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Access and Widening Participation in College HE

Briefing Paper 1: Widening Participation Measures and Indicators

February 2015 Author: Dr Viv Wylie, MBE, Action on Access

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Contents

Introduction ........................................................................................................ 3

National and Institutional Measures for Widening Participation ................ 4

Life Cycle approach ............................................................................................ 5

Target Groups ...................................................................................................... 6

Measurement ..................................................................................................... 7

POLAR3 and Low Participation Neighbourhoods (LPNs) ............................... 8

Indices of Multiple Deprivation (IMD) .............................................................. 9

Income Deprivation affecting Children Index (IDACI) .................................. 10

National Statistics Socio-Economic Classification (NS-SEC) Four to Seven 11

Free School Meals ............................................................................................. 12

First in Family .................................................................................................... 12

Using the Measures: Implications for Colleges ............................................. 13

Reflective Questions ........................................................................................ 14

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Introduction

This is the first in a series of briefings on aspects of college higher education (HE) sponsored

by Association of Colleges (AoC) and Action on Access. The briefings describe key concepts

and models of practice and realistic ways to implement widening participation policies and

practices. The briefings will be useful for all colleges that receive HEFCE the student

opportunity grant. The other guidance notes in this series of briefings will examine:

Student success and retention;

Effective and collaborative outreach;

Evaluation.

Measures and indicators for targeting students and evaluating performance in respect of

widening participation are challenging for most institutions. The recent AoC survey of 63

further education (FE) colleges indicated that a number of institutions, while employing a

diversity of measures, were generally more comfortable with monitoring than targeting and

evaluation.

Widening participation has a long history during which it has shifted criteria and changed

practice. In the last few years monitoring and evaluation have become more central as

governments have asked whether and how participation patterns are responding to widening

participation investment. For example, since 2005 the Office for Fair Access (OFFA) has

required an access statement, or evidence based plan for supporting and improving widening

participation strategies across the student life cycle, where college higher education (HE) is

directly funded and attracts fee income above the basic level. As a result measures have

become smarter and the collection and analysis of data more critical.

Widening participation students are those students who are under-represented in higher

education because they are subject to various forms of disadvantage. National measures

have been developed which aim to identify these students by proxy. This paper attempts to

contextualise six key indicators currently in use and clarify what they measure and how they

can be useful.

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National and Institutional Measures for Widening

Participation

Widening participation to HE is a key strategy for the social equality agenda and a

considerable amount of public finance has been invested in it. As a result governments and

institutions alike wish to know how successful the strategy is and how effectively the money

has been spent. National measures to define and identify the widening participation cohort

have become a key toolkit in this endeavour.

At the macro level Higher Education Statistics Agency (HESA) provides national widening

participation performance indicators on which higher education institutions (HEIs) rely quite

heavily to determine and benchmark their performance. FE colleges which have directly

funded HE provision, however, are not represented in HESA statistics and so until recently

have not been able to benchmark themselves against this range of national criteria. Since

2012 the Higher Education Funding Council for England (HEFCE), recognising the information

gap in HE provision in FE colleges, has undertaken two annual exercises to return statistics

for HE students registered at FE colleges in respect of widening participation and non-

continuation,1 and in the second publication (2013) has also included employment indicators

for students completing in 2010-11.

This work currently does not include part time or mature students. However, all the

indicators and the sector adjusted averages are “as consistent as possible” with HESA

performance indicators (PIs). This means that the HEFCE published data can sit alongside the

relevant HESA indicators and make available some valuable sector level comparisons. The

2013 publication shows that the sector adjusted average for widening participation in respect

of all full-time undergraduates registered in FECs in 2010/11 was 16% and in HEIs was 10.6%,

for non-continuation it was 21% (HEIs 16.1%) and for employment it was 92.8% (HEIs 94.2%).

However, HESA data needs to be considered in context. Firstly the data applies to the

previous year and arrives too late for prompt intervention. Secondly national statistics

capture enrolments but not pre-entry students on outreach activities who may or may not be

recruited to the providing institution2 and who should be identified as belonging to the target

group in order to evaluate the effectiveness of the college’s outreach strategy.

