The Student/Staff Ratio (SSR) compares the number of staff teaching a subject with the number of students studying it. It is a measure of human resource input that is deemed to affect the student experience and, ultimately, the academic attainment.
It assesses the extent to which Universities are able to provide students with meaningful access to lecturers and tutors, and recognises that a high number of faculty members per student will reduce the teaching burden on each individual academic.
There is not a golden rule for the SSR, because SSRs vary according to course requirements and the nature of teaching within certain subjects.
Where SSR appears?
League tables
A number of national and international league tables use SSR, with slight differences in methods and weights attributed to this metric.
On The Guardian University Guide, SSR constitutes 15% of the University overall score and a low SSR is treated positively.
The Times Higher Education World University Ranking uses the inverse of the SSR, hence Staff/Student Ratio, where it constitutes 4.5% of the University overall score and a high Staff/Student Ratio is treated positively.
The QS World University Ranking uses the inverse of the SSR, hence Staff/Student Ratio, where it constitutes 20% of the University overall score and a high Staff/Student Ratio is treated positively.
Planning
SSR can be used as a proxy for a teaching unit's operational capacity, thus informing planning activities.
Why there are different SSRs for the same department?
Although it only takes two numbers as inputs, there is a wide variety of methods to select which students and staff members will be included in the calculation. A list of factors that affect the selection of the population follows below:
Staff:
- Type of contract (academic, non-academic)
- Academic function (teaching only, teaching and research, research only)
- Terms of employment (typical, atypical contracts)
Students:
- Type of record (“in league tables” students - i.e. students whose records are submitted to HESA, all students)
- Location of study (industrial placement, abroad, franchised)
- Status (will a Post Graduate Research student in the write up stage be included or not?)
Level of aggregation:
- Students (available at programme, department, subject, and cost centre levels)
- Staff (figures are readily available at cost centre level only)
- Multi-department programmes (will students count towards the route owner only or will they be split into the respective departments?)
SSR on the Department Degree Results Explorer
Student/staff ratio shows the total number of students reported to HESA at all levels of study (FTE) per member of staff (FTE).
This metric uses staff data sourced from HESA, therefore subject to HESA rounding and suppression rules. The student numbers stem from internal data sets.
The data set covers both academic and non-academic staff, where academic is defined as those whose academic employment function is not defined as "Research only".
The data set covers only staff in a typical working contract. Atypical contracts are contracts that involve non-permanent working arrangements or complex employment relationships.
The SSR on the workbook has been updated so as to calculate the SSR using only “in league tables” students, i.e. students whose records are submitted to HESA.
The difference stems from the fact that The Guardian uses data from the “HESA Student Staff Ratios by Cost Centre and provider (SSRs) v1” dataset, where they obtain SSR by Cost centre, whereas we use student numbers by department divided by staff FTE by cost centre.
Since Cost centres and JACS codes or Departments do not align, the internal SSR is not a perfect metric, despite being closer to the actual figure.
SSR on RAMP
RAMP reports calculate SSR using student population either by route owner or by department. The route owner numbers are much closer to the HESA figures.
There are some data quality issues with the salary forecaster, which underlies the staff reports on RAMP. In effect you are using two inflated figures to calculate the SSR, when compared to HESA or the workbook I mentioned.
SSR on The Guardian
The Guardian uses data from the a SSR dataset provided by HESA.
Students are selected based on type of record and the FTE is weighted by location of study. Staff are selected by type of contract, academic function and terms of employment.
The figures are aggregated at cost centre level.
The method is thoroughly explained on https://www.hesa.ac.uk/support/definitions/technical#studentstaff-ratios-ssr or on https://www.theguardian.com/education/2019/jun/07/methodology-behind-the-guardian-university-guide-2020
Because a cost centre may encompass multiple subject areas, there is no perfect alignment among departments and cost centres.