The Higher Education Journey of Young London Residents

By Professor John Storan

This report is the fifth in a series of reports providing analysis of the higher education journey of young London residents as they progress from 16-18 institutions on to their higher education study and beyond. The report also explores achievement at university and graduate employment. Taken together, the five years of reports span a significantly changing period in higher education – starting in the year before the increase in tuition fees to a maximum of £9,000 per year, and the four years after.

Our primary aim in producing these reports is to assist London local authorities to map the whole of the higher education journey of their young people, and the research aims to not only provide an illustration of that journey, but to also evidence the value of higher education to young people in London in terms of their early graduate employment six months after completing their higher education studies.

Information on the numbers of young people progressing to higher education in London has always been of interest to London local authorities, but it has taken on added importance as more and more jobs in London now and in the future will be at graduate levels 4 & 5, with an emphasis on specialist degrees.

Higher education itself is also changing and responding to the new conditions, with more colleges of Further Education and Further & Higher Education directly funded by Higher Education Funding Council to deliver degrees within the last three years; the removal of limits on the number of undergraduates universities can recruit; a decrease in the number of international students choosing to study in the UK, including EU students; the re-launch of apprenticeships and the growing development of Level 4 higher and degree apprenticeships.

These changes in the provision of higher education represent a reordering of higher education opportunities and a range of different pathways for young people in London who want to progress to Level 4 qualifications and above.

In each of our reports, we have included a different focus each year, and this year we have focused on the impact of higher education on social mobility. Government policy has focused on increasing the percentage of people entering higher education and achieving degrees since the 1990s. This has been primarily a policy drive to provide the higher-skilled workforce that the economy needs, but Widening Participation initiatives have also focused on the social mobility that higher education can offer to young people who are able to enter graduate professions.

For the last 20 years, the Higher Education Funding Council for England has provided financial incentives to universities that recruit students from low income postcodes, and who are the first in their families to enter higher education. Higher Education Funding Council for England has also provided universities with substantial funding for outreach work to encourage more and different young people to participate in higher education and access a wider range of Higher Education Institutions. The establishment of the Office for Fair Access further provided a sector-wide resource in the form of Access Agreements, which are soon to be replaced by Access and Participation Plans regulated by the Office for Students. In October 2015, Universities UK was invited by the Minister of State for Universities and Science, Jo Johnson MP, to provide advice on how universities in England could build on their contribution to social mobility. Universities UK was asked to form an advisory group to focus efforts on improving educational and career outcomes for students from disadvantaged backgrounds, those with a disability, as well as those from black, minority and ethnic backgrounds1.

The Universities UK, Social Mobility Advisory Group published their report in October 20162. The report states that there is an overwhelming correlation between a student’s experience at school, and their outcomes at university. They also cited the importance of analysing the whole of the student journey through school 16-19 education, higher education and into employment.

An important finding from the Social Mobility Advisory Group report is that “socio-economic disadvantage continues to be the most significant driver of inequality in terms of access to and outcomes from higher education”.

The report noted that “eighteen year-olds from the most advantaged groups remain 2.4 times more likely to enter university than their disadvantaged peers, and 6.3 times more likely to attend one of the most selective institutions in the UK. Having graduated from university, students from disadvantaged backgrounds are less likely to go into professional jobs, and if they do they are likely to be paid less”. The findings from the Universities UK report further demonstrate the relevance of the analyses in our reports on the journey of young people in from 16-19 education, through higher education and into employment at London regional and individual borough level. The Universities UK report cites and draws on our 2015 research in its evidence, and given this theme, our report this year includes a section on social mobility, including latest data from the Index of Multiple Deprivation on progression to higher education by IMD decile; the socio-economic status of young higher education entrants, and previous parental participation in higher education.

The social mobility data further underlines the importance of information about the progression of our young people to higher education, and of understanding the social and economic value of higher education in increased employment, graduate earnings, and in building a highly educated, socially mobile and skilled young population to support London’s economic growth and London’s future.

The report can be accessed at:




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Connecting Learning Gain and Widening Participation

By Dr Fuad Ali

As the Omnibus study has unfolded, our team has been keen to design measures that help us understand the relationships between inequality and learning gain, and how these might express themselves, directly and indirectly, through the metrics that we use and through institutional data. With more students than ever entering HE from non-traditional (HE)ritage, more of them working to maintain themselves at the time of study and the forthcoming challenges of enabling lifelong learning in a changing job market, HE institutions and the programmes that they deliver will be increasingly required to adapt to their students’ life worlds’ and terms in order to bring the best out of them. One point of entry into this dynamic space is through our data on how students report spending their time.

Student Viscosity

Student Viscosity Model Fig. 1

Figure 1

The previous blog post on learning gain introduced the idea of a Student Viscosity Model (SVM), to account for multiple challenges many students face, outside their HEI participation, that shapes their engagement with it. The ‘viscosity’ referred to here is structural in nature but negotiable to a degree. The metaphor I like to use here is of the fish swimming upstream (Figure 1), encountering specific and dynamic pressures according to their individual situations journeys and efforts. SVM differs from the contextual value add trailed briefly, if clumsily, then dropped from the schools sector, in its individual student-centricity.