1 Higher Education Indicators for Further Education Colleges, 2012 and 2013.

2 The tracking of outreach students is a national problem in recognition of which HEFCE has supported the

extension of HEAT, the HE Access Tracker System.

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Nevertheless FE colleges, like HEIs, are still accountable for their individual performance on

widening participation, whether or not they submit access agreements to OFFA.

Consequently FE colleges need to be confident that they have engaged the target cohort and

are therefore able to support widening participation colleges successfully at all stages of their

journey. The use of national measures which enable clarity and comparability is a key

requisite in the demonstration of a robust institutional approach to widening participation.

Life Cycle Approach

Emerging concerns about under performance by students from poor backgrounds and ethnic

minorities have made it imperative that widening participation strategies include support at

all stages of the student’s journey. OFFA’s Director of Fair Access, Professor Les Ebdon, makes

the point:

An effective approach to access should not stop at the front door when a person enters

higher education. Disadvantage can follow you like a shadow down the years, affecting the

degree you end up with and your ensuing postgraduate study or search for a job. For access

to be meaningful, there must be appropriate support for students as they progress through

their studies and continue to employment or postgraduate study.3

Widening participation is now regarded as encompassing the cycle from pre-entry support

through to successful completion and entry into the next phase of work or education.

3 OFFA Press Release, July 7 2014.

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Target Groups

The primary challenge for any institution is to be able to identify the widening participation

students both in terms of outreach groups and those enrolled. Before national measures

were extensively used by practitioners widening participation students were identified as a

range of groups under-represented in HE nationally – Black, Asian and Minority Ethnic

groups, people with disabilities, first in family to go to HE, people from low income

backgrounds, travellers, vocational students, adult students, white working class males, Afro

Caribbean males - among whom there were many individuals who did not meet the criterion

of disadvantage. By 2006 a HEFCE review of Aimhigher reduced the criteria for widening

participation to disability and belonging to National Statistics Socio-Economic Classification

(NSSEC) categories four to seven. Care leavers were later added as a separate category. The

current OFFA advice on who is defined as a widening participation students, that is,

belonging to under-represented groups or OFFA countable groups, is as follows:

…groups that are currently under-represented in higher education at the national level

rather than at a particular institution or course including (but not limited to)

people from low income backgrounds

people from lower socio-economic groups

people from low participation neighbourhoods

some ethnic groups or sub-groups

people who have been in care

disabled people4

In view of this definition it is important to use indicators which will clearly identify these

groups.

4 OFFA 2014, How to produce an Access Agreement for 2015/16, Questions and Answers on Drawing up you

r2015/16 Access Agreement (Students covered by access agreements).

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Measurement

Broadly speaking measures of disadvantage are based on geographical areas (e.g.

Participation of Local Areas (POLAR), Indices of Multiple Deprivation (IMD), Income

Deprivation Affecting Children Index (IDACI) and on individual level characteristics (e.g.

NSSEC, free school meals (FSM), HE Heritage) which identify socio-economic status.5 These

measures mostly support each other but they do frequently overlap and even when there is

good correlation there are inevitably individuals who do not conform to statistical norms.

Some indicators are more relevant to widening participation than others which measure

different constituents of disadvantage. Some measures are more difficult to use in terms of

the accessibility or validity of the relevant data and some are more appropriate to targeting

possible cohorts than to monitoring individuals. The Supporting Professionalism in

Admissions (SPA) report on Contextualised Admissions usefully summarises the problem of

Performance Indicators as follows:

data collected from applicants (such as the socio-economic status of the household) can be

hard to verify; data relating to the circumstances of an individual’s school/college

experience can be hard to match to applications in a consistent way; and postcode data

relating to an applicants’ neighbourhood/community may not reflect individual

circumstances.6

It is always good practice, therefore, to use a number of indicators in relation to each other as

there is no one completely accurate indicator.

