Exploring student outcomes data dashboard

Use the buttons in the top left of the dashboard to select a student outcome across which percentage point differences between student groups will be reported. 

You can choose from the following three outcomes, as proposed in our consultation: 

• Continuation: A continuation indicator that measures the percentage of students that continue in the study of a higher education qualification (or have gained a qualification) after one year (two years for part-time students). 
• Completion: A completion indicator that measures the percentage of students that complete a higher education qualification, which we propose to base on either tracking individual entrants, or by calculating the proportion of students likely to complete the qualification they started, through up to six subsequent years of study.
• Progression: A progression indicator constructed from the Graduate Outcomes survey data that measures progression to managerial or professional employment, or further study, 15 months after a higher education qualification has been awarded.  

Use the buttons at the top to select the population of students under consideration in the analysis. You can choose from the following groups:

• Student domicile: UK domiciled or non-UK domiciled
• Level of study: undergraduate or postgraduate
• Mode of study: full-time or part-time.

It should be noted that different student populations relate to different academic years included in the analysis and that data is not available for all combinations of outcomes and populations (see ‘What is the coverage of this analysis?’ on our frequently asked questions webpage). The dashboard will prompt you to adjust the filters if this is the case.

Use the buttons labelled ‘Select characteristic’ and ‘Select category’ to choose a group of students for whom differences in the chosen outcome will be reported, relative to a pre-defined reference group. 

You can select multiple categories within one characteristic, which will be shown above one another in the dashboard.

The reference group – from which differences in student outcomes are taken – is shown in bold text in the title above the chart.

Use the button on the right hand side to control for multiple groups of factors when estimated differences in student outcomes are reported.

These groups of factors correspond to the inclusion of terms in a statistical model, which is used to estimate differences in student outcomes while accounting for underlying differences in the factors chosen.

To see the full list of factors included in one of these groups, either use a mouse to hover over the relevant bar in the chart or see the data file associated with this dashboard (available below).

When controlling for ‘No other factors (actual difference)’, the differences shown in the chart correspond to the actual percentage point difference in the chosen outcome between the two student groups, averaged over the period.

When selecting ‘All factors’ or ‘All factors (except provider)’, the estimated differences account for all factors in all the other groups listed above (except provider where stated).

For more information on the interpretation of these charts, see the question ‘What does it mean when the bars change in size after controlling for other factors?’ in our frequently asked questions.

This dashboard seeks to better understand the extent to which observed differences in student outcomes for the following characteristics can be accounted for by other underlying factors:

• age group
• disability type
• ethnicity
• sex
• Index of Multiple Deprivation (IMD) quintiles
• Tracking Underrepresentation by Area (TUNDRA)
• free school meals eligibility.

The underlying factors we account for include a number of student and course characteristics which vary across student groups. Our analysis looks at this for various populations of students at English higher education providers.

It is important to note that the statistical modelling included in this analysis can only account for factors which we can observe in the data. It is possible that there remain unobserved factors correlated both with the student characteristic of interest and with the outcome itself. These unobserved factors could introduce statistical bias. For this reason, users should not interpret the estimates in this release as reflecting causal relationships.

Further information about these experimental statistics is available in our Exploring student outcomes report.

You can also read our frequently asked questions.

Download the Excel data file for this dashboard.