A basic model for SVM can be developed by summing the time spent working for pay, providing care for dependents and commuting to campus, as self-reported on the UKES subscales of the Wave 2 survey administered in Spring 2017. It is important to note here however that these variables are not necessarily independent, as commuting times may include the school run and commutes to work. It is as first order estimates, of “life stretch”, that they are valuable.

The variability of SVM distributions between participating institutions, Gender, broad Ethnicity Groups and Age Range is plotted on Figures 2, 3, 4 and 5 below. To summarise, participating UELs’ students’ negotiate higher viscosities than Roehampton and Brunel’s. Female students face more demands on their time than their male peers. Black student groups face higher viscosity than Asian students, than White students, a well-known structural inequality. Somewhat intuitively, viscosity distributions for the four age ranges are progressively less skewed.

Student Vsicosity Model Fig. 2

Figure 2

Student Viscosity Model Fig. 3

Figure 3

Student Viscosity Model Fig. 4

Figure 4

Student Viscosity Model Fig. 5

Figure 5

Connecting with UEL attainment data, plotting SVM by marks attained on Figure 6 below suggests a modest negative correlation, and multiple linear regression analysis alongside socio-demographic dimensions of ethnicity group, gender and age group confirms viscosity as a variable of marginal significance to scored attainment. Given the predictive predilection of learning analytics in HE at the present moment, SVM may not have the perceived performance influencing heft of socio-demographic data, but from a Teaching and Learning support point of view there is an opportunity here to mould provision to everyday conditions not just when they become extenuating.

Student Viscosity Model Fig.6

Figure 6

Correlations between marks and individual UKES item scores were also educative, multiple linear regression analysis shows that time spent on individual study had a significant and positive correlation with module marks, but somewhat counter-intuitively, time spent on volunteering outside the HEI context and commuting had negative impacts.

Struggling to register the benefits of volunteering
Extra-curricular university activity and volunteering were also observed to have markedly negative impacts on Academic Behaviour Confidence Gain amongst our first year heavy cohort. Evidence of positive impacts of voluntary work on the UKES personal development subscale is challenging at this stage, as time spent on individual study is ubiquitous in its impact, be that on Being innovative and creative, acquiring employability skills or developing or clarifying personal values or ethics. Revisiting the time spent and personal development subscales in the Wave 4 data, which will be spread along more levels of study will help us understand this further, and whether benefits of voluntary commitments accrue with time or correlate with motivational values.

The question of voluntarism is interesting, not just because self-identified volunteering levels are relatively low, but for the inequality of the conditions for volunteering. In our data for last year across three institutions the, level of a student’s voluntary activity is significantly and negatively correlated to student viscosity and student study toil. Also in last year’s data, voluntary activities were not significantly correlated with the personal development indices deployed or academic behaviour confidence scores. Therefore given the data, should our most responsible advice, at least to first year students, be to just focus on their studies?

Commutancy and inequality reproduction
Recent research by Kingston University as explored the impacts of commuting on student performance and the learning support opportunities of commuting. Further analysis of commuting times in the Omnibus data shows how BAME groups and older age groups travelled on average longer weekly commutes than younger age groups and their white student peers. This ‘commutancy’ gap, when taken together with our institutional range of partners, says something quite important about the appeal of the specific university for specific genres of student, but is itself outscaled by that more sociogenetic (Fanon) Black-White attainment gap, whose strength was on the order of tens of hours of weekly commuting. The question that I have following this, is whether commutancy is additive and reproductive of existing inequality and what creative adjustments could be made at the institutional and sector level to prevent such institutional amplification of inequality.

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Beyond the REF: Making research count, making research accessible.

By Anthony Hudson and Carly Lightfoot.


This blog considers the value of institutional repositories not in only making research count, but also making it accessible to wider audiences. In the first part of the blog, drawing on an article by Carly Lighfoot, UEL’s Research Data Management Officer we provide a brief overview of the Research Excellence Framework (REF2021) and the requirement for Open Access. The second part of the blog considers the wider benefits of institutional repositories, particularly for staff who may not have the opportunity to disseminate their work through conference presentations and academic publications

Research Excellence Framework
The Research Excellence Framework is the system by which the four higher education funding bodies aim to assess the quality of research in UK higher education institutions. Panels of reviewers appraise the quality of research outputs, their impact beyond academia, and the environment that supports research.  There will be four main panels which will provide ‘leadership and guidance’ to the 34 sub-panels (subject-based units of assessment) tasked to undertake expert review. Essentially it is a mechanism to assist the funding bodies in allocating quality-related research (QR) funding. This is one part of the ‘dual support’ system which was designed to enable research councils and higher education institutions to choose which areas of research to support at arm’s length from political control. Whilst funding from research councils provides grants for specific projects or programmes of research; HE funding bodies, such as the Higher Education Funding Council for England (HEFCE) provide block grants to support institutions’ research priorities and fund their research infrastructure.

