Progression to Higher Education: in the West

Progression to Higher Education: in the West Midlands:

Widening Participation

Trends in the participation of disadvantaged learners

2002

2003

2004

2005

2006

An Aimhigher Perspective Chris Brownless & Mike Thompson

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - CONTENTS

Contents section

page

section

page

Foreword

3

4.2 Age - Full-time Students

20

1.

4

4.3 West Midlands Region 22 - Ethnic Group Data within Full-time Students

Introduction: Regional Context

2. Measuring Progress: The Challenge

5

3. Modelling Disadvantage

6

4.3.1 Overall Ethnic Profile of Applicants & Acceptances

22 23

3.2 West Midlands Aimhigher Model 7

4.3.2 Growth in Applicants 2002-06 - Ethnic Groups

3.3 Characteristics of the Model

7

4.3.3 Ethnicity & Disadvantaged Groups 24

3.4 Regional Model & the Regional Profile of Disadvantage

8

4.3.4 Ethnicity & the Proportion of Applicants Accepted

25

3.5 Educational Background of WM

9

4.3.5 Ethnicity & Age Groups

26

4.3.6 West Midlands Region - Area Applicants & Acceptances

27

4.4 Disability - Full-time Students

28

3.1 The Index of Multiple Deprivation 6

4. West Midlands Aimhigher Analysis 10 4.1 Applications & Acceptances - Full-time Students

11

4.1.1 National & Regional Perspective

11

4.5 Gender - Full-time Students

30

4.1.2 Regional Analysis & Disadvantaged Communities

12

4.6 Part-time Students

32 32

4.1.3 Socio-economic Classification

14

4.6.1 Regional Profile of Part-time Students

4.1.4 Non-acceptances & Disadvantaged Communities

16

4.6.2 Regional Profile of Part-time Students & Disadvantage

34

4.1.5 Regional & Area Analysis

18

Next Steps

36

4.1.6 Destination of West Midlands Students

19

Glossary

38

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Foreword I am delighted to introduce this Aimhigher publication and hope that you will find it a significant and useful piece of work. Up to this point the data on widening participation in the West Midlands has been patchy. It has been difficult to understand how Aimhigher partnerships and other widening participation initiatives have been progressing.

This publication is both opportune and welcome as it brings together for the first time authoritative data on widening participation in the region and demonstrates that progression to HE amongst disadvantaged learners is improving steadily over time.

Aimhigher is tasked with raising participation rates to Higher Education for learners from the poorest communities.

This necessitates a robust means of identifying disadvantaged learners and their communities. Aimhigher West Midlands has worked hard for the last two years to establish a regional model which will achieve this and provide a framework within which Aimhigher evaluation can take place with a high degree of consistency.

It is, of course early days but we can see from the evidence positive movements in patterns of participation. For example, we can see that applications to HE from learners from the 40% most disadvantaged communities have increased over the last four years and are now in percentage terms outpacing applications from the most advantaged. We can also see that applications from disabled students are increasing. This is excellent news for a region where an under-confidence about progression to Higher Education has been entrenched in community cultures.

Inevitably there are areas which need more work – for example the progression of learners with vocational qualifications (who are more likely to come from disadvantaged backgrounds), and the related issue of the lower conversion of applications to acceptances amongst the target cohort. Most importantly, to understand our effectiveness we now need to ascertain how far Aimhigher activity is responsible for changing learner attitudes to HE by drawing on other forms of evidence to inform the statistical data .

This publication, however, has an importance beyond Aimhigher.

It offers information which will be helpful to widening participation practitioners across the educational sectors, to agencies and organisations working on the Regional Economic Strategy and regeneration initiatives, and to advice and guidance professionals.

And it gives all of us cause to be positive about the outcome of our collective work on widening participation. I, and all Aimhigher colleagues, are very grateful to Mike Thompson (area coordinator for Birmingham and Solihull and chair of the regional Aimhigher Evidence Group) and Chris Brownless (regional consultant on data) for undertaking the challenging work presented here.

“It is, of course, early days but we can see from this evidence positive movements in patterns of participation.�

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - INTRODUCTION

1. Introduction: Regional Context The West Midlands faces a challenge in terms of its economic performance and its social inclusivity agenda. The impending demographic decline, the low levels of skills in the current workforce and the increasing number of jobs involving higher level skills combine to present a bleak picture unless some way of unpicking the current patterns can be found.

The work done by the Regional Observatory on skills shows with great clarity how, and why, the region lags behind others. The region has a broader base of unqualified people in the workforce than most other regions and a sharp taper in those who have higher level qualifications.

At the same time while there are distinct improvements in attainment at levels 2 and 3 these do not substantively reduce the gap between the West Midlands and the national average. Moreover the poor A level performance in the region also raises some concerns.

In terms of higher level qualifications the West Midlands performs poorly. In 2005 14.8% of its working population were educated to graduate level while the national average was 17.9%. Of the 190,000 students registered in West Midlands HEIs in 2005/6 (excluding the OU) 47% came from the region, and of those West Midlands domiciled students completing in 2005 58% found employment locally. From the perspective of developing a skilled workforce it is clear that more West Midlands learners need to enter HE and more need to be retained in the region to supply the needs of new high value industries.

However, the Aimhigher data shows that the participation rate amongst the most advantaged groups, the traditional entrants to HE, has flattened or fallen over the last few years. This would suggest that we may have reached saturation point with these groups and that the larger capacity for increased participation lies with the disadvantaged groups National Statistics Socio-economic Classification (NS SEC) 4-8 who are now beginning to aspire to HE. It is these groups whom for economic and social reasons we need to engage. These are learners who whether young full time or mature part time participants are more likely to study locally and to bring their graduate skills to the region’s labour market. These are learners from the most disadvantaged communities who can help transform local cultures and create virtuous circles.

“More West Midlands learners need to enter HE.�

The work of the Observatory shows that people with lower or no qualifications are more prevalent in the West Midlands urban areas and amongst disadvantaged groups. However, we should not forget the rurally isolated learner in the Marches who finds few educational and guidance opportunities within a convenient distance of home. A priority for the region, which is central to the regional economic and skills strategies has to be the engagement of young learners from a variety of disadvantaged backgrounds and the re-engagement of more mature learners. This will achieve a more equitable participation in higher education across all socioeconomic groups while at the same time helping the region to meet its future employment profile.

The task is considerable because of the correlation of low aspiration and poor attainment with disadvantage.

However, while numbers are still slight in terms of participation because the base line is so low, the data suggest that learners from disadvantaged backgrounds are beginning to see Higher Education as an opportunity for them.

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2. Measuring Progress: The Challenge Efforts to widen participation in higher education have many stakeholders, all requiring evidence of changes in the volume and nature of entrants to higher education in order to plan, monitor and evaluate the activities they variously fund, engage with or deliver.

The primary objective for Aimhigher is to support progress against the Public Sector Agreement target of 50% participation in higher education amongst 17 to 30 year olds by 2010, by raising the aspirations of people from under-represented communities and supporting their attainment and subsequent progression. The mechanism by which progress against this target is assessed is the Higher Education Initial Participation rate (HEIPR). This measure was introduced in 1999 / 2000, and, following several revisions, now incorporates all the statistically significant forms of higher education that England domiciled people aged 17 – 30 might participate in. However, the HEIPR is a national measure, and does not currently allow any interrogation of participation at regional or sub-regional levels, or by gender, ethnicity, disability or social class. It does not provide local and regional Aimhigher partnerships with the evidence they require to demonstrate progress towards the target they have been established to meet.

There are numerous other national datasets that seek to measure participation in higher education. Each provides valuable insights, but each has its limitations as a tool for measuring the impact of Aimhigher on the ground.

Some data explore participation in full-time higher education but do not capture the significant and growing cohort of part-time learners, who comprise over 40% of all higher education students. Some focus on youth participation, and thus do not reflect mature entrants.

Some are produced annually, enabling trends over time to be monitored, whilst others have been produced for specific year cohorts, and provide a more detailed snapshot of participation that subsequently becomes historic. Most are national in their scope, with few offering insights into patterns of participation at local or regional levels. Many measure the volumes of learners applying to, being accepted and entering higher education, some the proportionate participation of a defined population.

The criteria by which the various data seek to measure changes in the numbers and proportions of disadvantaged learners entering higher education also vary. For example, Universities and Colleges Admission Service (UCAS) seek to capture the socio-economic group of full-time applicants using the NS-SEC classification of occupations. This is perhaps the most widely cited evidence of the extent to which participation is or is not widening, but must be viewed with some caution, as over 25% of all applicants do not provide a response. Moreover, there is evidence to suggest that the socio-economic characteristics of this significant cohort of “unknowns� may skew any conclusions drawn from the 75% who do respond. (see pages 14 to 17 for a full exploration of this aspect of UCAS data).

