PIs 2007/08: Widening participation of under-represented groups - definitions (tables T1, T2)
Coverage
Higher education (HE) students are those students on programmes of study for which the level of instruction is above that of level 3 of the National Qualifications Framework, i.e. courses leading to the Advanced Level of the General Certificate of Education (GCE A levels), the Advanced Level of the Vocational Certificate of Education (VCE A levels) or the Advanced Higher Grade and Higher Grade of the Scottish Qualifications Authority (SQA) Advanced Highers/Highers).
The data used in constructing the indicators have been taken from the HESA database. The data specification of the record uses the term 'instance' to describe a student's engagement with the institution, which, because a student can have more than one instance of engagement, will exceed the number of students. Postdoctoral students are not included in the HESA Student Record.
All students included in the tables are those whose normal residence is in the United Kingdom, excluding Guernsey, Jersey and the Isle of Man. This information comes primarily from the HESA POSTCODE field, with the DOMICILE field used if there is no valid postcode supplied. If neither field supplies valid information, it is assumed that the student is resident in the UK. Incoming and visiting exchange students and students studying for the whole of their programme of study outside the UK are excluded from the tables.
Age
Many of the tables are split between young and mature students, defined as follows:
- Young students are those who are aged under 21 at 30 September of the academic year in which they are recorded as entering the institution. So for students recorded as entering an institution in 2007/08, young students are those born after 30 September 1986.
- Mature students are those who are aged 21 or over, also at 30 September of the academic year in which they are recorded as entering the institution.
Students whose date of birth is not given, or whose date of birth suggests that they are under 10 years, are allocated to age group ‘unknown’. For tables which provide information about young students, mature students, and all students, this means that the numbers under ‘All students’ are not necessarily the sum of ‘Young students’ and ‘Mature students’.
Mode of study
- Full-time students are those recorded as studying full-time at an institution, or on thick or thin sandwich courses, provided that the length of the course is at least 24 weeks.
- Part-time students are those recorded as studying part-time, or full-time on courses lasting less than 24 weeks.
Level of study
The level of study is taken from the qualification aim of the student. Only undergraduate students are included in Tables T1 to T2 at present. First degree students are those studying for any type of first degree; other undergraduate students are those studying for foundation degrees, diplomas, certificates and other undergraduate courses. The codes for qualification aims (HESA field COURSEAIM) used to define the level are shown below.
| 2007/08 COURSEAIM codes | |
| First degree | M22, H00, H11, H16, H18, H22, H23, H24, H50, I00, I11, I16 |
| Other undergraduate | H41, H42, H43, H60, H61, H70, H71, H72, H76, H78, H80, H81, H88,
I60, I61, I70, I71, I72, I74, I76, I80, I81, J10, J16, J20, J26, J30, J41, J42, J43, J45, J76, J80, C20, C30, C41, C42, C43, C80 |
Entrants
Tables T1 to T2 provide information about entrants to an institution. These are defined as students who started a programme of study at that institution during the academic year of interest. This is based on the commencement date of the student’s study (HESA field COMDATE). While most entrants go into the first year of a programme of study, some will start on the second, or later, year of programme, for example if they transfer from another institution. Entrants who are recorded as leaving before 1 December (HESA field ENDDATE) have not been included in the calculations, unless the record contains important information such as a qualification. It has been agreed that students leaving this early in their studies should be disregarded for the purposes of the performance indicators.
Type of school
School type is taken from previous institution attended (HESA field PREVINST). All schools or colleges that are not denoted ‘independent’ are assumed to be state schools. This means that students from sixth-form or further education colleges, for example, are included as being from state schools.
Socio-economic classification
The information on socio-economic classification is taken from the National Statistics Socio-Economic Classification (NS-SEC). The classifications used are:
1 Higher managerial and professional occupations
2 Lower managerial and professional occupations
3 Intermediate occupations
4 Small employers and own account workers
5 Lower supervisory and technical occupations
6 Semi-routine occupations
7 Routine occupations
The performance indicator is the proportion of students from NS-SEC classes 4 to 7 (HESA field SEC codes 4, 5, 6 and 7) out of those from NS-SEC classes 1 to 7. NS-SEC class 8, long-term unemployed or never worked, has been included with unknown classification for the purposes of the performance indicators.
