It is important to develop a shared language. This should be embedded and modelled at all levels of the system. Acronyms vary and should be explained and important terms should be shared and defined.

There should be clarity around what is meant by the terms ‘data’, ‘evidence’ and ‘research’ and how these interact with each other for school improvement.

Time should be taken to ensure that all educators, learners, partners and stakeholders understand key terminology as appropriate and necessary to each role.

Using data for improvement

Data for improvement can be classified as demographic, input, output, and perception. 

Demographic data

Demographic data refers to data organised by key learner characteristics such as male, female, or the Scottish Index of Multiple Deprivation (SIMD).

Effective use of demographic data

Effective schools or settings ensure that they look at data by demographic groups and characteristics including:

• boys and girls
• English as an Additional Language
• Black and minority ethnic (BAME)
• free school meals
• care experienced
• additional support needs (ASN)
• learners ‘at risk’ of underperformance or poor outcomes

Input data

Input data refers to data or evidence that captures the provision of pedagogical approaches received by learners.

Output data

Output data refers to data or evidence that demonstrates the impact or outcomes for learners. This may be ‘big’ data such as Achievement of a Curriculum for Excellence Level (ACEL) or ‘small’ data such as work in jotters or ongoing reading assessments.

Perception data

Perception data represents the perceptions or views of stakeholders including learners, families, educators and partners.