Given this abundance of partial or highly aggregated data Aimhigher and its precursor initiatives have faced the challenge of producing evidence of widened participation at a regional and local level. In response Aimhigher West Midlands have developed a Regional Evidence Model with the active support of the six area partnerships.

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - MODELLING DISADVANTAGE

3. Modelling Disadvantage Given the difficulties and limitations of available data it is necessary to consider what other measures of disadvantage or deprivation are available.

One that offers new insights is the Index of Multiple Deprivation (IMD), introduced alongside the 2001 census by the Office of the Deputy Prime Minister. It allows the degree of deprivation of very small communities to be identified, which can then be related to UCAS, Higher Education Statistics Agency (HESA) and other data. It is this measure that is used as the basis of the West Midlands Aimhigher Regional Model.

3.1 The Index of Multiple Deprivation

The Index of Multiple Deprivation provides an overall indication of deprivation that is based on seven domains reflecting various dimensions of deprivation. These are weighted, as indicated in the table below, with Income and Employment deprivation being the two largest components. The index provides a measure of deprivation of very small communities called Super Output Areas (SOAs). These can be ranked so that the most deprived communities can be identified. SOAs are smaller than wards and have a typical population of 1,500 with a minimum of 1,000.

The index is well recognised and increasingly used to inform public spending and policy development.

The Index of Multiple Deprivation

All IMD domains

West Midlands Aimhigher Model

Domain Weight

Weighted average of selected domains

Domain Weight

Income deprivation

30%

13.5%

Education skills & training deprivation

60%

Barriers to housing & services

9.3%

Barriers to housing & services

10%

Crime

9.3%

Living Environment deprivation

9.3%

Income deprivation

22.5%

Employment deprivation

22.5%

Health deprivation & Disability

13.5%

Education skills & training deprivation

The charts in this section are derived from data from the Office of National Statistics (ONS), [http://neighbourhood.statistics.gov.uk/dissemination/] as well as commissioned data from UCAS. The data is analysed using the West Midlands Aimhigher Model. Information on the Index of Multiple Deprivation can be found on the Communities and Local Government website [http://www.communities.gov.uk/publications/communities/englishindices] from where the data can be downloaded.

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3.2 West Midlands Aimhigher Model

The West Midlands Aimhigher Model uses the IMD as a means of identifying educationally deprived communities at SOA level. A subset of the IMD domains is used and weighted to reflect what are believed to be the most important factors from the IMD to affect opportunities in education and progression to HE. This approach is a better discriminator of Socio-economic Classification (SEC), as well as a whole range of education indicators, than using all domains. The three domains and their weighting are shown on the right of the diagram on page 6. Deprivation is ranked for all West Midlands SOAs and then calibrated in a variety of ways. The main approach in the analysis that follows is based on quintiles where Q1 is the most disadvantaged or deprived and Q5 the least. The Higher Education Funding Council for England (HEFCE) have recently suggested identifying disadvantaged communities as those that are found in the 13,000 most deprived SOAs in England. This corresponds to the 40% most deprived communities or Q1 and Q2 on a quintile scale.

Disadvantage

more Quintiles

Q1

Q2

HEFCE

Q3

less Q4

Disadvantaged

Q5

Advantaged

3.3 Characteristics of the Model

It is important to test whether the model reflects other indicators of disadvantage. The charts below show that the qualifications and socio-economic group profiles are highly correlated with the quintiles of deprivation identified by the model. Only 1.5% of 16 to 74 year olds are in the Higher Professional classification in the most deprived quintile in contrast to the least deprived, where the proportion is nearly five time greater. Half of the communities in the most deprived/disadvantaged quintile (Q1) have no qualifications whereas only one in five of the most advantaged quintiles (Q5) lack qualifications and less than one in ten persons in Q1 have level 4/5 qualifications compared with Q5 where more than one quarter have these higher qualifications.

Socio-economic Group % of 16-17 year olds in each classification

20

Qualifications Profile % of 16-17 year olds in each classification

Higher Professional Routine

50

No Qualifications Level 4/5

40

15

30 10 20 5

0

10

Q1

Q2

Q3

Q4

Q5

0

Q1

Q2

Q3

Q4

Q5

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - MODELLING DISADVANTAGE

3.4 Regional Model & the Regional Profile of Disadvantage

The Model’s distribution of SOAs across the West Midland’s Areas is shown in the table below. Birmingham and Solihull is the largest area with 22% of the SOAs and Shropshire, Telford and Wrekin the smallest with 9%. There is a marked difference between the areas in the distribution of disadvantaged SOAs. Only one fifth of Herefordshire and Worcestershire’s SOAs are in the two most disadvantaged quintiles (Q1 and Q2) whereas the Black Country has nearly three times that proportion with 59% in Q1 and Q2.

Percentage of an Area’s SOAs in 2 most Disadvantaged Quintiles (Q1 & Q2)

Area Distribution of SOAs

800

40

700

35

600

30

500

25

400

20

300

15

200

10

100

5

0

B&S

BC

STAFFS COV & W H & W

0

STW

The distribution of SOAs by quintiles of deprivation shown in the chart to the right is the result of using all of the IMD domains and an all-England ranking of deprivation, that is the SOAs in Q1 are the SOAs that are in the fifth most deprived communities across the country. As the West Midlands is relatively deprived compared with England as a whole there are more SOAs in Q1 using this approach, 26%, compared with the 20% of the WM AH Model and less in the least deprived 15% in Q5 instead of 20%.

Q1 Q2

B&S

BC

STAFFS COV & W H & W

STW

Comparison of % Distribution of West Midlands SOAs using England Ranking (All Domains) & Model

30 25 20 15 10 5 0

Q1

Q2

Q3

Q4

Q5

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3.5 Educational Background of West Midlands

GCSE performance is highly correlated with disadvantage. The chart below shows that in 2002/3 the most disadvantaged quintile had less than a third of 15 year olds achieving 5+ passes at grades A*-C whereas 70% of Q5 achieved this level of passes. Also the chart shows that there has been a marked improvement by the most disadvantaged between 2002 and 2005 and the chart on the right shows that the average point score for GCSE and equivalent has increased most in the most disadvantaged quintile.

Average Point Score GCSE & Equivalent % Change 2003/4 to 2004/5

GCSE % of 15 year olds achieving 5+ A*-C 80

8

2002/3

70

2003/4

7

60

2004/5

6

50

5

40

4

30

3

20

2

10

1

0

Q1

Q2

Q3

Q4

0

Q5

Q1

The Model can be used with UCAS data on tariff points to examine the difference between quintiles of disadvantage. The chart to the right shows the distributional difference between quintiles Q1 and Q5. The most advantaged has larger proportions with higher points.

Q3

Q4

Q5

UCAS Applicants % Tariff Distribution Quintiles 1 & 5, 2006

Q2

20

Q1 Q5

15

10

The distribution for both quintiles Q1 and Q5 for 2002/3 and 2006/7 is shown below. In the case of both quintiles there has been a slight shift to the right over these years. This is slightly greater with the most disadvantaged quintile, though its mode is associated with a lower tariff score.

West Midlands UCAS Acceptances: % Distribution of A level points of most Disadvantaged Quintile (Q1)

25

2002

5

0

00

9 9 -419 9 9 40 179 -239 0240-299 -79 8080-119 5540 -119 20120-179 11-79 -47 -53 -35 60360-419 420-479 480-539 -29 00300-359 1 - 180180-239 3 420 480 3 24

West Midlands UCAS Acceptances: % Distribution of A level points of least Disadvantaged Quintile (Q5)

20

2002 2006

2006

20

15

15 10 10 5

5 0

00

79 080-119 40 119 -179 0-180-239 239 0-240-299 479 0-480-539 5540 539 359 60360-419 299 0-300-359 1-1-79 -419 20-420-479 8 - 120120-179 18 3 4 30 24 48

0

00

9 -419 9 9 179 -239 0240-299 -79 8080-119 540 539 -119 20120-179 11-79 -47 80-480-539 -35 60360-419 -29 00300-359 540 1 - 180180-239 3 420 420-479 3 24 4

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4. West Midlands Aimhigher Analysis The analysis in the following pages is mainly derived from data commissioned from UCAS and HESA. In combination with the West Midlands Aimhigher Model it produces a clear and largely encouraging picture concerning access to higher education from disadvantaged communities. Whilst the pattern of applications and acceptances has been affected by the new system of student finance (causing an acceleration in applications in 2005 and a consequential decline in 2006) the overriding feature of the analysis is the impact and influence of the disadvantage or deprivation of the community in which the students are domiciled.

