secondary school review finds an apparent behaviour difference for pupils recorded as receiving SEN Support. The first version counts incidents per pupil. It does not show lesson exposure, duplicate imports, positive recognition, current provision or missing attainment records, so the team records a signal and makes no conclusion.

Adding attendance shows that some pupils had fewer classroom sessions in the period. A source check finds duplicated behaviour rows after an import. Positive recognition is recorded less consistently in one department. Attainment coverage is incomplete for recent joiners, so that comparison is withheld. Provision records show that an agreed transition step was unavailable in several lessons.

The team then checks intersections with Pupil Premium, ethnicity and sex. Some groups are too small to report safely, and several ethnicity fields are unknown. Those cells are suppressed; the missingness is carried into the decision record. The school does not turn a fragile slice into a confident percentage merely because the meeting agenda has reached item six.

Authorised pupil-level review reveals different circumstances. Staff hear pupils through appropriate communication routes, correct the duplicate data, restore the transition support, review how praise is recorded and set a dated department-level review. The equality finding changes practice without assigning a common motive or cause to the pupils.

An aggregate paper pattern separates into individual blank evidence paths leading to a human review table and review loop
Editorial illustration: return an aggregate pattern to separate evidence, accessible voice, accountable action and later human review.

Decide whether the finding survives challenge

Ask whether the pattern persists after source correction, comparable denominators and safe group rules. Ask what school process could create or reduce it. Record plausible alternative explanations, disagreement and the evidence still missing.

A group difference cannot prove discrimination, disability, unmet need, staff intent, parenting, future risk or the effect of provision. It cannot diagnose a pupil or select a sanction, referral, statutory outcome or support plan. It can justify a closer, proportionate review and a school-controlled action.

Privacy is part of the method. Ethnicity and information revealing health are special category data. The ICO says processing needs a lawful basis, an additional condition where special category data is involved, data minimisation and appropriate safeguards. A small intersection may still identify a child when staff can combine it with local knowledge. Restrict access, agree suppression and sharing rules with the data lead or DPO, and do not call data anonymous while the school can reconnect it to pupils.

National data provides context, not a target for an individual child. The Department for Education's 2026 SEN release keeps provision, ethnicity, free school meal eligibility, sex, year group and primary need available as distinct dimensions. A school analysis should show the same discipline while using local definitions and source dates.

Where Student Radar fits

Student Radar's available Heatmapincludes demographic lenses and a route back to authorised pupil context. The current app's Cohort Summary brings year-group attendance, SEND and inclusion coverage into one view. Available Behaviour Analytics includes hotspot and equity views, while Assessment Reports can add attainment and progress gaps with small-group caveats where the Assess package is in use.

These views can help staff connect a signal to its source records. They do not establish causation, determine compliance, diagnose need or make the decision. Source validation, access control and professional judgement remain with the school.

For the population and missingness method, use the attendance cohort guide. For the wider evidence boundary, read what connected pupil data means in practice. To review this workflow with your school's authorised data, request a SEND-focused walkthrough.

Sources and further reading

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