Staff and outputs
For many academic colleagues, submitting to the REF and having outputs which are considered REF-able is important, because of the impact it has on career progression within the academy.  The recent publication of REF2021 Decisions on staff and outputs provides guidelines for institutions to identify who is in scope for submission, the number of outputs required and the policy on open access. It seems expedient to remind colleagues of how to fulfil the Open Access requirements in order for their research publications to be eligible for submission to REF2021. The policy will require the final peer-reviewed manuscripts of outputs in scope – journal articles and conference proceedings published with an ISSN – must be deposited in an institutional or subject repository within 3 months of being accepted for publication. From 1 April 2018 a deposit exception will be introduced allowing outputs that are unable to adhere to the deposit timescale to be deposited within three months of the date of publication.

Research repositories
The majority of higher education institutions have an institutional repository or research archive. UEL’s repository is called ROAR: it contains a wide variety of research outputs including journal papers, book chapters, monographs, conference posters, theses and more.  Institutional repositories or research archives can enhance an institution’s profile, and as we have described above, manage research assets to meet the needs of funders. Open Access is about making research outputs accessible online. Within the academy this can lead to increased visibility and wider dissemination of work which may result in higher citation impact and opportunities for interdisciplinary collaboration. Beyond the academy there may be increased public engagement, and more equitable access to research for those less privileged.

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Outreach rapid review of the literature

by Dominik Jackson-Cole

The following rapid review of UK based outreach literature was conducted for the Reaching East and Reaching London projects. We hope you find it useful.

Figure 1. Types and volume of outreach in London 2013/14 academic year.

outreach types of events

Introduction – outreach landscape

The Higher Education Funding Council (HEFCE) and Office for Fair Access (OFFA) are the two main Widening Participation (WP) regulatory bodies which have provided funding and direction for outreach efforts. Significant amounts of WP funding was introduced in 2004 (HEFCE, 2015), however the outreach landscape changed significantly since. Aimhigher partnerships funded until 2010 provided impartial outreach and information advice and guidance (IAG) while from 2012 there has been a stronger emphasis on Higher Education institutions’ (HEIs) outreach work with the OFFA requirement of a reinvestment of a proportion of additional fee income into WP. Based on the analysis of access agreements (documents which outline the outreach strategy and expenditure for HEIs), McCaig (2016) found that the shift resulted in modern/post-1992 institutions concentrating their outreach efforts on working with 16+ high achieving students, at the expense of diversity, as they already had a good demographic profile. At the same time pre-1992 HEIs targeted their outreach at raising attainment and aspirations of under-represented (mostly disadvantaged/poor) pupils who were already high achievers.

 Types of outreach

Based on a survey of 90 HEIs the most popular forms of outreach are: HEIs’ visits to secondary and further education establishments in order to (in order of frequency) raise aspirations, support progression and attainment, and provide mentoring to target groups (CFE and Edge Hill University, 2013). Summer schools, campus visits, mentoring and interventions using student ambassadors were seen as the most effective (Sutton Trust, 2008), however establishing causality here has been problematic (see below).

Evaluation and its limitations  

Evaluation schemes differ from institution to institution and there is a lack of consistency across the sector, especially in terms of quantitative data (ARC Network, 2013; Rodger and Burgess, 2010; UVAC, 2010). Issues with establishing causality seem to be a recurring theme (ARC Network, 2013; HEFCE, 2015). There are particular difficulties with measuring effectiveness of outreach to mature, part-time and vocational students, as well as primary school pupils (ARC Network, 2013). This is due to the impact of a multitude of factors on the educational pathways of learners. By now, most research projects account for these, e.g. socio-economic backgrounds, types of schools attended, achievement type and level, etc. However, they do not often, if at all, account for and link with policy changes in other parts of the education sector, like the effects of withdrawal of EMA in Further Education (Britton and Dearden, 2015), or the introduction of pupil premium in primary and secondary schools (Carpenter, et al., 2013). Although with their own limitations and ethical issues, longitudinal studies (Gazeley and Aynsley, 2012) as well as controlled trials (Gorard et al., 2012) have been suggested as a way forward for evaluation efforts. To this effect, since 2014 the HEFCE has recommended that institutions sign up to the Higher Education Access Tracker (HEAT) scheme, which helps track individual learners’ exposure to outreach interventions all through their student life cycle (HEFCE, 2014).

Effectiveness – what works.

As the evaluation of outreach is problematic there is no hard evidence as to which particular combination of outreach interventions is the most effective (ARC Network, 2013). The HEFCE (2015) study linking GCSE results with HE participation found that since significant WP investment began in 2004 the actual HE participation of young learners (aged 18-19) has increased by up to 4 percentage points above the expected participation rate, as inferred from GCSE results (HEFCE, 2015) therefore supporting a thesis that existence of any form of outreach has been beneficial (ARC Network, 2013).  However, big dataset/cohort research projects suggest that attainment and in particular, Key Stage 4 (KS4, e.g. GCSEs, usually taken at 16), are the best predictors/have the biggest impact on HE participation (Chowdry et al., 2012; Crawford, 2014).