The more disadvantaged the community the less likely it is that young people will enter higher education. The encouraging feature of this analysis is that this inequality is starting to be addressed.

Over the last five years the more disadvantaged communities have produced the largest increases in applications and acceptances. This favourable pattern is also found in applications and acceptances from those with disabilities and most minority ethnic groups (particularly from Black families).

The differences between areas within the WM Region would seem to be largely due to the distribution of disadvantaged communities. The degree of disadvantage is a major influence on where a student studies – the more disadvantaged the community the more likely it is the student will study in the West Midlands rather than study in other regions.

There is still a long way to go to produce greater equality of access to higher education. Disturbingly there is a correlation between lower acceptance rates (the proportion of applicants who are accepted) and disadvantage. However, the overall conclusion from this analysis is that inequality is being reduced and that the evidence is consistent with the activities of Aimhigher being effective as well as some early indications that the new system of student finance is not discouraging people from lower income backgrounds from applying to higher education.

“Over the last five years the more disadvantaged communities have produced the largest increases in applications and acceptances.�

The charts and tables in sections 4.1 to 4.5 refer to full-time students and are derived from data commissioned from UCAS and analysed using the West Midlands Aimhigher Model.

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4.1 Applications & Acceptances - Full-time Students 4.1.1 National & Regional Perspective

There has been an overall increase in applicants of 7% in the West Midlands in the period 2002-2006, a little lower than the national average of 8%. The pattern of growth of applicants has been affected by the changes in student financing with a spike in applications in 2005 followed by a subsequent fall in 2006/07 when the new system of fees was introduced.

UCAS Applicants England & West Midlands

120

UCAS Accepted Applicants England & West Midlands

120

West midlands

West midlands

England

England 115

110

110

105

105

2002=100

2002=100

115

100

2002

2003

2004

2005

2006

100

2002

2003

2004

2005

2006

The acceptances follow a similar pattern though there are lower rates of increase compared with the growth of applicants. As with applicants the West Midlands has grown slightly less than England, growing by 4% over the five year period 2002-05 compared with the national figure of 5%.

Region

2002

2003

2004

2005

2006

Applicants

Region

2002

2003

2004

2005

2006

WM

100

101

101

107

104

England

100

102

103

110

106

Acceptances

WM

100

102

103

109

107

England

100

102

102

111

108

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.1.2 Regional Analysis & Disadvantaged Communities

Using the WM Aimhigher Regional Model the pattern of growth across communities of varying disadvantage or deprivation can be examined.

The more advantaged communities still dominate applications. In 2002 over half (53%) the applicants came from the two most advantaged quintiles, and these groups still account for half of the applicants in 2006. The pie charts show the uneven distribution but indicate that the inequality is being reduced.

These differences are not the result of different population bases. Indeed the 2001 census data indicates that the most disadvantaged quintile, Q1, has the largest number of young people of all the quintiles hence the picture conveys an impression that underestimates the inequality of access to HE.

Distribution of Applicants by Disadvantaged Communities in 2002

Distribution of Applicants by Disadvantaged Communities in 2006

Q1 13%

Q5 31%

Q1 15%

Q5 28% Q2 16%

Q2 17%

Q3 18%

Q4 22%

Q4 22%

Q3 18%

Looking at the five year period, 2002-06 there is a clear correlation between disadvantage and growth of applicants - the more disadvantaged the community the higher the rate of growth. There was a 23% growth of applicants from the most disadvantaged quintile compared with only a 1% growth in applicants from the least disadvantaged quintile. The year by year pattern shows that there was a continued growth in 2006 by the two most disadvantaged quintiles whereas the less disadvantaged quintiles followed the national pattern of decline. The often expressed fear that the most disadvantaged groups would be particularly adversely affected by the new student financing arrangements is contradicted by these findings. Indeed the findings are consistent with the view that new arrangements, which give additional support to those from low income families, along with Aimhigher initiatives are encouraging applications from disadvantaged communities.

West Midlands UCAS Applications 2002-2006 % change

West Midlands UCAS Applications 2002-06

25

130

20

120

Q1

Q4

Q2

Q5

Q3

Total

15 110 10 100

0

2002=100

5

Q1

Q2

Q3

Q4

Q5

WM Total

90

2002

2003

2004

2005

2006

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West Midlands UCAS Applications 2002-2006 Quintiles

2002

2003

2004

2005

2006

2006/02 Nos.

%

Q1

4,481

4,643

4,836

5,371

5,518

1,037

23%

Q2

5,296

5,344

5,430

5,895

5,991

,695

13%

Q3

6,180

6,255

6,252

6,579

6,458

,278

4%

Q4

7,551

7,802

7,811

8,266

7,797

,246

3%

Q5

10,072

10,217

10,155

10,564

10,166

,094

1%

WM Total

33,999

34,655

34,889

37,062

36,306

2,307

7%

Acceptances follow a similar pattern to that seen with applicants. The overall increase from 2002 to 2006 was 4%, three percentage points lower than the growth of applications.

As with applications the largest increase (19%) was by the most disadvantaged quintile and unlike the three least disadvantaged quintiles there was no decline in 2006.

West Midlands UCAS Acceptances 2002-2006

West Midlands UCAS Acceptances 2002-2006

20

2006/02

120

15

110

10 100

5 Q4

Q2

Q5

Q3

Total

2005

2006

2002=100

-5

Q1

90

0

Q1

Q2

Q3

Q4

Q5

WM Total

80

2002

2003

2004

West Midlands UCAS Acceptances Quintiles Q1

2002 3,492

2003 3,649

2004 3,667

2005 4,029

2006

2006/02

2006/02

Nos.

%

4,156

,664

19%

Q2

4,306

4,310

4,297

4,718

4,734

,428

10%

Q3

5,140

5,240

5,149

5,443

5,292

,152

3%

Q4

6,442

6,588

6,564

6,980

6,462

,020

0%

Q5

8,812

8,806

8,786

9,202

8,660

-,152

-2%

28,548

28,923

28,789

30,689

29,614

1,066

4%

WM Total

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.1.3 Socio-economic Classification

A useful insight into the progress of under-represented groups ought to arise from the data on socio-economic classification collected by UCAS. Unfortunately this is not the case because the question on SEC allows a voluntary response and as a consequence the category ‘unknown’ generates the largest single response. The value of the other responses is reduced further because the ‘unknown’ category has grown by nearly 50% over the last 5 years.

West Midlands UCAS Applicants 2002

2003

2004

2005

2006

2006/02 Nos.

5,523

5,398

5,393

5,304

5,208

-,315

-6%

2 Lower managerial and professional occupations

8,138

8,496

8,509

8,675

8,071

,-67

-1%

3 Intermediate occupations

3,766

3,648

3,741

3,784

3,443

-,323

-9%

4 Small employers and own account workers

1,949

1,945

1,891

2,005

1,889

,-60

-3%

5 Lower supervisory and technical occupations

1,401

1,484

1,491

1,383

1,384

,-17

-1%

6 Semi-routine occupations

4,153

4,161

4,312

4,523

4,251

,098

2%

7 Routine occupations

2,313

2,180

2,151

2,274

2,138

-,175

-8%

8 Unknown

6,756

7,343

7,401

9,114

9,922

3,166

47%

33,999

34,655

34,889

37,062

36,306

2,307

7%

2002

2003

2004

2005

2006

West Midlands UCAS Acceptances 2006/02 Nos.

2006/02 %

1 Higher managerial and professional occupations

4,833

4,719

4,678

4,600

4,496

-,337

-7%

2 Lower managerial and professional occupations

6,948

7,177

7,207

7,387

6,770

-,178

-3%

3 Intermediate occupations

3,162

3,062

3,118

3,100

2,821

-,341

-11%

4 Small employers and own account workers

1,661

1,638

1,560

1,669

1,556

-,105

-6%

5 Lower supervisory and technical occupations

1,182

1,245

1,236

1,181

1,139

,-43

-4%

6 Semi-routine occupations

3,451

3,380

3,472

3,566

3,362

,-89

-3%

7 Routine occupations

1,886

1,798

1,748

1,866

1,756

-,130

-7%

8 Unknown

5,425

5,904

5,770

7,320

7,714

2,289

42%

28,548

28,923

28,789

30,689

29,614

1,066

4%

WM Total

%

1 Higher managerial and professional occupations

WM Total

2006/02

The West Midlands Aimhigher Model can be used to examine the distribution of disadvantage across the ‘unknown’ SEC category. The most disadvantaged quintile accounts for nearly a quarter of all in the ‘unknown’ SEC. The chart and the table on page 15 compare the distribution of applicants and ‘unknown’ SEC by quintiles of disadvantage in 2006. Whilst Q1 account for 15% of applicants it is responsible for 24% on those in the ‘unknown’ category, whereas Q5 accounts for 28% of the applicants but only 19% of those in the ‘unknown’ category.