Low-participation neighbourhoods (POLAR2)
A new method for producing the low participation neighbourhoods has been used from 2006/07 onwards and is not comparable with the old (Super Profiles) low participation data published previously.
The low particpation indicator has been produced using POLAR2. This method is based on the HE participation rates of people who were aged 18 between 2000 and 2004 and entered a HE course in a UK higher education institution or GB further education college, aged 18 or 19, between academic years 2000/01 and 2005/06.
It draws on data provided by the Higher Education Statistics Agency, the Learning and Skills Council, the Universities and Colleges Admissions Service, the other UK funding bodies and HM Revenue & Customs.
The POLAR2 classification is formed by ranking 2001 Census Area Statistics wards by their young participation rates for the combined 2000 to 2004 cohorts. This gives five young participation quintile groups (qYPR) of areas ordered from '1' (those wards with the lowest participation) to '5' (those wards with the highest participation), each representing 20 per cent of UK young cohort. Students have been allocated to the neighbourhoods on the basis of their postcode. Those students whose postcode falls within wards with the lowest participation (quintile 1) are denoted as being from a low participation neighbourhood.
More information on the POLAR2 classification and the files used in the mapping can be found on the HEFCE website.
Localised effects
Under certain conditions the location of an institution can have an impact on the low participation neighbourhood indicator, making it appear different from the other widening participation indicators. In particular, there are several characteristics which have an impact on institutions in London and Scotland.
In London, institutions tend to recruit a high proportion of students from this area. The participation rate overall is higher in London than for most other parts of the country. These factors taken together mean that areas in London may be less likely than similar areas elsewhere to be classed as low participation. As a result, institutions in London tend to have a lower proportion of students from low participation neighbourhoods relative to their benchmarks.
In Scotland, again institutions tend to recruit a high proportion of students from the local area. The old low participation indicator clustered together very small areas (enumeration districts or data zones) that were judged to be similar in terms of the values of a range of census 1991 variables. The resulting 160 GB clusters each then contained a large enough population for which to calculate participation rates, and it was on the basis of these calculated rates that the designation as low participation or not was made. The disadvantage of this was that areas within a cluster were not necessarily close together, so many of the clusters formed using Scottish data zones also included numbers of English enumeration districts. This meant that the high participation rates in many of the poorer areas of Scotland (high relative to those in England) were ‘diluted’ by those English areas. The POLAR2 low particiaption method uses the more numerous and smaller Census Area Statistics wards as the units for calculating participation rates so this dilution no longer occurs and the high participation rates in Scotland are correctly recorded. The participation measure also includes HE that takes place in FE colleges and is returned on non-HESA records. Previous work by HEFCE (2005/03) showed that this type of participation in FECs is much more prevalent in Scotland than in England and Wales, particular so for poorer areas (HEFCE 2005/03, page 42). Both these effects act to substantially reduce the proportion of areas in Scotland that are classified as having low participation relative to the rest of the UK. In turn this has acted to lower the low participation area performance indicator for any institution that has substantial recruitment from Scotland. For this reason, low participation data for Scottish Institutions have been excluded from the Performance Indicators.
Measuring effects of locality
Supplementary Table SP1 shows the percentages of young entrants from each of the regions of the UK who come from low participation neighbourhoods (POLAR2); NS-SEC Classes 4, 5, 6 and 7; and state schools. The scale of the differences between regions means that institutions which recruit most of their students locally may find they have characteristics quite different from the national average.
Because of these differences, we have looked at ways in which a student’s domicile could be incorporated into the existing benchmarks of the widening participation indicators. Using the same methodology as is used for the current benchmarks, and taking the student’s region of origin as another factor, we have produced a value that will give an indication of how important the location factor is. This is the location-adjusted benchmark.
For institutions which recruit from across the UK, there is very little difference between the standard benchmark and the location-adjusted benchmark. Institutions which recruit more locally will have larger differences, possibly 3 or 4%, between the original and the location-adjusted benchmark. These larger differences show that the indicator is affected by the characteristic of the area the institution recruits from. In general, the greatest differences occur for the low participation indicator, and the smallest for the NS-SEC indicator.
