The achievement rate is lower than the college expected
This has been flagged because it is worth checking. It may be entirely correct. Investigate before assuming anything is wrong.
In plain English
The published or modelled achievement rate is lower than the college's own view of how well learners did. The difference is usually in the data rather than in the teaching.
Why it matters
Published achievement rates drive accountability conversations, inspection and, in some provision, intervention thresholds. A rate depressed by data problems misrepresents the college and is extremely difficult to correct after the year closes.
Funding
Indirect. Achievement and retention feed some funding calculations, and sustained poor rates can lead to intervention.
Performance
This is the performance impact. The published rate is what the sector, inspectors and governors see.
Audit
Limited directly, though the underlying data problems are the same ones audit tests.
Most likely causes
Ranked, because in practice a few causes explain most cases.
- commonAims that ended with no outcome recordedThe single largest cause. An aim with no achievement recorded counts as a non-achievement.
- commonLearners left open past their planned end dateAn aim that never closes eventually resolves against the college rather than in its favour.
- occasionalA misunderstanding of which aims are in the cohortThe cohort is defined by rules about expected end dates. The college's own view often counts a different population, which explains part of the gap without any data being wrong.
- occasionalPlanned end dates that do not reflect the actual programmePlanned end dates determine which year an aim falls into. Wrong dates move aims between cohorts.
- occasionalWithdrawals recorded against the wrong dateThe date can change whether the aim counts at all, and if so in which year.
Check these first
- Check how many aims in the cohort have no outcome recorded. Start here.
- Check for aims left open past their planned end date.
- Reconcile the cohort the calculation used against the population the college is thinking of.
- Check planned end dates for a sample of programmes against the actual programme length.
OutcomeCompletion statusPlanned end dateActual end date
How to investigate
- Reconcile the cohort before reconciling the rate. Most of the surprise is usually in the denominator.
- Model the rate with the missing outcomes filled in as achievements: the difference tells you how much of the gap is data.
- Look at the pattern by curriculum area. A single area with a results-handover problem can move the whole college's rate.
- Where the year is still open, fix it now. After the final return, nothing can be changed.
In your system
These steps are system-neutral: they describe what has to be true in the data, which is the same whatever software your college runs. We do not publish supplier screen paths we have not verified, because menu locations differ by version and by local configuration, and a confidently wrong instruction is worse than none.
System-neutral
- Rebuild the cohort from your own data using the published methodology for the year.
- Reconcile your cohort against the calculated one and account for every difference.
- Within the cohort, identify aims with no outcome and aims still open.
- Correct anything that is genuinely wrong, while the year is still open.
Building your own map of where each of these lives in your system is the most useful induction document an MIS team can have. How to build one.
How to fix it
- Record the missing outcomes and close the aims that should be closed, before the final return.
- Correct planned end dates where they are genuinely wrong, with a reason recorded.
- Where the rate is correct and the expectation was wrong, explain the cohort definition rather than adjusting the data.
Stop this happening again
Fixing the record clears this case. A control is what stops the next one, so each of these names what to do, who owns it and how often.
A monthly report of ended aims with no outcome, worked to zero throughout the year.
Achievement rate modelled from live data each term and shared with curriculum areas while it can still be influenced.
A results handover agreement with each curriculum area, with a named owner and a deadline per results window.
The rules behind this
Qualification achievement rates are calculated from submitted ILR data. Data-quality problems in the return become published performance problems.
Completion status records whether a learner is continuing, has completed, has withdrawn or has temporarily withdrawn. Outcome records what the learner achieved. They answer different questions and both are needed.
Sources
These are the official documents this page rests on. Where a figure, a deadline or an exact rule matters, the document is the authority and this page is the explanation.
Content reused from GOV.UK is Crown copyright, used under the Open Government Licence. FEFunding is not endorsed by the Department for Education.