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UCAS Applicants & Unknown SEC 2006 Distribution by Quintiles of Disadvantage 30

Applicants Unknown SEC

25 20 15 10 5 0

Q1

Q2

Q3

Q4

Q5

This variation across quintiles of disadvantage means that there is a large variation in the proportion of applicants that are of unknown SEC across disadvantaged groups. The chart below shows the SEC of 43% of the most disadvantaged quintile (Q1) is unknown in comparison to 19% of the most advantaged quintile (Q5).

Unknown SEC as % of Applicants 2006 Quintiles of Disadvantage 50

40 30 20 10 0

Q1

Q2

Q3

Q4

Q5

West Midlands UCAS Applicants Unknown SEC as % of Applicants Quintiles

2002

2003

2004

2005

2006

Q1

36%

38%

38%

41%

43%

Q2

26%

28%

29%

30%

34%

Q3

20%

21%

20%

23%

26%

Q4

16%

17%

16%

20%

22%

Q5

12%

14%

14%

18%

19%

WM Total

20%

21%

21%

25%

27%

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.1.4 Non-acceptances & Disadvantaged Communities

The proportion of applicants accepted for HE courses has declined slightly over the last five years from 84% to 82%. There is a marked correlation between the acceptance rate and the degree of disadvantage. The most disadvantaged communities (Q1) has an acceptance rate of 75% in 2006 compared with 85% for the most advantaged group (Q5). This warrants further exploration. One of the challenges of widening participation is to raise aspirations and encourage underrepresented groups to apply for HE. Here there is evidence of cases where this has been achieved but is not then converted into acceptances and places in HE.

Acceptances as % of Applicants 2006 (All ages)

West Midlands Acceptance Rate

85

Quintiles

2002 2003 2004 2005 2006

80

Q1

78%

79%

76%

75%

75%

75

Q2

81%

81%

79%

80%

79%

Q3

83%

84%

82%

83%

82%

Q4

85%

84%

84%

84%

83%

Q5

87%

86%

87%

87%

85%

WM Total

84%

83%

83%

83%

82%

70

0

Q1

Q2

Q3

Q4

Q5

A closer examination of 18 year old applicants shows the same pattern- 21% of the most disadvantaged quintile are not accepted compared with 12% of the most advantage quintile.

Non-acceptance Rate 2006 (18 year olds)

25 20 15 10 5 0

Q1

Q2

Q3

Q4

Q5

Total

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For A level applicants there is a difference in the tariff point distribution of the two quintiles Q1 and Q5 with the latter having more applicants in the higher point categories. This may well account for much of the lower acceptance rate for applicants from the most disadvantaged communities when places are rationed on the basis of tariff scores. The graph below shows how the non-acceptance rate for quintiles Q1 and Q5 varies with point score. Not surprisingly the rate declines as point score rises. Both quintiles follow a very similar pattern though for all the categories, except one, the most disadvantaged quintile has the higher non-acceptance rate.

Non-acceptances as % of Applicants (18yo) compared with A-level Points 80

Q1

70

The non-acceptance rate for the most disadvantaged is higher (29% for Q1) than for the most advantaged (23% for Q5)

Non-acceptance rate for BTEC Lower Applicants (18yo) 2006

Q5

30

60 50

25

40

20

30 20

15

10

10

0

0

0

79 0-80-119 40 119 0-120-179 179 0-180-239 419 0-420-479 239 0-240-299 479 0-480-539 5540 359 60-360-419 539 299 0-300-359 1-1-79 8 12 18 3 42 30 24 48

There are some disturbing aspects to the data for disadvantaged communities following a BTEC Lower route to HE. The non-acceptance rate for this route is higher at 22% for all applicants compared with 14% for all routes for 18 year olds. It is a route that is more favoured by the most disadvantaged applicants. BTEC applicants account for 14% of all applicants from the most disadvantaged quintile, Q1, compared with only 6% of the most advantaged, Q5.

BTEC Lower Applicants as % of Total Applicants (18yo) 2006

15

5 0

Q1

Q2

Q3

Q4

Q5

All

For the most disadvantaged quintile the combination of the popularity of the BTEC route and the higher non-acceptance rates associated with it and this quintile means nearly 1 in 5 of non-acceptances (19%) for the most disadvantaged is accounted for by the BTEC route compared with 12% for the most advantaged.

BTEC Lower Non-acceptances as % of all Non-acceptances (18yo) 2006

20

12

15

9 10 6 5

3 0

Q1

Q2

Q3

Q4

Q5

All

0

Q1

Q2

Q3

Q4

Q5

All

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.1.5 Regional & Area Analysis

West Midlands UCAS Applications % Change 2002-06 20

The analysis of applicants and acceptances over the last five years in the West Midlands Aimhigher areas shows considerable variation.

The following chart and tables show the five year change in applicants and the changes vary from a 16 % rise in applicants in the Birmingham and Solihull area to a 2% fall in Shropshire and Telford and Wrekin.

15 10 5

0 -5

West Midlands UCAS Applicants 2002-06 Areas

2002

2003

B&S

BC

2004

COV & W STAFFS & SoT H & W

2005

2006

STW

2006/02 Nos.

2006/02 %

B&S

8,263

8,690

8,884

9,506

9,577

1,314

16%

BC

6,060

6,021

6,216

6,455

6,478

,418

7%

COV & W

5,341

5,471

5,581

5,882

5,597

,256

5%

H&W

4,839

4,890

4,902

5,190

4,935

,096

2%

STAFFS & SoT

6,265

6,299

6,207

6,735

6,574

,309

5%

STW

2,812

2,890

2,694

2,907

2,769

,-43

-2%

33,999

34,655

34,889

37,062

36,306

2,307

7%

WM Total

WM

West Midlands UCAS Acceptances % Change 2002-06 12

A similar pattern for growth rates is found with acceptances, as the chart to the right and the table below illustrate.

10 8 6 4 2 0 -2 -4 -6

West Midlands UCAS Acceptances 2002-06 Areas

2002

2003

B&S

BC

2004

COV & W STAFFS & SoT H & W

2005

2006

STW

WM

2006/02 Nos.

2006/02 %

B&S

6,787

7,080

7,154

7,609

7,531

,744

11%

BC

5,010

4,963

5,094

5,308

5,254

,244

5%

COV & W

4,487

4,560

4,682

4,894

4,655

,168

4%

H&W

4,089

4,191

4,113

4,427

4,073

,0-16

0%

STAFFS

5,419

5,384

5,137

5,678

5,529

,110

2%

STW

2,400

2,415

2,283

2,456

2,262

-,138

-6%

28,548

28,923

28,789

30,689

29,614

1,066

4%

WM Total

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Growth in Acceptances 2002-06 & % of SOAs in most Disadvantaged Quintile

12

Acceptances

10

% of LSOAs in Q1

8 6 4 2 0 -2 -4 -6

B&S

BC

COV & W

STAFFS

H&W

STW

The variations in growth of acceptances of different areas is highly correlated with the distribution of disadvantaged communities - the higher the proportion of the most disadvantaged communities the higher the growth in acceptances. The chart on the left shows the growth in acceptances for each of the areas and the percentage of the most disadvantaged quintile of SOAs that are found in each of the West Midlands areas. Section 1.2 showed that the more disadvantaged the quintile the higher the growth in applicants and acceptances and given the differences in the distribution of disadvantaged communities between Aimhigher areas, this explains much of the variation in growth of applicants and acceptances between areas.

WM

4.1.7 Destination of West Midland students

There has been a growing tendency for HE students to study near their homes. In 2006 half of WM domiciled students began HE courses in the West Midlands region – an increase of 3 percentage points since 2002.

There is a very marked difference between communities depending on the degree of disadvantage. Three quarters of the most disadvantaged quintile (Q1) study in the West Midlands whereas one third of the most advantaged quintile study in their own region.

Quintiles Of Disadvantage, % of West Midlands Domicles Entering HE in the West Midlands 80

Quintiles Of Disadvantage, % of West Midlands Domicles Entering HE in the West Midlands Quintiles

2002

2003

2004

2005

2006

70

Q1

74%

75%

74%

73%

75%

60

Q2

62%

62%

64%

62%

66%

Q3

50%

50%

53%

51%

53%

50

Q4

41%

42%

40%

41%

42%

40

Q5

33%

33%

34%

33%

34%

30

WM Total

47%

47%

48%

48%

50%

20 10 0

Q1

Q2

Q3

Q4

Q5

Total

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.2 Age - Full-time Students

120

People under 30 years old account for well over 90% of applicants and acceptances. Seventy percent of the applicants are under 20 years old. In the last five years the largest growth rate in applicants was from those over 30 years of age (see the following chart and table).

