This is the second part of an extended post considering what we know – and do not know – about high attainment gaps between learners from advantaged and disadvantaged backgrounds in England.
Mind the Gap by Clicsouris
Part one provided an England-specific definition, articulated a provisional theoretical model for addressing excellence gaps and set out the published data about the size of excellence gaps at Key Stages 2,4 and 5, respectively.
Part two continues to review the evidence base for excellence gaps, covering the question whether high attainers remain so, international comparisons data and related research and excellence gaps analysis from the USA.
It also describes those elements of present government policy that impact directly on excellence gaps and offers some recommendations for strengthening our national emphasis on this important issue.
Whether disadvantaged high achievers remain so
The Characteristics of High Attainers
The Characteristics of high attainers (DfES 2007) includes investigation of:
- whether pupils in the top 10% at KS4 in 2006 were also high attainers at KS3 in 2004 and KS2 in 2001, by matching back to their fine grade points scores; and
- chances of being a KS4 high attainer given a range of pupil characteristics at KS2 and KS3.
On the first point it finds that 4% of all pupils remain in the top 10% throughout, while 83% of pupils are never in the top 10% group.
Some 63% of those who were high attainers at the end of KS2 are still high attainers at the end of KS3, while 72% of KS3 high attainers are still in that group at the end of KS4. Approximately half of high attainers at KS2 are high attainers at KS4.
The calculation is not repeated for advantaged and disadvantaged high attainers respectively, but this shows that – while there is relatively little movement between the high attaining population and other learners (with only 17% of the overall population falling within scope at any point) – there is a sizeable ‘drop out’ amongst high attainers at each key stage.
Turning to the second point, logistic regression is used to calculate the odds of being a KS4 high attainer given different levels of prior attainment and a range of pupil characteristics. Results are controlled to isolate the impact of individual characteristics and for attainment.
The study finds that pupils with a KS2 average points score (APS) above 33 are more likely than not to be high attainers at KS4, and this probability increases as their KS2 APS increases. For those with an APS of 36, the odds are 23.73, meaning they have a 24/25 chance of being a KS4 high attainer.
For FSM-eligible learners though, the odds are 0.55, meaning that the chances of being a KS4 high attainer are 45% lower amongst FSM-eligible pupils, compared to their non-FSM counterparts with similar prior attainment and characteristics.
The full set of findings for individual characteristics is reproduced below.
An appendix supplies the exact ratios for each characteristic and the text points out that these can be multiplied to calculate odds ratios for different combinations:
The odds for different prior attainment levels and other characteristics combined with FSM eligibility are not worked through, but could easily be calculated. It would be extremely worthwhile to repeat this analysis using more recent data to see whether the results would be replicated for those completing KS4 in 2014.
In 2008, the Sutton Trust published ‘Wasted talent? Attrition rates of high achieving pupils between school and university’ which examines the attrition rates for FSM-eligible learners among the top 20% of performers at KS2, KS3 and KS4.
A footnote says that this calculation was ‘on the basis of their English and maths scores at age 11, and at later stages of schooling’, which is somewhat unclear. A single, unidentified cohort is tracked across key stages.
The report suggests ‘extremely high rates of ‘leakage’ amongst the least privileged pupils’. The key finding is that two-thirds of disadvantaged top performers at KS2 are not amongst the top performers at KS4, whereas 42% advantaged top performers are not.
Also in the longitudinal tradition ‘Performing against the odds: developmental trajectories of children in the EPPSE 3-16 study’ (Siraj-Blatchford et al, June 2011) investigated through interviews the factors that enabled a small group of disadvantaged learners to ‘succeed against the odds’.
Twenty learners were identified who were at the end of KS3 or at KS4 and who had achieved well above predicted levels in English and maths at the end of KS2. Achievement was predicted for the full sample of 2,800 children within the EPPSE study via multi-level modelling, generating:
‘…residual scores for each individual child, indicating the differences between predicted and attained achievement at age 11, while controlling for certain child characteristics (i.e., age, gender, birth weight, and the presence of developmental problems) and family characteristics (i.e., mothers’ education, fathers’ education, socio-economic status [SES] and family income). ‘
The 20 identified as succeeding against the odds had KS2 residual scores for both English and maths within the highest 20% of the sample. ‘Development trajectories’ were created for the group using a range of assessments conducted at age 3, 4, 5, 7, 11 and 14.
The highest job level held in the family when the children were aged 3-4 was manual, semi-skilled or unskilled, or the parent(s) had never worked.
