The reliability of evidence on disaggregated education data is examined together with the limits that apply when findings inform consequential decisions.
In examining using administrative data to examine disaggregated education data, a proportionate arrangement protects educational outcomes and fair treatment without creating avoidable barriers.
In examining using administrative data to examine disaggregated education data, a national or international pattern may justify closer review of the issue, but provider-level action requires evidence relating to the affected provision.
Implementation of the analysis should be organised around a decision that can be tested. For disaggregated education data, where an indicator is used as a proxy, the relationship between the proxy and the underlying educational outcome should be stated and tested.
Application to disaggregated education data
For administrative data to examine disaggregated education data, the public interest is not confined to institutional compliance.
In examining using administrative data to examine disaggregated education data, an average may improve while a material group experiences no improvement or a worse outcome. For disaggregated education data, disaggregation should follow a defined public-interest question and should protect confidentiality where small numbers could identify individuals.
The principal risks in relation to the comparison are financial or geographic barriers, completion measures detached from learning, admission without adequate support, and aggregate gains concealing excluded groups. In the context of disaggregated education data, the relationship between the risks is material: one failed safeguard may remove the evidence needed to activate another.
Relevant evidence for the issue will normally include records of barriers and support, progression and early-warning information, resource allocation by need, clearly defined access and completion indicators, and disaggregated participation and outcome data. For decisions concerning disaggregated education data, contradictory evidence should be investigated and resolved, not omitted from the record.
Controls for disaggregated education data
The method for the issue is to examine results by relevant learner, programme, location and delivery characteristics; compare both levels and rates of change; and test whether observed gaps persist after differences in coverage and prior conditions are considered. For disaggregated education data, the review record should preserve exceptions capable of showing a weakness in design, implementation or coverage.
Review of disaggregated education data
Interpretation of administrative data to examine disaggregated education data should avoid two errors: treating a formal commitment as proof of effect, and treating one adverse case as proof that every part of the system has failed.
In examining using administrative data to examine disaggregated education data, the present development should inform review of the issue, with attention to the relationship between commitment, implementation and demonstrated outcome.
In examining using administrative data to examine disaggregated education data, use of the findings should remain within the population and analytical level of collection.