West Midlands UCAS Applications 2002-06 Age Groups Under 20 20-29 Over 30

115

110

2002=100

105

100

2004

2005

2006

West Midlands UCAS Acceptances 2002-06 Age Groups Age Under 18 18 19 20 21 22 23 24 25-29 30-39 40 and over Under 20 20-29 over 30 WM Total

2002

2003

2004

2005

2006

2006 % of Total

2006/02 Nos.

2006/02 % -29%

,084

,097

,063

,070

,060

0%

,-24

16,967

17,365

17,100

18,450

18,109

50%

1,142

7%

7,366

7,397

7,757

7,711

7,366

20%

-

0%

2,616

2,656

2,550

2,883

2,731

8%

,115

4%

1,410

1,445

1,490

1,462

1,597

4%

,187

13%

1,019

,934

,966

1,049

1,022

3%

,013

0%

,665

,713

,651

,752

,722

2%

,057

9%

,418

,473

,548

,565

,575

2%

,157

38%

1,293

1,391

1,496

1,648

1,649

5%

,356

28%

1,546

1,524

1,591

1,682

1,621

4%

,075

5%

,615

,660

,677

,790

,854

2%

,239

39%

24,417

24,859

24,920

26,231

25,535

70%

1,118

5%

7,421

7,612

7,701

8,359

8,296

23%

,875

12%

2,161

2,184

2,268

2,472

2,475

7%

,314

15%

33,999

34,655

34,889

37,062

36,306

100%

2,307

7%

2003

2002

The increase in applicants of those over 30 years old has not been converted into acceptances as the following chart and tables show.

West Midlands UCAS Acceptances 2002-06 Age Groups

120

Under 20 20-29 Over 30

115

100

2002=100

105

80

2002

2003

2004

2005

2006

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West Midlands UCAS Acceptances 2002-06 Age Groups Age Under 18 18 19 20 21 22 23 24 25-29 30-39 40 and over Under 20 20-29 over 30 WM Total

2002

2003

2004

2005

2006

2006 % of Total

2006/02 Nos.

2006/02 % -36%

,072

,084

,046

,055

,046

0%

,- 26

14,715

14,976

14,819

16,160

15,521

52%

,806

5%

6,298

6,381

6,572

6,616

6,243

21%

,- 55

-1%

2,169

2,199

2,062

2,332

2,200

7%

,031

1%

1,135

1,111

1,120

1,126

1,222

4%

,087

8%

,799

,705

,,696

,741

,728

2%

,- 71

-9%

,498

,528

,454

,536

,487

2%

,- 11

-2%

,308

,352

,389

,,362

,391

1%

,083

27% 22%

,919

,,991

1,041

1,080

1,118

4%

,199

1,162

1,085

1,112

1,131

1,068

4%

,- 94

-8%

,473

,511

,478

,550

,590

2%

,117

25%

21,085

21,441

21,437

22,831

21,810

74%

,725

3%

5,828

5,886

5,762

6,177

6,146

21%

,318

5%

1,635

1,596

1,590

1,681

1,658

6%

,023

1%

28,548

28,923

28,789

30,689

29,614

100%

1,066

4%

The table below shows the growth rates in applicants for the period 2002-06 for different age groups and quintiles of disadvantage. There is a tendency for the most disadvantaged groups to apply at an older age than the most advantaged group (see the chart below, which is colour-coded to reflect these trends).

Growth in Applicants 2002-2006 by Age & Quintile of Disadvantage Age ALL AGES 18 19 20 21 22 23 24 25-29 30-39 40 and over

Applicants 2006 - Age Distribution

Q1

Q2

Q3

Q4

Q5

19%

10%

3%

0%

-2%

12%

7%

5%

5%

4%

21%

14%

-1%

-7%

-12%

30%

11%

0%

-6%

-13%

35%

17%

4%

-11%

3%

0%

-14%

-8%

-8%

-7%

21%

-3%

44%

-28%

-20%

22%

50%

29%

22%

16%

39%

47%

12%

18%

-2%

12%

-5%

-15%

-8%

-22%

22%

39%

33%

38%

-3%

80

Q1

70

Q5

60 50 40 30 20 10 0

18

19

20

21

22

23

24

25-29 30-39 40+

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.3 West Midlands Region - Ethnic Group Data within Full-time Students 4.3.1 Overall Ethnic Profile of Applicants & Acceptances

The pie charts and tables below show the distribution across the main ethnic groups of UCAS applicants and acceptances. White applicants dominate with 70% of all applicants and acceptances. The next largest group is Asians with 16% followed by Black applicants with 5% of the applicants (and 4% of the acceptances) in 2006. Black applicants have grown more rapidly than other groups over the last five years (see next section) and now account for 5% of all applications in 2006 compared with 3% in 2002. It is not easy to calculate the progression rates for different groups because there are no up-to-date figures for population size of the relevant age groups, but comparison with 2004 KS2 figures for the distribution of young people across ethnic groups suggest that Whites and to a lesser extent Mixed Race are ‘underrepresented’ in the UCAS figures whereas Asians and to a lesser extent Blacks are ‘over-represented’.

West MIdlands UCAS Applicants 2006

West Midlands UCAS Acceptances 2006

Asian 16%

No Data 5%

Asian 15%

No Data 5%

Black 5%

Black 5% Mixed Race 5%

Mixed Race 5%

Other 1%

White 70%

Other 1%

White 70%

West Midlands UCAS Applicants % by Ethnic Group

West Midlands UCAS Acceptances % by Ethnic Group

Ethnic group

2002

2003

2004

2005

2006

Ethnic group

2002

2003

2004

2005

2006

Asian

16%

16%

16%

16%

16%

Asian

16%

16%

16%

16%

16%

Black

3%

3%

4%

5%

5%

Black

3%

3%

4%

4%

4%

Mixed Race

2%

2%

2%

3%

3%

Mixed Race

2%

2%

2%

2%

3%

Other

0%

0%

0%

1%

1%

Other

0%

0%

0%

1%

1%

White

71%

70%

70%

70%

70%

White

71%

71%

71%

72%

70%

No Data

8%

8%

7%

5%

5%

No Data

8%

7%

6%

5%

6%

100%

100%

100%

100%

100%

100%

100%

100%

100%

100%

WM Total

WM Total

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4.3.2 Growth in Applicants 2002-06 - Ethnic Groups

The largest increases in applicants in the period 2002-06 were from the Black (79%) and Mixed Race (71%) ethnic groups. White and Asian applicants grew by 6% over the period, close to the regional average of 7%. The year-by-year pattern for Asian applicants was almost identical to that of White applicants with both groups showing a sharp increase in 2005 followed by a decline in 2006. In contrast, both Black and Mixed Race applicants increased in each year with double-digit percentage increases in all years except for Black applicants in 2006 when the increase was just over 1%.

The pattern of acceptances is similar to that of applicants. The Black and Mixed Race groups display the fastest growth, far in excess of that of the Asian and White groups. As with applicants the last two groups follow a similar path on a year-by-year basis. There is a differential relationship between acceptances and applicants which is considered in section 4.3.4.

West Midlands UCAS Applicants 2002-06

200

200

Asian

Black

Mixed Race

Mixed Race

White

White

2002=100

2002

2003

2004

2005

2006

100

2002

2003

2004

2004

2005

2006

2005

2006

2006/02

2006/02

Nos.

%

West Midlands UCAS Applicants Ethnic group

2002

2003

Asian

5,551

5,681

5,736

6,065

5,891

,340

6%

Black

1,029

1,162

1,419

1,822

1,838

,809

79%

,598

,705

,755

,939

1,020

,422

71%

Mixed Race

WM Total

150

2002=100

100

Asian

Black

WM Total

150

West Midlands UCAS Acceptances 2002-06

Other

,130

,134

,251

, 249

,,119

92%

White

23,979

24,355

24,502

,174

26,056

25,339

1,360

6%

WM Total

33,999

34,655

34,889

37,062

36,306

2,307

7%

2002

2003

2004

2005

2006

West Midlands UCAS Acceptances Ethnic group

2006/02

2006/02

Nos.

%

Asian

4,546

4,684

4,634

4,902

4,693

,147

3%

Black

,740

,860

1,024

1,231

1,263

,523

71%

Mixed Race

,497

,580

,599

,747

,800

,303

61%

Other

,103

,101

,122

,185

,182

,079

77%

White

20,332

20,531

20,573

22,051

20,855

,523

3%

WM Total

28,548

28,923

28,789

30,689

29,614

1,066

4%

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.3.3 Ethnicity & Disadvantaged Groups

Applicants from the minority ethnic groups are far more likely to come from disadvantaged backgrounds than their White counterparts. The distribution of each ethnic group across the quintiles of disadvantaged communities is shown in the bar charts and tables below. For the Asian, Black and Mixed Race groups the largest percentage of applicants in the West Midlands is found in the most disadvantaged quintile. The sharpest contrast is between the White and Black ethnic groups - nearly half (48%) of Black applicants are from the most disadvantaged quintile whereas only 8% of White applicants are from this quintile.