The 20 were randomly selected from each gender – eight boys and 12 girls – while ensuring representation of ‘the bigger minority ethnic groups’. It included nine students characterised as White UK, five Black Caribbean, two Black African and one each of Indian (Sikh), Pakistani, Mixed Heritage and Indian (Hindu).
Interviews were conducted with children, parents and the teacher at their [present] secondary school the learners felt ‘knew them best’. Teacher interviews were secured for 11 of the 20.
Comparison of development trajectories showed significant gaps between this ‘low SES high attainment’ group and a comparative sample of ‘low SES, predicted attainment’ students. They were ahead from the outset and pulled further away.
They also exceeded a comparator group of high SES learners performing at predicted levels from entry to primary education until KS2. Even at KS3, 16 of the 20 were still performing above the mean of the high SES sample.
These profiles – illustrated in the two charts below – were very similar in English and maths respectively. In either case, Group 1 are those with ‘low SES, high attainment’, while Group 4 are ‘high SES predicted attainment’ students.
Interviews identified five factors that helped to explain this success:
- The child’s perceived cognitive ability, strong motivation for school and learning and their hobbies and interests. Most parents and children regarded cognitive ability as ‘inherent to the child’, but they had experienced many opportunities to develop their abilities and received support in developing a ‘positive self-image’. Parenting ‘reflected a belief in the parent’s efficacy to positively influence the child’s learning’. Children also demonstrated ability to self-regulate and positive attitudes to homework. They had a positive attitude to learning and made frequent use of books and computers for this purpose. They used school and learning as distractions from wider family problems. Many were driven to learn, to succeed educationally and achieve future aspirations.
- Home context – effective practical and emotional support with school and learning. Families undertook a wide range of learning activities, especially in the early years. These were perceived as enjoyable but also valuable preparation for subsequent schooling. During the primary years, almost all families actively stimulated their children to read. In the secondary years, many parents felt their efforts to regulate their children’s activities and set boundaries were significant. Parents also provided practical support with school and learning, taking an active interest and interacting with their child’s school. Their parenting style is described as ‘authoritative: warm, firm and accepting of their needs for psychological autonomy but demanding’. They set clear standards and boundaries for behaviour while granting extra autonomy as their children matured. They set high expectations and felt strongly responsible for their child’s education and attitude to learning. They believed in their capacity to influence their children positively. Some were motivated by the educational difficulties they had experienced.
- (Pre-)School environment – teachers who are sensitive and responsive to the child’s needs and use ‘an authoritative approach to teaching and interactive teaching strategies’; and, additionally, supportive school policies. Parents had a positive perception of the value of pre-school education, though the value of highly effective pre-school provision was not clear cut with this sample. Moreover ‘very few clear patterns of association could be discerned between primary school effectiveness and development of rankings on trajectories’. That said both parents and children recognised that their schools had helped them address learning and behavioural difficulties. Success was attributed to the quality of teachers. ‘They thought that good quality teaching meant that teachers were able to explain things clearly, were enthusiastic about the subject they taught, were approachable when things were difficult to understand, were generally friendly, had control over the class and clearly communicated their expectations and boundaries.’
- Peers providing practical, emotional and motivational support. Friends were especially valuable in helping them to respond to difficulties, helping in class, with homework and revision. Such support was often mutual, helping to build understanding and develop self-esteem, as a consequence of undertaking the role of teacher. Friends also provided role models and competitors.
- Similar support provided by the extended family and wider social, cultural and religious communities. Parents encouraged their children to take part in extra-curricular activities and were often aware of their educational benefits. Family networks often provided additional learning experiences, particularly for Caribbean and some Asian families.
Ofsted’s The most able students: Are they doing as well as they should in our non-selective secondary schools? (2013) defines this population rather convolutedly as those:
‘…starting secondary school in Year 7 attaining level 5 or above, or having the potential to attain Level 5 and above, in English (reading and writing) and or mathematics at the end of Key Stage 2.’ (Footnote p6-7)
There is relatively little data in the report about the performance of high-attaining disadvantaged learners, other than the statement that only 58% of FSM students within the ‘most able’ population in KS2 and attending non-selective secondary schools go on to achieve A*-B GCSE grades in English and maths, compared with 75% of non-FSM pupils, giving a gap of 17 percentage points.
I have been unable to find national transition matrices for advantaged and disadvantaged learners, enabling us to compare the proportion of advantaged and disadvantaged pupils making and exceeding the expected progress between key stages.