Implications and future changes.

This suggests therefore that most of outreach should be targeted at pre-16 education and concentrate on improving attainment (Crawford, 2014), which differs significantly from the current outreach landscape. Further changes in the outreach arena may be needed, as the analysis of 2016-17 access agreements suggests that despite systematically increasing the outreach budget, institutions still allocate the majority of their WP funds into financial support (OFFA, 2015), which has been proven to have very little, to no, effect on attracting/deterring students from under-represented/ disadvantaged backgrounds (Nursaw Associates, 2015).


ARC Network (2013) Literature review of research into widening participation to higher education. Report to HEFCE and OFFA.

Britton, J and Dearden, L. (2015) The 16 to 19 bursary fund: impact evaluation. Research report. Institute for Fiscal Studies & Institute of Education

Carpenter, H., Papps, I., Bragg, J., Dyson, A., Harris, D., Kerr, K., Todd, L. and Laing, K. (2013) Evaluation of Pupil Premium. Research Report. TNS BMRB, TECIS, Centre for Equity in Education, University of Manchester & Newcastle University

CFE and Edge Hill University (2013) The uses and impact of HEFCE funding for widening participation. Bristol: HEFCE. Available at:

Chowdry, H., Crawford, C., Dearden, L., Goodman, A. and Vignoles, A. (2012) Widening participation in higher education: Analysis using linked administrative data. Journal of the Royal Statistical Society. Series A: Statistics in Society, 176(2), 431-457.

Crawford, C. (2014) The link between secondary school characteristics and university participation and outcomes. CAYT Research Report. Institute for Fiscal Studies and University of Warwick.

Gazeley, L. and Aynsley, S. (2012) The contribution of pre-entry interventions to student retention and success. York: Higher Education Academy. Available at:

Gorard, S., See, B. H. and Davies, P. (2012) Attitudes and aspirations in educational attainment: exploring causality. York: Joseph Rowntree Foundation. Available at:

Nursaw Associates (2015) What do we know about the impact of financial support on access and student success? Review of the research and evaluation of the impact of institutional financial support on access and student success. Report to the Office for Fair Access (OFFA).

Higher Education Funding Council for England (HEFCE) (2014) Guidance for national networks for collaborative outreach. No. 20/2014. HEFCE: Bristol.

HEFCE (2015) Delivering opportunities for students and maximising their success. Evidence for policy and practice 2015-2020. No. 2015/14 Policy development. HEFCE: Bristol.

Office for Fair Access (OFFA) (2015) Access agreements for 2016-17: key statistics and analysis. No 2015/06 OFFA: Bristol.

Rodger, J. and Burgess, M. (2010) Qualitative evaluation of the Aimhigher Associates programme: pathfinder. Bristol: HEFCE. Available at:

The Sutton Trust (2008) Increasing higher education participation amongst disadvantaged young people and schools in poor communities. Available at:

University Vocational Awards Council (UVAC), (2010) Progression from Vocational and Applied Learning to Higher Education across the UK. London: UK Commission for Employment and Skills (UKCES). Available at:


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Summit Commentary: Managing Change and Unlocking the Future

In this guest blog, Andrew Rawson, Principal of Action on Access, provides a thoughtful commentary on this year’s summit.

Access HE SummitEvery year the Summit provides the latest information and practical support enabling delegates to address directly their own policies, processes and practice with regard to current issues in access, participation and enabling successful students.

Excellent speakers, committed and enthusiastic delegates, and valued, exceptional workshops gave clear direction, maximum traction and coherence to the main themes of the day:

  • the impact of myriad recent – and imminent – changes in the policy landscape
  • the raising of attainment in secondary education, of BAME students in HE
  • demonstrating evaluation, evidence and impact across WP activity
  • the intersectionality of Equality, Diversity and Inclusion and WP with focuses on adults, on estranged students, on BAME students, on mental health, on entrepreneurship, preparing students for employment and exploring unconscious bias.

Seven practical, worked-through, evidenced tool kits and frameworks presented practice that delegates could use; with valuable offers of further support from presenters. Networking opportunities, as always, were high and greater space this year was given to networking, sharing practice and, from conversations I heard, collaborative opportunities and bids.

The key messages from keynote speakers: John Storan (Summit chair) concisely summed up the volatile policy landscape with its opportunities. Dominic Herrington (SE Regional Commissioner for Schools) detailed DfE core commitment to WP and access; and developing relationships between HEIs and schools with HEIs often offering leadership support but he stressed it was ‘the alignment in values of aspiration, inclusion and collaboration’ which was delivering raised standards across the sectors and driving access, participation and success. Professor Les Ebdon (Director, Fair Access) summarised and evidenced how much access and WP had improved over the last ten years, not least through access agreements. He highlighted long-term sustained outreach programmes and student lifecycle approach as two highly critical contributory factors. He emphasised that part-time and mature student recruitment and BAME attainment need to be seriously addressed.

