Student Radar
All articles
Attendance articlesAttendance analysis

How to report attendance cohort and disadvantage gaps without exposing pupils

Use a six-line attendance reporting card with clear denominators, FSM and pupil-premium distinctions, privacy rules and human review.

Founder, Student Radar

Sources last checked .

  • School attendance cohort analysis
  • Attendance data
  • Attendance support
  • Cohort review

Report an attendance cohort or disadvantage gap with a defined population, comparable possible sessions and visible unknowns. Before sharing it, check whether the audience could identify a pupil from the group or other information they hold. Suppress or aggregate the result where needed, and give the finding an owner and a review question.

A cohort can reveal where to look. It cannot explain why a pupil is absent, diagnose a need, establish cause or harm, assign blame, predict future absence or trigger automatic support, referral, sanction, penalty notice or a legal route.

This guide is for attendance leaders, school leaders, pastoral teams, DSLs, family-support staff, data leads and SENCos in England. It is current to 2 October 2026.

Start with one question the school can act on

The July 2026 edition of the Department for Education's statutory attendance guidance asks schools to analyse weekly patterns at pupil, cohort and year-group level, then use deeper half-termly, termly and full-year review.

The question should name a period, population and possible school response. “Which enrolled Year 9 pupils show a recurring afternoon pattern that needs a conversation about access?” is usable. “Why is Year 9 attendance poor?” asks the chart to write a biography.

Decide who owns the analysis and when it will be reviewed. Agree who can see pupil-level detail. A colourful dashboard without ownership is still an unattended spreadsheet, only with better lighting.

A six-line reporting card to complete before sharing

  1. Question and population. Define enrolled pupils, leavers, compulsory-school-age scope, admission dates and any planned exclusions from possible attendance sessions.
  2. Reporting window and measure. Use comparable dates and state whether the view shows attendance, absence, unauthorised absence, persistent absence or another measure.
  3. Denominator and coverage. Show cohort count, possible sessions, missing marks, unknown characteristics, late feeds and changes to pupil status.
  4. Characteristic and unknowns. Define the source and whether it reflects current status or status in the reporting period. Free school meals (FSM) status and pupil-premium entitlement are different fields. The DfE daily attendance collection includes FSM but does not collect pupil-level pupil-premium entitlement. Do not relabel an FSM comparison as a pupil-premium gap. Keep unknown status visible.
  5. Safe presentation and access. Record suppression or aggregation and who may see the result or open pupil-level evidence. The DfE similar-schools report suppresses comparisons for groups below six pupils. Six is not a universal school reporting threshold. Agree a context-specific safe reporting rule with the data lead or DPO, considering singling out, linkability and information the audience already knows.
  6. Owner, enquiry and review. Open authorised underlying sessions and relevant context, hear pupil and family views, then record an action, owner and review date. A group pattern prompts human enquiry only.

Keep that sequence on the analysis card. It makes the denominator and the human follow-up part of the result, instead of notes added after a meeting has already adopted the headline.

Paper pupil tokens move through a cohort board and privacy screen into a simplified group report
Editorial illustration: a privacy screen separates the detailed cohort from the shared group report.

Freeze the denominator before comparing groups

Write the inclusion rule beside the result. The DfE Monitor your school attendance tool can include leavers and pupils outside compulsory school age until filters are applied. Entry-year comparisons can also lack data from a previous school.

Its filters use the most recent pupil characteristics from the MIS. A pupil who received SEN support last year but does not now will be grouped by current status. That is a valid view for some questions and a misleading one for others.

Compare like with like: the same dates, possible-session rules, pupil scope and measure. The DfE notes that school reports, daily-data tools and published statistics may differ because their coverage, timing and calculations differ.

Keep rapid, revisable daily MIS figures separate from accredited census-based statistics. Pupil absence in schools in England: autumn term 2025/26, published on 6 August 2026, is accredited official statistics based on school census data. Label that coverage period explicitly. It cannot stand in for this week's school figures.

Layer characteristics slowly and keep missingness visible

The statutory guidance says schools choose relevant cohorts from their context. It names groups such as year, SEND, free school meals, young carers and pupils with a social worker. This is a prompt for proportionate analysis, not a request to combine every field.