This picture is reversed when the least disadvantaged quintile is considered - only 4% Black applicants are from this quintile but a third of White applicants are from this most advantaged quintile.

The relationship between acceptances and disadvantaged groups is essentially the same as the distribution observed with applicants.

UCAS Applicants Ethnic Groups & Disadvantage 2006 50

50

White Black

40

UCAS Acceptances Ethnic Groups & Disadvantage 2006

30

20

20

10

10

Q1

Q2

Q3

Q4

50

0

Q5

UCAS Applicants Ethnic Groups 2006

Q1

Q2

50

Black

Asian

Mixed Race 30

20

20

10

10

Q1

Q2

Q3

Q4

0

Q5

UCAS Applicants - 2006, Ethnic Group Distribution: Disadvantage Quintiles Quintile

Q5

Black

Mixed Race 30

0

Q4

White

40

Asian

Q3

UCAS Acceptances Ethnic Groups 2006

White

40

Black

40

30

0

White

White

Black

Asian

Mixed

Q1

8%

48%

32%

25%

Q2

13%

28%

26%

Q3

19%

13%

Q4

26%

Q5

34%

Q1

Q2

Q3

Q4

Q5

UCAS Acceptances - 2006, Ethnic Group Distribution: Disadvantage Quintiles Quintile

White

Black

Asian

Mixed

Q1

7%

47%

31%

23%

21%

Q2

12%

28%

27%

21%

16%

18%

Q3

19%

13%

16%

18%

6%

12%

16%

Q4

26%

7%

12%

17%

4%

13%

18%

Q5

36%

4%

13%

20%

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4.3.4 Ethnicity & the Proportion of Applicants Accepted

There are differences in acceptance rates (the proportion of applicants that are accepted) between ethnic groups.

The rate is highest with White applicants (82% in 2006) and lowest with Black applicants where the rate was below 70% (69%). Much of these differences is likely to be related to the varied distribution of ethnic groups.

West Midlands UCAS Acceptances as % of Applicants 2006

West Midlands UCAS Acceptances as % of Applicants 2002-06

85 80 75 70 65 0

White

Asian

Mixed Race

Ethnic group

2002

2003

2004

2005

2006

Asian

82%

82%

81%

81%

80%

Black

72%

74%

72%

68%

69%

Mixed Race

83%

82%

79%

80%

78%

Other

79%

75%

70%

74%

73%

White

85%

84%

84%

85%

82%

WM Total

84%

83%

83%

83%

82%

Black

Generally acceptances are just under 80% of applicants for all ages and around 87% for 18 year olds but there is a significant difference according to the degree of disadvantage of the applicant. There is a clear correlation between disadvantage and acceptance rates with the lowest quintile experiencing about a 75% acceptance rate in 2006 compared with a rate ten percentage points more for the most advantaged quintile (see page 16).

“There is a clear correlation between disadvantage and acceptance rates.�

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.3.5 Ethnicity & Age Groups

The age profile is similar for most ethnic groups except for Black applicants. The age distribution of applicants is shown in the charts and tables below.

West Midlands UCAS % Age Distribution of Applicants, White & Black Applicants

60

West Midlands UCAS Applicants (2002 = 100)

40 30

10

2005

2006

Under 30

100

102

102

109

105

Over 30

100

98

104

108

109

Total

100

102

102

109

106

Under 30

100

102

103

109

106

Over 30

100

104

112

136

120

Total

100

102

103

109

106

Under 30

100

110

133

163

168

Over 30

100

127

160

241

227

Total

100

113

138

177

179

Under 30

100

120

131

164

177

Over 30

100

91

70

66

93

Total

100

118

126

157

171

Black

0

2004

Asian

20

2003

White

Black

50

2002

White

18

19

20

21

22

23

24 25-29 30-39 40+

The largest single age category for all ethnic groups is the 18 year olds accounting for over half of all White applicants (56%) and around 45% for Asians (44%) and Mixed Races (46%). However only 21% of Black applicants are 18 years old. The Black applicant age profile is also distinctive for the high proportion of over 30 year olds accounting for 20% of all applicants , whereas only 6% of White applicants and 2% of Asians are over 30.

These differences do not change the overall picture presented in section 4.3.2. The chart below shows the changes in applicants under 30 years old.

Mixed

Under 30s

2002

2003

2004

2005

2006

White

100

102

102

109

105

Asian

100

102

103

109

106

Black

100

110

133

163

168

Mixed

100

120

131

164

177

West Midlands UCAS Applicants - Under 30s 200

Asian

2002=100

Black Mixed Race White

150

100

2002

2003

2004

2005

2006

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4.3.6 West Midlands Region- Area Applicants & Acceptances

West Midlands UCAS Applicants 2006*

The charts and tables show the growth of applicants and acceptances in each of Aimhigher areas for different ethnic groups. In broad terms the patterns seen for the region as a whole are found in the areas – Asian and White groups have similar patterns and Black and Mixed Race groups grow significantly more rapidly than other groups. Where there are differences from these general patterns it is normally associated with very small numbers. There are differences in growth of applicants and acceptances between areas and these differences are often associated with different distributions of disadvantaged communities and as section 1 showed growth rates are higher the more disadvantaged the community. There are large differences in the distribution of ethnic groups between areas. This is shown in the tables below.

Asian 17% Black 5% Mixed Race 3%

Other 1%

White 74%

West Midlands UCAS Applicants (All ages) 2006 Ethnic Group Asian Black Mixed Race Other White Total* Ethnic Group Asian Black Mixed Race Other White Total*

Birm'ham & Solihull

Black Country

Coventry & Warwick

Hereford & Worcester

Staffs & S-o-T

Shrop & Telford & W

Total WM

2,858

1,737

,748

,123

,280

,100

5,846

1,031

,478

,186

,025

,072

,025

1,817

,416

,205

,143

,067

,126

,049

1,006

,148

,043

,020

,009

,021

,008

, 249

4,580

3,677

4,199

4,576

5,627

2,487

25,146

9,033

6,140

5,296

4,800

6,126

2,669

34,064

Birm'ham & Solihull

Black Country

Coventry & Warwick

Hereford & Worcester

Staffs & S-o-T

Shrop & Telford & W

Total WM

32%

28%

14%

3%

5%

4%

17%

11%

8%

4%

1%

1%

1%

5%

5%

3%

3%

1%

2%

2%

3%

2%

1%

0%

0%

0%

0%

1%

51%

60%

79%

95%

92%

93%

74%

100%

100%

100%

100%

100%

100%

100%

Hereford & Worcester

Staffs & S-o-T

Shrop & Telford & W

Total WM

West Midlands UCAS Acceptances (All ages) 2006 Ethnic Group Asian Black Mixed Race Other White Total* Ethnic Group Asian Black Mixed Race Other White Total*

Birm'ham & Solihull

Black Country

2,216

1,415

, 616

,104

, 224

,0 80

4,655

,702

,344

,120

,016

, 050

,0 19

1,251

,323

,158

,113

,055

, 102

,0 39

,790

,107

,0 29

,0 14

,006

,020

,006

,182

3,693

3,007

3,503

3,767

4,705

2,025

20,700

7,041

4,953

4,366

3,948

5,101

2,169

27,578

Birm'ham & Solihull

Black Country

Coventry & Warwick

Hereford & Worcester

Staffs & S-o-T

Shrop & Telford & W

Total WM

31%

29%

14%

3%

4%

4%

17%

10%

7%

3%

0%

1%

1%

5% 3%

5%

3%

3%

1%

2%

2%

2%

1%

0%

0%

0%

0%

1%

52%

61%

80%

95%

92%

93%

75%

100%

100%

100%

100%

100%

100%

100%

* excludes cases of unknown/no response data

Aimhigher Mike t (v7).indd 27

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.4 Disability - Full-time Students

150

More people with disabilities are gaining access to higher education. There was an increase of 31% in acceptances over the last five years from those with a disability. This contrasts with an overall increase of 4% for all students and a rise of 1% for those with no disability. The tables and chart below show the changes.

There was no decline in acceptances for students with a disability in 2006 despite the general fall as a consequence of reacting to the new fee regime.