Questions
In considering how best to measure locality effects, a major concern was raised. By allowing for the effects of locality, there is a danger that what we are trying to measure could be partly obscured. Differences between geographical areas may be caused by disparities between institutions, or these disparities may be the result of geographical differences. Until we have resolved this circularity we need to be careful in making allowances for geographical effects.
There is a further difficulty with the method used. In theory, if an institution situated in a region of low participation were to recruit predominantly from another region of high participation, that institution’s benchmark would not reflect its locality. Rather, it would reflect the locality from which its students were recruited. In practice that is unlikely to happen, partly because we have used region rather than some smaller geographical area as the basis.
The location-adjusted benchmark has only been used with the participation indicators, because of the known differences in the way these groups are spread across the country. They have not been used with the indicators of retention or non-continuation, nor is there any plan to do so, for two reasons. The major reason is that to include location as a factor in non-continuation would imply that people from different regions could have different continuation rates, even taking into account their subject of study and their entry qualifications. This would not be acceptable. A further reason is that the differences between the non-continuation rates for students from different regions is small. A location-adjusted benchmark for these indicators would therefore not provide any extra information.
Benchmarks
For definitions of the fields used to create the benchmarks, please refer to the benchmarks document. These fields include:
- subject of study
- entry qualifications
- region of domicile.
Context statistics
Two additional context statistics have been provided for the indicators in Tables T1, T2 and T3. These are:
- the average number of institutions in the adjusted sector benchmark comparison
- the average proportion which the institution’s own students contribute to the benchmark
These context statistics are provided for both the original benchmark and the location adjusted benchmark in Tables T1 and T2.
It is important to note that both of these statistics are average values. The numbers do not relate to specific institutions. The interpretation is fairly straightforward. If the average number of institutions in the comparison is small, say less than 20, then there are not many institutions whose students are similar to the one in question. If the students at the institution contribute a large proportion to the benchmark, say more than 20 per cent, then the adjusted sector benchmark will be similar to the institution’s own value. For the original benchmarks, very few institutions have a small number of comparable institutions or contribute a large proportion to the benchmark. For the location-adjusted benchmarks, the number of comparable institutions is likely to be smaller and the average contribution to the benchmark is likely to be larger than for the original benchmarks, and so the location-adjusted benchmarks are generally closer to the indicators than are the original benchmarks.
These statistics are designed, in particular, to pick up situations where the benchmark is of limited use because there are few other institutions that really are comparable.
Average number of institutions in comparison
The calculation of the two context statistics is based on the sector grid of entry
qualifications and subject of study (please refer to the benchmarks document for details). For each cell in the grid, we count the number of institutions with students in that cell. Let this number be nij for
subject i and entry qualification j. For the institution of interest, call the number of its students t,
and let tij be the number studying subject i with entry qualification j. Then for each cell compute 
, and sum these values over all cells. So the required value is:
average number of institutions in comparison 
Average contribution to benchmark
To find the contribution of the institution’s students to the benchmark, we use a similar
weighted average, but now of the proportion of each cell’s students who come from the
institution. If the number of students in the sector who are studying subject i and have entry
qualification j is Tij, then in any cell the institution’s students form a proportion 
of the total,
and the context statistic is the weighted average of these values, namely
average contribution to the benchmark 
Rounding strategy
Due to the provisions of the Data Protection Act 1998 and the Human Rights Act 1998, HESA implements a strategy in published and released tabulations designed to prevent the disclosure of personal information about any individual. This strategy involves rounding all numbers to the nearest 5. A summary of this strategy is as follows:
- 0, 1, 2 are rounded to 0
- All other numbers are rounded to the nearest 5.
So for example 3 is represented as 5, 22 is represented as 20, 3286 is represented as 3285, while 0, 20, 55, 3510 remain unchanged.
This rounding strategy is also applied to total figures; the consequence of which is that the sum of numbers in each row or column will rarely precisely match the total shown.
Average values, proportions and FTE values prepared by HESA will not be affected by the above strategy, and will be calculated on precise raw numbers. However, percentages and indicators calculated on populations which contain less than 20 individuals will be suppressed and represented as a blank value.
Enquiries
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Enquiries regarding the Performance Indicators Steering Group (PISG)
should be directed to the HEFCE Press Office on 0117 931 7307