Echoing Dominic Herrington on HEI-school partnerships Les Ebdon pointed out that the DfE have stressed repeatedly that WP would be at the heart of the Office for Students and reminded us that the new organisation would be lead by a Director of Access and Participation’. He encouraged us all to respond to the current consultation on the Office for Students to ensure professional and practitioner viewpoints were clearly represented

Professor Mary Stuart, Vice Chancellor, University of Lincoln, spoke on student retention and success and her notion of institutional responsibilities to provide and incorporate ‘comfortableness’ (similar but not equivalent to engagement/belonging); the encouragement of persistence in students through appropriate support; and a responsive and flexible curriculum. Institutions must develop their enhanced understanding of the importance of ‘place’ and their role in preparing students for a volatile and non-stable job market.

Following recommendation of the Social Mobility Advisory Group last year Chris Hale, Director of Policy UUK, explained how UUK were developing an ‘Evidence and Impact Exchange’ to help institutions develop and share evidence and data to inform and evidence WP and student success. Priorities for development were; understanding the evidence base, comprehensive data mapping, identifying and closing gaps, dissemination. The overall aim – knowledge mobilisation. Two main challenges for the Exchange were to ensure independence and yet be properly a part of the sector; and to ensure sustainability.

Ilyas Nagdee, Black Students’ Officer, NUS, spoke of a sector with embedded persistent racial inequality undermining HE as a public good and force for social inclusion, citing: significant poorer attainment; poorer representation in higher tariff institutions; poorer employment outcomes; and lack of BAME progression to positions of power and influence. He reminded us of the role that (BAME) students should play; contributions to the development of curriculum design, of extra curricular activities, of teaching practice, as well as supporting programmes such as mentoring. BAME students are active in HEIs but keen to be more involved. Ilyas is gathering case studies and exemplars of SU/NUS projects and research, especially on BAME attainment. The NUS is working nationally with the Equality Challenge Unit to promote the race equality charter.

Finally, Stephen Isherwood, CEO, Institute of Student Employers highlighted that ‘graduate’ employers, rather than solely recruiting graduates, are recruiting students with lower qualifications and as apprentices. He reflected that 50% of graduate jobs each year do not get filled – often due to unpreparedness or lack of desired skills. Nevertheless, it is a very competitive market. Stephen surprised us with the assertion that one of the top drivers for employers in recruitment was diversity – together with the information that a practice of contextual recruitment was developing derived from HEI contextual admissions practice. He left us with messages of a broader recruitment practice from employers and the critical importance of work experience and other real exposure to the world of work whilst in study.

These Summits are invaluable.

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Using Free School Meals data in education research: potential and pitfalls

Free School Meals (FSM) data is commonly used in education research here in the UK, and is collected annually at the time of the school census for both primary and secondary schools. There are a number of relevant FSM data columns in the publically available census data – both numbers and percentages of those who take up the offer of free school meals, as well as the numbers and percentages of those learners who are eligible. In addition there is a third metric – those who are eligible (for performance tables) which is the most robust as this is an average of three years’ worth of data.

To be eligible for FSM the family must be in receipt of one of a number of state benefits, including jobseekers, disability, housing etc. As such, the FSM eligibility data points have been independently verified and as such are a very robust and useful to use as a proxy to determine the numbers of learners in low income households at a particular school.

Interestingly there is a differential between those learners who are eligible for FSMs and those who take advantage of the offer. This discrepancy varies considerably between Local Authority (LA) areas, and many LAs run programmes and drives to ensure those who are eligible take up the offer, as this also has an impact on the pupil premium funding that the school receives from central government.

Using London as an example, based on the latest school census (collected January 2017) we can see that there are differences in the numbers of those who are eligible for FSM, those who are actually taking up free school meals, and the metric of FSM used for the performance tables.

Graph 1: Comparison of the three FSM metrics by Local Authority (London)

London FSM data all cols percent 2017


When the latest school census was released, it was noted by various commentators that the numbers of those who were in receipt of school meals were fewer than in the previous years. In fact, across all school types there were 14% of learners eligible for FSM provision, the lowest proportion since 2001 when records began.

While this is true – it does not reflect fewer learners from low income households – rather this reflects the continuation of austerity economics whereby many benefits have been cut, and where the earning threshold for state assistance has also been lowered. As FSM eligibility depends on the receipt of income related benefits – when there are fewer benefits claimants the proportion of learners who are eligible for FSMs also decreases. The following graph shows the average FSM data for those learners who are eligible for and who claimed FSMs at maintained nursery and state-funded primary schools, state funded secondary schools, special schools and pupil referral units.