West Midlands UCAS Acceptances 2002-06

No Disability WM Total

2002=100

120

90

Disability

2002

2003

2004

2005

2004

2005

2006

2006/02

2006/02

West Midlands UCAS Applicants Disability

2002

2003

2006

Nos. 1,595

1,590

1,877

1,957

,434

28%

No disability

32,474

33,060

33,299

35,185

33,994

1,520

5%

Total

33,999

34,655

34,889

37,062

36,306

2,307

7%

2002

2003

2004

2005

2006

Disability

West Midlands UCAS Acceptances Disability

2006/02

2006/02

Nos.

%

1,236

1,323

1,297

1,540

1,614

,378

31%

No disability

27,311

27,600

27,492

29,149

27,653

,342

1%

Total

28,547

28,923

28,789

30,689

29,267

,720

3%

Disability

%

1,523

West Midlands UCAS Applicants (2002 = 100)

West Midlands UCAS Acceptances (2002 = 100)

Disability

2002

2003

2004

2005

2006

Disability

2002

2003

2004

2005

2006

Disability

100

105

104

123

128

Disability

100

107

105

125

131

No disability

100

102

103

108

105

No disability

100

101

101

107

101

WM Total

100

102

103

109

107

WM Total

100

101

101

108

103

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A detailed breakdown of acceptances by different category of disability is shown in the table below.

West Midlands UCAS Acceptances Disability

2002

2003

2004

2005

2006

2006/02

2006/02

No disability

27,311

27,600

27,492

29,149

27,653

,342

1%

Learning difficulty

,639

,665

,683

,841

,884

,245

38%

Other disability

,225

,184

,194

,224

,230

,005

2%

Unseen disability

,172

,199

,178

,206

,147

,- 25

-15%

Deaf/partial hearing

,047

,054

,059

,076

,093

,046

98%

Blind/partial sight

,038

,061

,046

,045

,063

,025

66%

Mental health

,030

,040

,038

,033

,060

,030

100%

Wheelchair/mobility

,045

,057

,042

,052

,056

,011

24%

Multiple disabilities

,040

,046

,041

,043

,054

,014

35%

,017

,016

,020

,027

,010

59%

1,066

4%

Nos.

Autistic disorder Unknown/Not Known WM Total

,001 28,548

,347 28,923

The distribution of disability by quintile of disadvantage is shown in the table on the right. There is a correlation between quintile of disadvantage and the proportion of acceptances that have a disability – the less disadvantaged the quintile the higher the proportion of disability.

This maybe partly a matter of declaration of a disability as the more disadvantaged the quintile the higher the proportion of ‘not known’. The large difference between the disadvantaged communities is the identification of ‘learning difficulty’, 1.5% of the most disadvantaged quintile (Q1) have declared learning difficulties whilst 3.8% of the most advantaged quintile (Q5) have learning difficulties.

%

28,789

30,689

29,614

West Midlands UCAS Acceptances 2006 - Disability & Disadvantage Disability

Q1

Q2

Q3

Q4

Q5

No Disability

93.8% 94.4% 93.5% 93.2% 93.0%

Disability

4.2%

4.4%

5.5%

5.9%

6.2%

Autistic disorder

0.1%

0.1%

0.1%

0.0%

0.1%

Blind/partial sight

0.3%

0.2%

0.1%

0.3%

0.2%

Deaf/partial hearing

0.3%

0.2%

0.5%

0.3%

0.3%

Learning difficulty

1.5%

1.9%

2.9%

3.7%

3.8%

Mental health

0.2%

0.2%

0.3%

0.2%

0.2%

Multiple disabilities

0.1%

0.1%

0.2%

0.2%

0.2%

Other disability

0.8%

0.7%

0.9%

0.7%

0.7%

Unseen disability

0.6%

0.6%

0.5%

0.4%

0.5%

Wheelchair/ mobility

0.3%

0.2%

0.2%

0.2%

0.2%

Not Known

2.0%

1.3%

0.9%

0.9%

0.8%

WM Total

100%

100%

100%

100%

100%

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.5 Gender - Full-time Students

There has been an 11% increase in female applicants over the last five years. This is significantly greater than the 2% increase in male applicants and has increased further the proportion of female applicants from 54% in 2002 to 56% in 2006.

West Midlands UCAS Applicants Gender

2002

2003

2004

2005

2006

2006/02

2006/02

Nos.

%

Female

18,322

18,858

19,244

20,570

20,361

2,039

11%

Male

15,677

15,797

15,645

16,492

15,945

,268

2%

Grand Total

33,999

34,655

34,889

37,062

36,306

2,307

7%

West Midlands UCAS Applicants

West Midlands UCAS Acceptances

Gender

2002

2003

2004

2005

2006

Gender

2002

Female

54%

54%

55%

56%

56%

Female

53%

54%

55%

55%

55%

46%

45%

45%

45%

100%

100%

100%

100%

Male

46%

46%

45%

44%

44%

Male

47%

WM Total

100%

100%

100%

100%

100%

WM Total

100%

2003

2004

2005

2006

A similar relative picture is seen with acceptances - female acceptances have increased by 7% since 2002 and the proportion of females accepted is 55% in 2006.

The following tables show the relationship between gender and disadvantage for applicants and acceptances. The higher growth rate for females applies across all of the quintiles.

Acceptances 2002-06

Applicants 2002-06 - Gender & Disadvantage

120

Female

2002

2003

2004

2005

2006

Male

55%

53%

54%

56%

56%

45%

47%

46%

44%

44%

56%

56%

57%

57%

57%

Q1 Female Male Q2 Female Male Q3 Female Male Q4 Female Male Q5 Female Male

110

100

2002=100

105

80

2002

2003

2004

2005

44%

44%

43%

43%

43%

56%

56%

56%

57%

58%

44%

44%

44%

43%

42%

54%

54%

56%

56%

57%

46%

46%

44%

44%

43%

51%

54%

54%

53%

54%

49%

46%

46%

47%

46%

2006

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West Midlands UCAS Applications 2002-2006 - % change Gender & Disadvantage

30

25

Female Male

25

West Midlands UCAS Acceptances 2002-2006 - % change Gender & Disadvantage

15

15

10

10

5

5

0

0

-5

Q1

Q2

Male

20

20

-5

Female

Q3

Q4

-10

Q5

Q1

Q2

Q3

Q4

Q5

West Midlands UCAS Acceptances 2002-2006 - Gender & Disadvantage

Female Q1 Q2 Q3 Q4 Q5

2002

2003

2004

2005

2006

100

103

103

110

107

100

101

102

118

121

100

99

101

110

111

100

103

102

108

107

100

103

107

112

105

100

106

104

108

104

Male Q1 Q2 Q3 Q4 Q5

2002

2003

2004

2005

2006

100

100

98

105

100

100

109

108

113

117

100

102

98

109

109

100

101

98

104

98

100

101

96

104

95

100

94

95

101

93

The non-acceptance rate for female students is consistently higher than for males. There is a strong correlation between measures of disadvantage and non-acceptances rates as observed earlier. This analysis suggests that more than one in four (27%) of female applicants from the most disadvantaged communities (Q1) are not accepted for higher education.

West Midlands UCAS Non-Acceptance Rate 2006 - Gender & Disadvantage 30

West Midlands UCAS Non-Acceptance Rate 2006

Female

Quintile

Male

25

Female

Male

20

Q1

27%

22%

15

Q2

23%

19%

10

Q3

19%

17%

5

Q4

18%

15%

Q5

16%

14%

0

Q1

Q2

Q3

Q4

Q5

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.6 Part-time Students 4.6.1 Regional Profile of Part-time Students

There has been an overall growth of part-time students since 2002. From 2002 to 2005 (the latest year for which HESA figures are available) the number of part-time students entering the first year of courses grew faster than full-time students over the same period.

West Midlands Full and Part-time Students 2002-2006

120

FT Acceptances [UCAS] PT 1st Year All Courses All ages [HESA]

115

110

2002=100

105

100

2002

2003

2004

2005

2006

HESA data allows those entering higher education for the first time to be identified. The pie chart on page 33 shows the distribution of part-time students (17-30 year old) on undergraduate programmes in 2005. Those entering the first year of courses account for nearly half of all part-time students and nearly half (46%) of these have not been on courses in HE previously. First year entrants to undergraduate courses generally grew by a large amount (albeit from declines in the previous two years) and within this category those entering HE for the first time in the age group 17-30 years grew most rapidly of all.

“There has been an overall growth of part-time students since 2002.�

The charts and tables in this section are derived from data commissioned from HESA, except where otherwise stated and analysed using the West Midlands Aimhigher Model.