The following looks at some key indicators for widening participation which could be used

together to produce individual student profiles and institutional evaluations of performance.

5 See Aimhigher: A brief guide to data sources on HEA websitefor more detail. This is useful despite the fact that

it only relates to targeting young students who would not otherwise progress to HE. 6 Contextualised Admissions: Examining the Evidence, Joanne Moore, Anna Mountford-Zimdars, Jo Wiggans

2013, p2.

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POLAR3 and Low Participation Neighbourhoods

Low participation neighbourhoods (LPN) is a key HESA PI7 for young full-time students. From

2011/12 it has been based on POLAR3, a UK wide measure which identifies the relative rates

of progression of young students to HE. It does not seek to link low participation with any

other deprivation factor such as poor backgrounds. POLAR3 is based on 18 to 19-year-olds

entering HE between 2005-6 and 2010-11.8 It works by ranking the 2001 Census Area

Statistic9 wards according to young participation for these cohorts in five Quintiles, each

Quintile containing 20% of the young population. The majority of those who fall into Quintile

one (i.e. the lowest participation area) will constitute the widening participation cohort. This is

a key measure since it is the only one which addresses the issue of young participation and

correlates well with other measures of disadvantage.

There is a small likelihood that not all young students living in Quintile one wards will be

widening participation students as identified by economic disadvantage.10 Conversely there

is a fair chance that some widening participation students as defined by socio-economic

disadvantage reside in other Quintiles. However, POLAR3/LPN is a robust national measure

used by HESA and by HEFCE in respect of HE indicators for FE colleges. Indeed, OFFA lists

those from LPNs as a target constituency per se and so can be used for targeting outreach on

schools in Quintile one neighbourhoods and for evaluating institutional performance in

terms of actual recruitment.

7 This measure is flexed slightly by HESA for mature and part-time students as some mature students have a

degree and NSSEC/School information for part-time can be difficult to obtain. Here the widening participation

cohort is defined as those who come from a low participating neighbourhood and do not have a first degree.

8 See HEFCE website for POLAR 3 data maps of young participation in the UK.

http:www.hefce.ac.uk/whatwedo/wp/ourresearch/polar/mapofyoungparticipationareas/

9 These wards, of which there are 8,850, were created for the 2001 census and are largely identical with political

wards except that in some cases small wards have been merged. 10

Further Information on POLAR3: An Analysis of Geography, Disadvantage and Entrants to Higher Education,

HEFCE, 2014. This helpful analysis demonstrates that most young students live in sub wards with a participation

rate which is not very different from that of the ward. This is particularly the case with the most and least

advantaged Quintiles. Overall it is estimated that only 1 in 14 young students lives in a sub ward with a

participation rate markedly different from that of the ward.

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Indices of Multiple Deprivation (IMD)

This is an area based national measure of multiple deprivation which was introduced in 2000

and updated in 2007. Unlike POLAR3 which is a UK wide measure IMD relates only to

England. It charts multiple deprivation at the level of the lower super output area (LSOA)

which is smaller than a ward and contains an average of 1500 people and 650 households.11

It is based on a combination of seven domains capturing different aspects of disadvantage:

income deprivation;

employment (ie those excluded from work by unemployment, ill health, family

circumstances) ;

health and disability;

education, skills and training (this is divided into 2 sub-domains – lack of attainment

among children and young people and lack of skills qualifications among the adult

population);

barriers to housing and services;

living environment (based on quality of housing stock and environmental quality); and

crime.

Altogether there are 38 indices across the seven domains plus a further two supplementary

domains involving children (IDACI) and adults in relation to income deprivation.

While it has a correlation with POLAR3 IMD is not such an accurate measure of educational

disadvantage since it is based on a synthesis of measures rather than directly on progression

to HE and it identifies the nature and severity of deprivation in an area rather than numbers

of deprived people. It has a potential usefulness for targeting widening participation

students in higher Quintile POLAR3 wards by identifying pockets of material disadvantage

which could affect participation of some young students. However, because it addresses a

range of disadvantage IMD is a blunter instrument than IDACI.

