Transparency tables
Introduction
1. This regulatory advice sets out guidance for higher education providers in England that are registered with the Office for Students (OfS). Section 9 of the Higher Education and Research Act 2017 (HERA) requires the OfS to ensure that the ongoing conditions of registration for certain providers includes a transparency condition.
2. This mandatory condition will apply to all registered higher education providers in either the Approved or Approved (fee cap) part of the register, once regulations are made by the Secretary of State pursuant to section 9 of HERA. The regulations have been approved by both Houses of Parliament in accordance with section 119 of HERA and we expect them to be made in December 2018. We are issuing this guidance now to give providers more time to take preparatory steps in relation to the transparency requirements.
3. This guidance sets out what you must do once you are registered, to prepare to comply with the ongoing condition of registration relating to transparency information. More detailed technical requirements will be published in February 2019 and you will need to comply with these. This guidance should be read in conjunction with the OfS’s regulatory framework (OfS 2018.01) which sets out in full the approach that we will take to the regulation of providers. If there are any inconsistencies between the regulatory framework and this document then the regulatory framework will prevail.
What is the transparency information condition?
4. Our regulatory framework contains an ongoing condition of registration that applies to providers in either the Approved or Approved (fee cap) part of the register:
Condition F1: The provider must provide to the OfS, and publish, in the manner and form specified by the OfS, the transparency information set out in section 9 of HERA.
5. The transparency information means the information we request in relation to the following:
a. The number of students who attained a particular degree or other academic award, or a particular level of such an award, on completion of their course with the provider.
6. In each case, the information that we ask you to provide may include those numbers by reference to the following:
a. The gender of the individuals to which they relate.
b. Their ethnicity.
c. Their socioeconomic background.
It is important to note that the data presented has not been contextualised. This means, for example, that you will not be able to see from this data how many of those applying to courses met the entry criteria. It is also the case that universities and colleges will often receive many more applications than they have spaces on courses and so offer rates will necessarily be lower than application rates in those circumstances
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Download the full Transparency Return 2021 (MS Excel)...
Tables
| Characteristic | Characteristic split |
Percentage |
|---|---|---|
| Ethnicity | BAME | 71% |
| White | 82% | |
| EIMD 2019 quintile | 1 and 2 | 74.2% |
| 3 to 5 | 84.0% | |
| Gender | Female | 78.1% |
| Male | 80.6% | |
| Other | N |
| Mode of Study | Characteristic | Characteristic split | Headcount of classified First Degrees awarded | Percentage of classified First Degrees awarded as first class | Percentage of classified First Degrees awarded as upper second class | Percentage of classified First Degrees awarded as lower second class | Percentage of classified First Degrees awarded as third class / pass | Headcount of unclassified First Degrees awarded | Headcount of other undergraduate awards |
|---|---|---|---|---|---|---|---|---|---|
| Full-time | Ethnicity | Asian | 550 | 30% | 45% | 20% | 5% | N | 50 |
| Black | 190 | 15% | 45% | 30% | 10% | N | N | ||
| Mixed | 120 | 30% | 45% | 20% | 5% | N | N | ||
| Other | 60 | 20% | 65% | 15% | DP | N | N | ||
| White | 2450 | 35% | 45% | 15% | 5% | 30 | 220 | ||
| Unknown | 50 | 40% | 50% | 10% | DP | N | N | ||
| EIMD 2019 quintile | 1 | 1100 | 29% | 43% | 22% | 5% | N | 120 | |
| 2 | 650 | 34% | 42% | 20% | 3% | N | 60 | ||
| 3 | 470 | 36% | 47% | 15% | 3% | N | 40 | ||
| 4 | 560 | 36% | 47% | 14% | 3% | N | 40 | ||
| 5 | 530 | 41% | 45% | 12% | 2% | N | 40 | ||
| N/A | 120 | 38% | 52% | 11% | DP | N | N | ||
| Unknown | N | N | N | N | N | N | N | ||
| Gender | Female | 1910 | 34.6% | 43.4% | 18.6% | 3.5% | N | 140 | |
| Male | 1510 | 33.9% | 46.6% | 16.2% | 3.3% | N | 170 | ||
| Other | N | N | N | N | N | N | N | ||
| Part-time | Ethnicity | Asian | N | N | N | N | N | N | N |
| Black | N | N | N | N | N | N | N | ||
| Mixed | N | N | N | N | N | N | N | ||
| Other | N | N | N | N | N | N | N | ||
| White | 80 | 44% | 44% | 12% | DP | N | 40 | ||
| Unknown | N | N | N | N | N | N | N | ||
| EIMD 2019 quintile | 1 | N | N | N | N | N | N | N | |
| 2 | N | N | N | N | N | N | N | ||
| 3 | N | N | N | N | N | N | N | ||
| 4 | N | N | N | N | N | N | N | ||
| 5 | N | N | N | N | N | N | N | ||
| N/A | N | N | N | N | N | N | N | ||
| Unknown | N | N | N | N | N | N | N | ||
| Gender | Female | 50 | 45% | 35% | 15% | DP | N | N | |
| Male | 40 | 40% | 50% | 15% | DP | N | 30 | ||
| Other | N | N | N | N | N | N | N | ||
| Apprenticeships | Ethnicity | Asian | N | N | N | N | N | N/A | N |
| Black | N | N | N | N | N | N/A | N | ||
| Mixed | N | N | N | N | N | N/A | N | ||
| Other | N | N | N | N | N | N/A | N | ||
| White | N | N | N | N | N | N/A | 70 | ||
| Unknown | N | N | N | N | N | N/A | N | ||
| EIMD 2019 quintile | 1 | N | N | N | N | N | N/A | 40 | |
| 2 | N | N | N | N | N | N/A | N | ||
| 3 | N | N | N | N | N | N/A | N | ||
| 4 | N | N | N | N | N | N/A | N | ||
| 5 | N | N | N | N | N | N/A | N | ||
| N/A | N | N | N | N | N | N/A | N | ||
| Unknown | N | N | N | N | N | N/A | N | ||
| Gender | Female | N | N | N | N | N | N/A | 70 | |
| Male | N | N | N | N | N | N/A | N | ||
| Other | N | N | N | N | N | N/A | N |