Begin with one lens. If the pattern persists, test a second characteristic because it could change the operational question. Stop when the group becomes too small, unstable or identifiable, or when missing fields make the comparison unreliable.

Counts matter beside percentages. So do unknowns. Record pupils excluded by the period, missing sessions, late joiners, leavers and characteristics that are unavailable or current only. A blank cell is evidence about the analysis, even when it is not evidence about a child.

Removing names does not ensure anonymisation. Detailed cohort views remain personal data when staff can identify pupils directly or by combining fields. Another table or an earlier report may reveal a suppressed value, so check the whole release. Restrict access and involve the DPO when the purpose, audience or sharing changes.

Walk a made-up cohort back to the children

This composite combines invented circumstances to explain the reporting decision. It is not a school result, customer story or claim about any real pupil.

An attendance lead prepares an autumn-to-date FSM comparison for governors. Two unknown FSM records and a late admission need checking. A proposed year-group and SEND intersection would make a small group recognisable to people who know the school, so the shared report uses a broader aggregate. Authorised staff inspect the individual records separately.

The lead checks possible sessions and finds that the selected period includes late joiners. Current-status filtering also hides changes in SEN support. Some assessment records are incomplete, so no attainment comparison is made for those pupils.

Authorised pupil-level review shows different stories. One pupil missed teaching during a phased return. Another had approved off-site education. A third describes a difficult transition after lunch, while provision records show that agreed support was not consistently available.

The cohort finding therefore becomes several human questions. Staff check coding and access, hear each pupil and family, review adjustments or support, and use the DSL route immediately if separate safeguarding evidence creates an urgent concern.

The aggregate did not prove a common cause. It helped the team find where a careful review was needed and prevented one group label from becoming a substitute for individual context.

A broad reporting group connects to separate private evidence cards and a human review conversation
Editorial illustration: the aggregate pattern leads back to separate evidence, pupil and family voice, correction and a reviewable human action.

Turn the finding into a review question

End the analysis with one sentence: “We will check whether the identified in-school barrier is present, whether agreed support is accessible, and what pupils and families say; the attendance lead will review this on the agreed date.”

Name what would change the decision. Corrected codes, fuller source coverage, pupil or family evidence, delivered adjustments, curriculum access, health advice or a different time pattern may all alter the interpretation.

Review all absence bands, not only pupils who have crossed a persistent or severe absence threshold. The DfE absence-bandings guide also directs leaders to consider underlying reasons and then inspect individual pupil data.

What the cohort view cannot prove

A group difference cannot prove motive, parenting, illness, unmet SEND, exploitation, safeguarding harm or the effect of school provision. Correlation across attendance, behaviour and attainment cannot establish which factor caused another.

A threshold does not decide support or enforcement. Statutory guidance places monitoring, listening, understanding and support before formal or legal routes, with decisions based on the individual circumstances and local procedures.

Urgent safeguarding concerns still go to the DSL and established local or emergency route. Decisions follow the full evidence and established local or emergency procedures.

Where Student Radar fits

Student Radar's available Attendance Analytics can review headline, period, class, session and cohort patterns. The available Heatmap can help authorised staff move from a group signal to the pupil context behind it.

Schools still validate source fields and apply their reporting and access rules. Do not assume a dashboard automatically suppresses every small cohort. Where permission-controlled full attendance exports are enabled, Student Radar requires permission and records the export for audit before generating it. Authorised staff still decide suppression and sharing under the school's rules.

Student Radar does not diagnose a barrier, predict future absence, guarantee an outcome or choose a referral, sanction, penalty notice or legal route. The source MIS remains the attendance record, and professional review remains with the school.

Take the card into the next reporting meeting

  1. Write one attendance question and the school response it could inform.
  2. Record the population, period, measure and possible-session rule.
  3. Choose one characteristic lens and list the missing fields beside it.
  4. Set a minimum safe group rule with the data lead or DPO.
  5. Name who may open pupil-level evidence and who will hear pupil or family views.
  6. Give the finding an owner, review date and a question that can be revised.

For the wider evidence route, read what connected pupil data means in practice. For register accuracy, use the pre-term attendance-code check.

To review how this workflow could work with your authorised school data, request an attendance-focused walkthrough.

Sources and further reading