Graph 2: Percentage of learners’ eligible for, and claiming FSM

Percent learners eligible for and taking FSM


Graph 3: Percentage of pupils and claiming FSM, secondary and primary level

FSM primary secondary since 2001

So while FSM data is still a robust proxy for low income households, it is increasingly clear that there are many households who continue to be economically impoverished but no longer are counted by this data point. To understand the recent history of FSM figures, we need to examine the previous coalition government’s policy which began to cap benefits that a household could claim in a year. The first benefits cap was introduced in 2013 and was set at £26,000 (the average income for a family in the UK at the time). In November 2016 there was a further benefits cap introduced by the conservative government which further reduced the income rate at which a household could claim state benefits. This was lowered to £23,000 in London, and £20,000 for the rest of the country. These caps have affected thousands of households with children, the majority of which are in London.

It is clear then that FSM data should no longer be used alone as a proxy for low income households, but instead should be used as one of a bundle of measures to establish the numbers of learners from low income households.

This does present a number of problems for the schools’ data analyst. The other data sets available to establish household income are not based on school level data and these data are not collected annually. The Indices of Deprivation – in particular the Index of Multiple Deprivation (IMD) and the income deprivation affecting children index (IDACI) are geographically based series of data which although robust, are difficult to analyse alongside school based data as the areas of geography do not necessarily correspond to where learners live in relation to the school postcode. Alongside this the latest IMD data is from 2015, so there will be a mismatch of years. While there will be more technical skill involved, and time taken to marry these data sets, it is clear that relying solely on the FSM data as an indicator of poverty at school level is problematic. Certainly any FSM data since 2013, and particularly after 2016 needs to be understood within the wider context of the change in state benefits and therefore no longer adequately reflects the numbers of young people from low income households.


Graph 3 taken from Department for Education, Statistics: school and characteristics of schools and pupils. Main Text: SFR28/2017, page 1, available from:



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Outreach survey with London schools

Coming from the work that Continuum conducted for the Reaching East and Reaching London project are the results of a survey we conducted with London schools regarding their outreach delivery.

We developed the survey in consultation with colleagues from UEL’s Education and Community Partnerships team to ensure ease of use, and the correct terminology for outreach events. Initially we piloted the survey with four schools with whom UEL has a good relationship. No problems were reported during the pilot and the average time taken on these surveys was around 10 minutes.

We had 159 complete responses from schools across London – which is approximately a 33% response rate.

From the survey we found that nearly 70% of schools surveyed have at least one dedicated staff member dealing with the organisation of outreach activities.

In terms of frequency of activity, the schools are quite varied in how often their learners attended any type of outreach activity. The two largest categories here are over 15 events in the year under investigation, and between 4-6 events. This shows that there is a large difference between schools in how often they are accessing outreach activity.

how many times outreach

It is clear from the survey that the majority of activity is taking place with year 12 and year 13 groups. From the 2266 total events we mapped via the project, 1299 of them were for year 12 and 13 students, representing 57% of all activity. While we would expect a considerable amount of activity in these years as some events are designed specifically for the final years of schooling (e.g. UCAS application support, and student finance talks) we also know from the literature that the most effective way to widen participation is to target outreach activity to pre-16 year olds and concentrate on improving attainment (Crawford, 2014).

year groups

When we examine this question in terms of type of activity offered, it is clear that campus visits are the most popular activity (comprising 15.1% of all outreach), followed by gifted and talented programmes (14.6%). The least amount of outreach activity comes in the form of examination support which is just 6% of all outreach activity.

outreach types

We asked about increases in outreach activity between the 2013/14 and 2014/5 academic years, and nearly 60% of schools surveyed said that there had been an increase in activity, with a further 32% saying the frequency of activity has remained approximately the same.


Crawford, C. (2014) The link between secondary school characteristics and university participation and outcomes. CAYT Research Report. Institute for Fiscal Studies and University of Warwick.

This project was funded by UEL, UCL and the University of Greenwich from HEFCE NNCO monies.

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Widening participation to postgraduate study: Undiscovered country or the next frontier?

By Anthony Hudson

Postgraduate and undergraduate student numbers are at record highs.  Some 408,000 students commenced full-time undergraduate study in 2016/17, a 1 percent increase on 2015/16 and 90,600 students embarked on a full-time taught postgraduate course, a 22 per cent increase on the previous year. The concerns about initial access to higher education and widening participation on entry have now shifted to differential education outcomes between student groups and their progression post-graduation to further study or into employment.

Through the Catalyst fund HEFCE have committed £7.5 million to support institutional projects designed to address the barriers to student success, which result in differential outcomes for students with widening participation characteristics. The groups the projects are designed to benefit include: students from lower socio-economic groups, black and minority ethic students, disabled students, mature students and those who study part-time. In the Office for Fair Access (OFFA) guidance for 2018-19 access agreements; understanding and responding to the challenges faced by different groups of students is one of the strategic priorities institutions are expected to address (OFFA, 2017). But for many learners, particularly those from widening participation backgrounds, the barriers to study at undergraduate level are replicated at postgraduate level.

Undiscovered country or the next frontier in widening participation?
Widening postgraduate participation has been described as the ‘undiscovered country’ (Hudson, 2013: 151). Whilst there is a well-developed body of literature and mature policy on initial access to higher education, in comparison widening postgraduate participation is under researched and has received limited policy attention. The Panel on Fair Access to the Professions (2009) recognised that a postgraduate qualification was necessary for many professional careers and enabled access to competitive sectors of the labour market.  A number of subsequent reports (Smith et al, 2010; and 1994 Group, 2012) voiced concerns about the future of postgraduate education, describing postgraduate participation as ‘the next frontier of widening participation’ (Higher Education Commission, 2012:12).

