Advance HE has released new annual reports detailing staff employed by, and the profile of students attending, higher education providers in the United Kingdom (UK).
The (1) staff statistical report 2019 (294 pages); and (2) student statistical report 2019 (220 pages) can be downloaded by those working for our member institutions. Each report is based on data collected by the Higher Education Statistical Agency (HESA).
The reports are the latest in a series of twelve annual reports, offering equality data about staff employed by, and students attending, higher education.
Each report contains data for the academic year 2017-18, and time series data going back to 2003-04. Both reports are accompanied by online data tables that can be downloaded. Separately.
The staff statistical report 2019
The staff report “aims to assist the sector in better understanding the main equality challenges for staff and directing future efforts to overcome them.” The report includes data on a range of workforce characteristics, for example:
The following discussion draws on the data available in the report and the information that can be derived.
Between 2003-04 and 2017-18 the number of staff employed in higher education grew by 23% per cent. Over the same period, the proportion of staff classified as academic rose from 44.4% to 49.3%, while the proportion of professional service staff fell from 55.6% to 50.7%.
The higher education workforce has become more ethnically diverse, with an increase in Black, Asian and minority ethnic (BAME) staff employed. However, there is considerable variation between the four nations of the UK, and individuals from ethnic minority groups are less well-represented in senior management roles or in higher salary bands. There is also considerable variation in proportion of BAME staff employed in different subject areas. (For details, see data in Section 3 of the report, pp.128-195).
Student statistical report 2019
The student report covers both part- and full-time students. The report presents student data in relation to a number of characteristics, including:
- Age – disaggregated by four age groups: 21 and under, 22 to 25, 26 to 35 and 36 and over
- Disability – detailed by type of impairment. Impairment being recorded using one of 11 possible categories. The data also identifies whether a student is in receipt of a disabled students’ allowance (DSA).
- Ethnicity – sub-divided into six groups: Asian, Black, Chinese, mixed, other ethnic background and White
- Religion and belief
How might the student data be used?
The data enables, for example:
- Differences in student characteristics between subject areas to be identified
- Institutions to compare the profile and characteristics of their student body with the national data
- Changing trends to be identified
Table 2.3 (p.79) provides a profile of all/disabled students by impairment type. The Table contains data for the last three years. i.e. 2015-16, 2016-17 and 2017-18.
In 2017-18 disabled students comprise 12.9% of the student population, and non-disabled students 87.1%. The most frequently cited impairments were:
- Special learning difficulty (38.3% of disabled students; 115,865 students; 4.9% of the total student population)
- Mental health condition (23.9%; 72,360 students, 3.1%)
- Two or more impairments (10.3%; 31,300 students, 1.3%)
- Long-standing illness or health condition (9.7%; 29,460 students, 1.3%)
Three-year trends, included:
- The number of students based on the HESA student record who self-assessed themselves as being disabled rose from 256,995 to 302,705. This represented an increase of 17.7%. During the same period the total student population increased by 2.7%. This prompts the question of what are the reasons for the increase in the number of students self-assessing themselves as disabled?
- Looking at the individual impairments, the proportion of students with a mental health condition rose from 44,900 students in 2015-16, accounting for 17.5% of the total number of disabled students; to 72,360 students in 2017-18, representing 23.9% of the total. i.e. a 61% increase. By comparison, over the same period, the number of students with a specific learning difficult increased by 2.1%.
The time series data highlights the rising propensity for students to self-assess themselves as having a mental health disability. Governing bodies might therefore wish to ask whether the experience for their institution mirrors this national trends?
Further, if the institution has experienced a significant increase in the numbers of students declaring that they have a mental health condition how has the institution responded?
Section 3 of the report presents statistical data on ethnicity. For example, Table 3.6 (p.121) breaks down UK domiciled students by subject area and BAME/White identity [Tables 3.7 to 3.10 (pp.122-129)]. There is considerable variation in the ethnic mix of students across different subject areas.
Intersectionality acknowledges that people’s identities and social positions are shaped by multiple factors, and suggests the need to consider how the multiple factors interact. For example, looking at age and disability status, the data shows (Table 5.2) that “disclosing a mental health condition, social communication/autistic spectrum learning difficulty tended to have a younger age profile.” (p.168)
The two statistical reports provide a rich source, allowing institutions to benchmark their staff and student profiles against national data.
By reviewing the comparative data, governors can assess the extent to which their institution mirrors the average values for the sector, and the extent to which there is a need for either further investigation of an issue or further action.