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There are 32,844 LSOAs in England compared with 8,850 CAS wards.

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Income Deprivation affecting Children Index (IDACI)

This is one of the two supplementary measures within the Indices of Multiple Deprivation. It

is useful because it focuses on low income in relation to children. IDACI assigns scores to

LSOAs where children are living in poor households which are in receipt of benefits such as

income-based job seekers allowance or income support. The most deprived LSOA has the

highest score and a ranking of one. There is a strong correlation between IDACI scores (when

aggregated to ward level) and POLAR3 across the regions but there can be overlap in all

Quintiles. Some Quintile 5 wards, for example, have higher IDACI scores than in Quintile three

which would suggest that low income is not inevitably a determinant of low participation in

all cases. This is particularly so in London which, unlike the regions where the correlations are

more consistent, has high levels of income deprivation affecting children but also high levels

of participation.12

Since OFFA identifies individuals from lower socio-economic groups as widening participation

students IDACI can be used effectively with POLAR3 for targeting and for evaluation of

performance. Both indicators are concerned with disadvantage as it affects children. The

combination can help to confirm the coincidence of poor backgrounds and low participation,

and to identify economic disadvantage in more advantaged areas with the caveats that low

income may not inevitably be a deterrent to progression and that the combination will not

improve the identification of mature widening participation students.

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Further Information on POLAR3, p13.

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National Statistics Socio-Economic Classification

(NS-SEC) Four to Seven

This indicator is based on parental occupation and is used by HESA as an indicator for young

full time participation. It is based on seven categories of occupation, (an eighth category

covers unemployment):

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

8. Long term Unemployed/Never worked

NSSEC data can be related to areas by using information taken from the 2001 Census. This

enables a correlation between POLAR3 and the distribution of NSSEC categories. The

managerial and professional occupations are more prevalent in the more advantaged POLAR

Quintiles and in general these show that the proportion of children participating in HE rises in

NSSEC one to three households. The correlation between NSSEC information and POLAR3

holds across the regions, though London is somewhat out of kilter in that it has the highest

participation rate nationally despite having a proportion of NSSEC one to three households

only slightly above the national average.13 It is worth remembering that there will always be

families from NSSEC one to three in poor areas: Quintile one in the North East, the poorest

region for participation, has 20% of households in the NSSEC one to three category.

Although NSSEC has the benefit of relating to an individual’s status it is a difficult indicator to

use at the individual level as it is reliant on the way the question about parental occupation is

asked and answered. UCAS found that a high proportion of applicants returned “unknown” in

response to the question on parental occupation.14 Using NSSEC data in relation to the

Census information and in conjunction with POLAR3 can be helpful in targeting likely groups

but it is probably easier to establish whether an individual is from a low income background

by using Free School Meals as a proxy though this measure also has its problems.

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Further Information on POLAR3, p16.

14 Over 25% applicants returned “unknown” to the question on parental occupation in 2007, “Exploring the

KnownUnknowns: A Study of UCAS Data”, Sue Hatt and Neil Harrison, UWE Widening Participation Conference

paper, 2009.

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Free School Meals (FSM)

In general there is a correlation between the proportion of students claiming FSM and rates

of participation with 21% of all students claiming in Quintile one wards and 8% in Quintile five

wards. In all regions except London, a high number of claimants are associated with lower

participation rates. From 2012 this indicator was preferred by the Government as a proxy for

socio-economic disadvantage. However, criticism has been levelled at FSM because it would

appear to exclude some significantly deprived pupils and because over 300,000 of those

eligible in the UK did not claim.15 It also excludes mature students. However, for the purposes

of determining whether a student is in the widening participation category FSM is a reliable

indicator of low income and low potential for progression. If a student is not in receipt of FSM,

however, they are not necessarily excluded from widening participation status and First in

Family may be a useful alternative indicator.