In calling for changes to policy and practice, the reports set out detailed recommendations on: better understanding postgraduate provision and the postgraduate population; assessing the demand for postgraduate skills; and widening postgraduate participation. The arguments for doing so are made in terms of both economic health and social justice.

Policy response
Despite numerous reports the policy response has been somewhat limited. Having identified finance as a major barrier to widening postgraduate progression, HEFCE funded the Postgraduate Support Scheme (PSS). Informed by a pilot PSS in 2014/15, the scheme provided scholarships for taught postgraduate courses in 2015/16. An evaluation of the scheme (Wakeling et al 2017a) reported that data collection and monitoring needed to be improved in order to evaluate impact. Whilst there was some evidence for institutional impact, with a strengthened commitment to widening postgraduate participation, in many other institutions, PSS ‘…has not led to a substantial change in policy or practice’  (Wakeling et al, 2017a: 5).

Widening postgraduate participation or widening inequality?
Prior to the PSS initiative and the subsequent introduction of postgraduate loans, studies  identified inequalities in postgraduate progression (Wakeling and Hampden-Thompson, 2013) and further that ‘…existing inequalities are transmitted more strongly across generations and social mobility falls’  (Lindley and Machin, 2012: 266).

Drawing on Labour Force Survey data (LFS) Wakeling & Laurison (2017:552) conclude: ‘that social class inequalities not only persist at postgraduate level, but have widened over time.’  Consequently those institutions which have a demonstrable commitment to widening participation will be key in widening postgraduate participation (Wakeling et al, 2017b).

Loan alone
Loans alone are not enough – in many cases they will not cover the full cost of study. Prospective postgraduates may also be surprised to discover that a number of their chosen institutions charge an application fee. Stubbs and Wakeling (2017) reported that many Russell Group institutions charge an application fee for taught postgraduate courses which ranges from £25.00 to £75.00. Making multiple applications could therefore become an expensive proposition, more so if additional costs for travel and accommodation are incurred to attend open days and interviews.

However, as Wakeling et al (2017b) note, it is still too early to determine the full impact of postgraduate loans and the impact of undergraduate debt is unknown. Clearly more research is required. In the meantime it will be interesting to see whether the newly created Office for Students (OfS), which will replace HEFCE and OFFA when it is fully operational in April 2018, will take a proactive approach to develop a more informed and comprehensive policy on widening postgraduate participation.

Hudson, A. (2013) ‘The undiscovered country: widening participation to postgraduate study’, in Hill, M., Hudson, A., Jones, P., Renton, R., Saunders, D., and Storan, J. (eds.) Widening Access to Higher Education in Divided Communities. FACE: London.

Lindley, J. and Machin, S., (2012) ‘The Quest for More and More Education: Implications for Social Mobility’, Fiscal Studies, 33 (2): 265–286.

OFFA (2017), Strategic guidance: developing your 2018-19 access agreement. OFFA: Bristol.  Available at: Accessed: 21.02.2017.

Panel on Fair Access to the Professions (2009) Unleashing Aspiration: The Final Report of the Panel on Fair Access to the Professions. Cabinet Office: London.

Stubbs, J. & Wakeling, P. (2017) The hidden costs of applying for postgraduate study. Times Higher Education (22.08.2017).
Available at: Accessed: 18.10.2017.

Wakeling, P. and G. Hampden-Thompson (2013). Transition to higher degrees across the UK: an analysis of national, institutional and individual differences. York: HEA.

Wakeling, P., Hampden-Thompson, G. and Hancock, S. (2017b), Is undergraduate debt an impediment to postgraduate enrolment in England?. British Educational Research Journal. doi:10.1002/berj.3304. Accessed: 18.10.2017.

Wakeling, P., Hancock, S, and Ewart, A. (2017a). Evaluation of the Postgraduate Support Scheme 2015/16: Report to HEFCE. HEFCE: Bristol.

Wakeling, P. & Laurison, D. (2017) Are postgraduate qualifications the ‘new frontier of social mobility’? British Journal of Sociology, 68(3):532-555.

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HEON: Surrey Schools Dashboard

HEON Dashboard

Alongside the work that Continuum conducted for the Reaching East and Reaching London project, funded by UEL, UCL and the University of Greenwich from HEFCE NNCO monies, we also developed a dashboard of schools in Surrey for the HEON (the Higher Education Outreach Network) which is housed at the University of Surrey.

The Surrey dashboard contains contextual information about the schools in Surrey.