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West Midlands PT Students First Year Entrants 2002-05

West Midlands PT UG Students 2005 (17-30 years) 200

PT 1st Year UG 17-30y [HESA]

1st year No prev HE 21%

1st year Not know prev HE 3%

1st year prev HE 23%

PT 1st Year UG New to HE 17-30y [HESA] 150 2002=100

Not 1st year 53%

100

PT 1st Year UG New to HE All ages [HESA]

2002

2003

2004

2005

2006

West Midlands Part-time Students 2002-05 All courses, All ages 1st year No Prev HE 1st year Prev HE

2002

2003

2004

2005

8,741

8,939

9,664

8,706

18,157

20,242

20,247

20,886

2,210

3,102

2,303

2,600

Not 1st year

31,072

29,215

29,392

29,314

Total WM

60,180

61,498

61,606

61,506

UG courses, All ages

2002

2003

2004

2005

1st year Not Known Prev HE

1st year No Prev HE

3,499

5,441

5,973

5,740

1st year Prev HE

5,117

6,217

6,677

7,518

,446

1,174

,726

,805

9,942

15,075

15,648

15,782

Total WM

19,004

27,907

29,024

29,845

UG courses, 30 and under

2002

2003

2004

2005

1st year Not Known Prev HE Not 1st year

1st year No Prev HE

1,464

2,254

2,590

2,548

1st year Prev HE

1,913

2,294

2,386

2,734

,153

,552

,263

,314

Not 1st year

4,395

5,497

5,972

6,307

Total WM

7,925

10,597

11,211

11,903

1st year Not Known Prev HE

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - WEST MIDLANDS AIMHIGHER ANALYSIS

4.6.2 Regional Profile of Part-time Students & Disadvantage

The analysis by quintiles of disadvantage of part-time students joining the first year of courses and entering HE for the first time is shown in the charts below. Both the two lowest quintiles for all ages grew by more than the West Midlands average. The pattern for the under 30’s is less clear, though the highest growth was in the most disadvantaged quintile (Q1).

Growth of West Midlands Part-time Students 2002-05 UG New Entrants to HE

100

UG All Ages

West Midlands Part-time UG New Entrants to HE

200

UG 17-30 yo

80

Q1 Q2

175

Q5 WM Average

60 150 40 125

0

2002=100

20

Q1

Q2

Q3

Q4

Q5

Total

100

2002

2003

2004

2005

“Both the two lowest quintiles grew by more than the West Midlands average.”

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The distribution of disadvantage amongst those entering full-time and part-time courses is almost a mirror image of each other. There is a clear correlation between disadvantage and entrants to HE but the association is reversed between part-time and full-time students. Nearly a quarter of part-tme students come from the most disadvantaged quintile (Q1) compared with only 14% for full-time students whereas the most advantaged quintile (Q5) accounts for 16% of part-time entrants yet 30% of full-time acceptances.

Distribution of New Entrants PT & FT FT Acceptances 17-29 years (UCAS) PT 1st Year New to HE 17-30 years (HESA)

30

The relationship between disadvantage and parttime new entrants with no previous experience is even stronger when Foundation Degrees are considered as the chart below shows

Distribution of New Entrants to Part-time UG courses 30 years or less

30

UG FD

25 20 15

PT

10

FT

25

5

20

0

15

Q1

Q2

Q3

Q4

Q5

10 5 0

Q1

Q2

Q3

Q4

Q5

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - NEXT STEP

Next Steps Progression Rates An important development will be a thorough examination of progression rates. Whilst there is a clear picture of the numbers of students applying for and being accepted into higher education by disadvantaged communities, the population size, which is needed to estimate progression rates, is less straight forward as there will have been population movements since the 2001 census.

Nevertheless preliminary work using this data suggests that the progression rates for the least disadvantaged quintile (Q5) is more than five times higher than the most disadvantaged (Q1). Further work will be undertaken using other data sources which are expected to provide more reliable estimates.

Developments to the Model There is a growing recognition and use of SOAs as a measure of disadvantage. Whilst the WM AH have a great confidence in the model used for this publication, which has been subject to considerable research and consideration, it is recognised that there will be an increasing use by other Aimhigher Regions and other bodies of an analysis based on all domains of the IMD (as opposed to the weighted average of selected domains in the present model) and using a national (rather than regional) ranking of deprivation.

It is proposed to develop the model so that a comparable analysis is available.

Aimhigher Initiatives & Projects To date the main focus of the model has been on analysing progression to HE using UCAS and HESA data. An important development will be to apply the model (along with some of the existing findings) to data from a range of Aimhigher initiatives and projects. Many of these have been in operation for some years and it is now possible to start to assess the impact and effectiveness of different initiative and project outcomes using the model.

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Use of Data to Prove & Improve Targeting The work outlined in the publication has demonstrated the richness of the West Midlands Aimhigher Model’s analysis of data on progression to HE, and the insights it provides on progress towards widened participation.

In providing a framework for identifying disadvantaged communities the model also has applications for the area level targeting of those communities, and the individual learners within them. Recent guidance from HEFCE introduces a requirement for Aimhigher partnerships and institutional higher education widening participation activities to demonstrate the extent to which they engage with learners from deprived IMD areas. It also highlights the importance of familial experience of HE and the occupation of the main wage earner on a learners propensity to progress.

West Midlands Aimhigher’s experience of using IMD data provides a firm foundation for development. This data is readily available, easily interpretable, consistent and reliable.

However, partnerships and HEIs have expressed concerns about the challenges involved in gathering and interpreting of data on occupational backgrounds, which in turn affect it potential reliability. Young people and parents may not be willing or able to provide such information, and what is captured may not be easily interpreted. The model’s ability to test the correlation of income-contingent indicators such as eligibility for free school meals and the Education Maintenance Allowance enables their use as proxy indicators of socio-economic class. Initial work in this area suggests there is a strong correlation worthy of further exploration.

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PROGRESSION TO HIGHER EDUCATION IN THE WEST MIDLANDS - GLOSSARY

Glossary AH

Aimhigher

B & S

Birmingham and Solihull Area

BC

Black Country Area

BTEC

Business and Technology Council

COV & W

Coventry and Warwickshire Area

GCSE

General Certificate of Secondary Education

H & W

Herefordshire and Worcestershire Area

HE

Higher Education

HEFCE

Higher Education Funding Council for England

HEI

Higher Education Institution

HEIPR

Higher Education Initial Participation Rate

HESA

Higher Education Statistics Agency

IMD

Index of Multiple Deprivation

KS

Key Skills

NS-SEC

National Statistics Socio-economic Classification

ONS

Office of National Statistics

SEC

Socio-economic Classification

SOA

Super Output Area. The SOA used by the WM AH model is the Lower Layer Super Output Area that has a mean population of 1,500

STAFFS

Staffordshire and Stoke-on-Trent Area

STW

Shropshire and Telford and Wrekin Area

UCAS

Universities and Colleges Admission Service

UG

Undergraduate

WM

West Midlands

WM AH Model West Midlands Aimhigher Model (or Regional Evidence Model) The model identifies disadvantaged communities by taking a weighted average of three IMD domains where the weights are:

• Education Domain 60% • Income Domain 30% • Barriers to Housing and Services Domain 10% The model is used to divide the WM region into quintiles where Q1 represents the fifth most deprived SOAs and Q5 the fifth least disadvantaged SOAs Disadvantage

more Quintiles HEFCE

Q1

Q2

Disadvantaged

Q3

less Q4

Q5

Advantaged

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www.aimhigherwm.org

“The work outlined in the publication has demonstrated the richness of the West Midlands Aimhigher Model’s analysis of data on progression to HE.”

Many thanks to John Clawley for pioneering the West Midlands Aimhigher Model and initiating this work. Thanks also to UCAS, HESA, ONS and the Census 2001 for their data that, in conjunction with West Midlands Aimhigher Model, made this document possible.

Every effort has been made to ensure the accuracy of data at the date of print (11/07).

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Contact your local Aimhigher office for further information

Birmingham and Solihull Tel: 0121 414 2670 Email: aimhigher@contacts.bham.ac.uk

Black Country Tel: 01902 323592 Email: r.hart@wlv.ac.uk

Coventry and Warwickshire Tel: 02476 795428 Email: philip.dent@coventry.ac.uk

Hereford and Worcestershire Tel: 01905 855554 Email: v.yates@worc.ac.uk

Shropshire, Telford & Wrekin Tel: 01902 323814 Email: k.hayward@wlv.ac.uk

Staffordshire & Stoke-on-Trent Tel: 01782 294116 Email: j.m.robinson@staffs.ac.uk

Further copies of this publication can be obtained by contacting the Aimhigher West Midlands Regional Office Wolverhampton Science Park, Wolverhampton WV10 9RU Tel: 01902 824437 Email aimhigherwm@wlv.ac.uk

www.aimhigherwm.org

Copies can also be downloaded from www.aimhigherwm.org Alternative formats can be made available on request.

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