First in Family

There is a close correlation between children having a graduate parent and young

participation rates which makes it a useful indicator for widening participation. The average

number of children with a graduate parent rises from 12% in Quintile one to 46% in Quintile

five. The lack of overlap at ward level between Quintiles would suggest that this measure

charts more accurately the areas of high and low participation than income based

measures.16 Used as an identifier for individuals it is, however, like all individual data, open to

possible misunderstanding or abuse.

15

“Take up of Free school Meals” ISER Working Paper, 2012; the BIS publication on Performance Indicators 2013

acknowledges that there may be pupils who qualify but do not claim which would affect the measure. 16

Further Information on POLAR3, HEFCE, 2014, p18 para 58.

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Using the Measures: Implications for Colleges

The OFFA report on Outcomes of Access Agreements, Widening Participation Strategic

Statement, and National Scholarship Programme Monitoring for 2012/1317 draws attention to

a range of measures which institutions develop for evaluation of the impact of their widening

participation activities. These include identifying schools with low GCSE performance,

collecting institutional data, using student tracking systems, commissioning research, and

canvassing feedback from a range of stakeholders. However, the key measure is the number

of widening participation students who are targeted and recruited and tracked through the

institution. All evaluation, and indeed, all management of the institutional widening

participation strategy, depends upon this. The choice of which measures to use therefore has

significant implications for colleges.

The HEFCE publication “HE Outreach: Targeting Disadvantaged Students”18 although written

in the days of Aimhigher has useful advice on targeting and evaluation. In targeting outreach

constituencies a proportion of around 65% of students engaged in pre-entry activities who

conform to widening participation criteria by area and economic status is acceptable. That

said it is important to use a basket of indicators in order to ensure that as far as possible

students are accurately assigned to the widening participation category. Which selection of

indicators is, of course, a matter for each institution and may well depend upon local

knowledge and institutional experience. Institutions in London may, for example, find that

socio-economic factors are not as significant as elsewhere since participation rates are

generally higher.

The most indispensable indicator has to be POLAR3. It has the key advantage of linking wards

to young participation (and to some extent to adult students) and so is superior to IMD. It

also demonstrates compatibility with a range of other key indicators and is used by HESA to

define LPNs. POLAR3 will indicate the catchment area of a school19 for targeting purposes

and will identify cohorts of Quintile one students who are defined by OFFA as belonging to

the widening participation target groups.

When it comes to individual students, however, whether attending outreach or entering the

institution, additional indicators need to be brought into play in order to define and evaluate

the college’s widening participation performance across the student lifecycle. At this point

when monitoring numbers of widening participation students recruited to the college it is

important to use a range of measures in order to establish individual levels of disadvantage.

17 OFFA, 2014. Outcomes of Access Agreements, Widening Participation Strategic Statement, and National

Scholarship Programme Monitoring for 2012/13, p26-7. 18

HEFCE, May 2007. 19

This can be refined through use of IMD and IDACI to locate schools in areas of high deprivation.

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Not all widening participation qualifiers live in POLAR3 Quintile one areas. A students living in

a POLAR3 Quintile two area but in a high scoring IDACI LSOA who is in receipt of free school

meals, has no HE heritage or is in NSSEC categories four - seven would certainly count as a

target student.

Reflective Questions

Measures and indicators often involve detailed work and so it is useful to step back from time

to time and ask some questions about their use in the context of institutional strategy. These

could include the following examples:

1. What indicators are we using and why? Are they the most effective indicators?

2. Do we have adequate access to information and resources for efficient data collection

and analysis?

3. Do we distinguish between indicators for targeting potential widening participation

cohorts and indicators for evaluating performance in terms of the recruitment and

progress of individual students?

4. Do we have more problems identifying particular groups of widening participation

students such as adults and/or part time? How do we tackle this?

5. Do we need to design any additional measures for evaluating particular activities

strategies, cohorts? For example, might it be useful to factor in predicted GCSE grades of

individual students?

6. Do we adequately factor widening participation statistics and their implications

regarding institutional performance into the institutional strategic plan?

7. What policies and strategic groups drive forward monitoring and evaluation of widening

participation within the institution, how are they reported and where is the

accountability located?