The Surrey HEON dashboard can be found here, and will open in a new window:

The HEON partnership has continued and expanded since the NNCO programme has ended, and is now the NCOP (the National Collaborative Outreach Programme) consortium for the region. The consortium partners are:

  • The University of Surrey
  • Farnborough College of Technology
  • Guildford College
  • North East Surrey College of Technology (NESCOT)
  • Royal Holloway, University of London
  • Surrey County Council
  • Surrey Sports Park
  • University for the Creative Arts

More information about the consortium can be found here.


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Developing inclusive measures of learning: The UEL Omnibus Learning Gain Study so far

By Dr Fuad Ali


The political economy of Higher Education (HE) is undergoing rapid transformation, with the proliferation of analytics, continuing marketization, not to mention the ongoing impacts and institutional responses to widened sectoral growth, historic fee rises, and the recent emergence of an alternative demarketised HE horizon.

With the establishment of the Teaching Excellence Framework (TEF) prompting HE administrations to take systematic quantitative stock of teaching and learning, the need and capacity for inclusive and robust ‘performance’ metrics has never been more urgent. To this end, the Omnibus Learning Gain Study is one of 13 HEFCE funded projects exploring what learning gain means in the English HE context. Here learning gain has been defined as the distance travelled, or the improvement in knowledge, skills, work-readiness and personal development demonstrated by students at two points in time.

The Omnibus Study is led by UEL, in partnership with Brunel University London and the University of Roehampton. Our approach has been to develop measures and evidence of institutional value, analyse their variability with time across a wide range of learners, institutions and disciplines and explore interrelations with inequality. Our key output will be an easily administered survey instrument which works effectively across multiple motivated students, HE organisations, disciplinary diversity, and which is supportive of the teaching demands of widening participation and employability.


Beginning in late 2015 and scheduled to complete at the end of the 2017/18 academic year, a longitudinal, mixed method approach was designed, integrating student focus groups, self-reported surveys administered to students during lectures with the support of teaching and learning support staff, as well as institutional data.

Survey scales included, the 18-item Need for Cognition (NfC) scale (Cacioppo, Petty and Kao, 1984), the Academic Behaviour Confidence (ABC) scale (Sander and Sanders, 2009), portions of the UK Engagement Study (UKES) administered by the Higher Education Academy as well as a 6-item sub scale designed to prompt students self-assessments of their academic standing with respect to their peers over the duration of their studies.

In the academic year 2016/17 over 2000, mainly first year students, participated in the study across the three partner institutions; participation in the first wave at the start of the academic year was far higher than the second wave of surveying towards the end of the teaching year.


Although subsequent blog posts will discuss our emerging results further, we would like to share a few of the headlines with readers. At institutional level, the difference in ABC was significant at wave 1, however this significance was not found at the later survey point. The narrative of NfC was the opposite, with no significant difference at wave 1, and a significant difference emerging at wave 2.

Both Academic Behaviour Confidence (ABC) and Need for Cognition (NfC) scores were observed to have dropped over the duration of the academic year in question. This drop off, whether due to students recalibrating themselves with a new learning environment, or fatigue, can be seen in the difference between dashed and solid lines in plot of ABC score distributions for respective institutions below in figure 1.

Figure 1 - UEL Omnibus

The partial United Kingdom Engagement Survey (UKES), administered only during wave 2, allowed considerable contextual insight into the differential challenges unfolding within the lives of students. The panel plot in figure 2 below breaks down participating UEL students by age and gender, then time spent studying, in taught sessions, volunteering, working for pay, caring and commuting.


Figure 2 - UEL Omnibus

While only a partial sample of students participating in a survey towards the end of the academic year, the diversity of lifeworld represented here is food for thought for those in the business of designing socially just metrics, and learning provision for HE. While wanting to avoid the mishaps of contextual value add in the schools sector, we propose a Student Viscosity Model to begin a joined up treatment of structural, institutional and behavioural factors in HE.

What next?

Over the coming academic year the team will be trialling our new streamline survey instrument across UEL, Brunel and Roehampton. This streamlined 10 minute instrument was developed following reflection upon experiences administering last year’s survey, analysis of last year’s data, consultation around our organisational ecologies and several student focus groups across campuses. Retaining the Academic Behaviour Confidence scale in its entirety for its Teaching & Learning value, this year we introduce a new 8-item Motivation scale, a new 9-item Employability scale and a truncated 5-item Need for Cognition scale. Additionally, we shift the sampling frame from disciplinary variety, to multi-year cohorts of single academic programmes. Shifting the gaze longways affords us the ability to probe longer programme-scale maturation processes, and connect with and affect Employability-orientated and Programme-level stakeholders in an evidence enabled and solution-driven way.

Following workshop sessions at UEL’s Learning & Teaching Symposium with the Centre for Student Success, we will be continuing our programme of internal and external engagement. We will be speaking at Inside Government and Learning & Skills Research Network events over the coming months.



Cacioppo, J. T., Petty, R. E., & Kao, C. F. (1984). The efficient assessment of need for cognition. Journal of Personality Assessment, 48 (3): 306-307.

Sander, P. & Sanders, L. (2009) Measuring academic behavioural confidence: the ABC scale revisited. Studies in Higher Education, 34 (1): 19-35.

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