Who studies SHAPE?

The dashboard uses area-based measures of deprivation as proxies to present inequalities in participation across UK higher education.

To measure deprivation, the dashboard uses the Indices of Multiple Deprivation for each UK domicile:

• England: IMD
• Scotland: SIMD
• Wales: WIMD
• Northern Ireland: NIMD

These are place-based measures reflect the area where a student lived before entering higher education, not their individual or household circumstances. They are only available for students with a permanent UK address. They are used across the dashboard, particularly in Section 2 (student characteristics) and Section 3 (regional mobility). This allows us to explore how participation and mobility vary across the socio-economic spectrum.

This is not a perfect measure, and it does not capture individual circumstances, thus people living in the same area may have very different experiences. Each UK domicile also constructs its deprivation index differently, using its own data and methodology.

For this reason, deprivation is best understood here as a way of describing a student’s context rather than a precise measure of disadvantage. Even so, it remains one of the most widely used ways to explore inequalities in participation across the system.

Please note that Scotland is not included in the most recent year of the deprivation breakdowns, as the latest Scottish deprivation index data was not available when the dashboard was produced.

How to interpret deprivation in this dashboard:

• Students are grouped into deprivation quintiles within each UK domicile, ranging from Quintile 1 (most deprived) to Quintile 5 (least deprived). These quintiles are constructed separately within each domicile. Each chart indicates the UK domicile being analysed, either through filters or titles, and it is important to keep this in mind when interpreting results. Because these deprivation indices are designed differently, a quintile in one domicile is not directly comparable to the same quintile in another. For this reason, the most robust comparisons are those made within a single domicile. Cross-UK views should be read as illustrative rather than strictly comparable.
• Deprivation is also best interpreted alongside other indicators in the dashboard. For example, in the regional mobility section, students from more deprived areas are more likely to remain in the parental home and less likely to move away. This suggests that mobility is not only a matter of preference, but also reflects constraints linked to socio-economic background.

The dashboard looks at where students come from and where they study, using a region-based measure of mobility and only for UK domiciled students. This is based on comparing their domicile region, where they lived before entering higher education, with the region of their provider.

We focus on first-year, first-degree students, as this most closely reflects initial access decisions. Using this approach, students are grouped into three categories, those who study in their home region, those who study outside their home region, and those who cross a regional boundary while continuing to live in the parental home.

This last group is small but important. It shows that crossing a regional boundary does not always mean relocating, and in some cases may reflect constraints such as long-distance commuting.

How should this measure be interpreted?

• There are different ways to think about student mobility, including distance travelled or commuting time. This dashboard uses regions as a consistent way to look across the whole system, but this comes with some limitations.
• Regional boundaries do not reflect distance, so moving across regions can mean very different things, from short distance travel to long distance relocation. The measure also does not capture travel time or cost. Even so, it provides a clear way to compare patterns across subjects, places and groups, and to understand how access to higher education is shaped by geography.
• The regions and nations used in the dashboard are the nine statistical or administrative regions of England (East of England, East Midlands, London, North West, North East, South East, South West, West Midlands, Yorkshire and the Humber) and the devolved administrations of Northern Ireland, Scotland and Wales. This means the dashboard does not fully capture all types of movement.
• Notably, it does not show movement within UK regions or nations, for example within Scotland, Wales or Northern Ireland. It may also insufficiently capture short distance commuting across regional boundaries. This reflects how the data are structured, as mobility is measured according to students’ crossing regional or national boundaries rather than by measuring continuous distance.

Student numbers are based on Full Person Equivalent (FPE), which accounts for students whose activity may be split across subjects or modes of study. This allows more consistent aggregation across the system than simple headcounts.

The data covers students registered at UK higher education providers within the standard registration population (1 August to 31 July), including all students studying towards a recognised qualification.

All counts follow HESA’s standard rounding methodology:

• counts are rounded to the nearest multiple of 5
• small values may be suppressed
• percentages based on small groups may not be shown

These rules are applied after calculations, meaning totals may not sum exactly across rows or charts. This is intentional and ensures that individuals cannot be identified from published data.

All characteristics in this dashboard (age group, ethnicity, disability and sex) are reproduced exactly as provided following the coverage and definitions used by HESA, to remain consistent with the source data.

No. Some characteristics (such as ethnicity or certain socio-economic indicators) are only collected for UK-domiciled students and are presented on that basis.

This reflects how the HESA Student record is collected, where some variables rely on UK administrative data sources or postcode-linked measures.

Subjects are based on the Common Aggregation Hierarchy (CAH) classification used in HESA data. From 2015/16 onwards, subject data are structured consistently enough to allow analysis using CAH-based groupings without requiring extensive back-mapping from earlier classification systems.

The dashboard uses a combination of:

• Granular subject groupings (broadly aligned with CAH level 3) for detailed analysis
• Aggregated subject groups (e.g. “Business and Management”, “Languages and Area Studies”) for clearer interpretation and more stable trends

The classification of subjects into SHAPE and non-SHAPE follows HESA subject definitions.

This means that:

• only subject areas classified within the relevant social sciences, humanities and arts domains are included in SHAPE
• subjects that fall outside these definitions are grouped under non-SHAPE subjects

For example:

• Human and Social Geography is included within SHAPE
• other areas of geography that are classified as physical or environmental sciences fall under non-SHAPE subjects

This ensures consistency with official data standards and avoids subjective reclassification.

Domicile refers to a student’s permanent home prior to entry to higher education and is used consistently across the dataset for geographic analysis.

Using domicile allows:

• alignment with regional and deprivation measures (which are place-based)
• consistent comparison between UK and international students
• clearer interpretation of where students are coming from, rather than legal status

Nationality is still available in the dataset but is not used as the primary geographic variable in this dashboard.