Regression to the mean and efforts to circumvent it
Much prominence has been given to Feinstein’s 2003 finding that, whereas high-scoring children from advantaged and disadvantaged backgrounds (defined by parental occupation) perform at a broadly similar level when tested at 22 months, the disadvantaged group are subsequently overtaken by relatively low-scoring children from advantaged backgrounds during the primary school years.
The diagram that summarises this relationship has been reproduced widely and much used as the centrepiece of arguments justifying efforts to improve social mobility.
But Feinstein’s finding were subsequently challenged on methodological grounds associated with the effects of regression to the mean.
Jerrim and Vignoles (2011) concluded:
‘There is currently an overwhelming view amongst academics and policymakers that highly able children from poor homes get overtaken by their affluent (but less able) peers before the end of primary school. Although this empirical finding is treated as a stylised fact, the methodology used to reach this conclusion is seriously flawed. After attempting to correct for the aforementioned statistical problem, we find little evidence that this is actually the case. Hence we strongly recommend that any future work on high ability–disadvantaged groups takes the problem of regression to the mean fully into account.’
On the other hand, Whitty and Anders comment:
‘Although some doubt has been raised regarding this analysis on account of the potential for regression to the mean to exaggerate the phenomenon (Jerrim and Vignoles, 2011), it is highly unlikely that this would overturn the core finding that high SES, lower ability children catch up with their low-SES, higher-ability peers.’
Their point is borne out by Progress made by high-attaining children from disadvantaged backgrounds (June 2014) suggesting that Vignoles, as part of the writing team, has changed her mind somewhat since 2011.
This research adopts a methodological route to minimise the impact of regression to the mean. This involves assigning learners to achievement groups using a different test to those used to follow their attainment trajectories and focusing principally on those trajectories from KS2 onwards.
The high attaining group is defined as those achieving Level 3 or above in KS1 writing, which selected in 12.6% of the sample. (For comparison, the same calculations are undertaken based on achieving L3 or above in KS1 maths.) These pupils are ranked and assigned a percentile on the basis of their performance on the remaining KS1 tests and at each subsequent key stage.
The chart summarising the outcomes in the period from KS1 to KS4 is reproduced below, showing the different trajectories of the ‘most deprived’ and ‘least deprived’. These are upper and lower quintile groups of state school students derived on the basis of FSM eligibility and a set of area-based measures of disadvantage and measures of socio-economic status derived from the census.
The trajectories do not alter significantly beyond KS4.
The study concludes:
‘…children from poorer backgrounds who are high attaining at age 7 are more likely to fall off a high attainment trajectory than children from richer backgrounds. We find that high-achieving children from the most deprived families perform worse than lower-achieving students from the least deprived families by Key Stage 4. Conversely, lower-achieving affluent children catch up with higher-achieving deprived children between Key Stage 2 and Key Stage 4.’
‘The period between Key Stage 2 and Key Stage 4 appears to be a crucial time to ensure that higher-achieving pupils from poor backgrounds remain on a high achievement trajectory.’
In short, a Feinstein-like relationship is established but it operates at a somewhat later stage in the educational process.
International comparisons studies
OECD PISA studies have recently begun to report on the performance of what they call ‘resilient’ learners.
Against the Odds: Disadvantaged Students Who Succeed in Schools (OECD, 2011) describes this population as those who fall within the bottom third of their country’s distribution by socio-economic background, but who achieve within the top third on PISA assessments across participating countries.
This publication uses PISA 2006 science results as the basis of its calculations. The relative position of different countries is shown in the chart reproduced below. Hong Kong tops the league at 24.8%, the UK is at 13.5%, slightly above the OECD average of 13%, while the USA is languishing at 9.9%.
The findings were discussed further in PISA in Focus 5 (OECD 2011), where PISA 2009 data is used to make the calculation. The methodology is also significantly adjusted so that includes a substantially smaller population:
‘A student is classified as resilient if he or she is in the bottom quarter of the PISA index of economic, social and cultural status (ESCS) in the country of assessment and performs in the top quarter across students from all countries after accounting for socio-economic background. The share of resilient students among all students has been multiplied by 4 so that the percentage values presented here reflect the proportion of resilient students among disadvantaged students (those in the bottom quarter of the PISA index of social, economic and cultural status.’
According to this measure, the UK is at 24% and the US has leapfrogged them at 28%. Both are below the OECD average of 31%, while Shanghai and Hong Kong stand at over 70%.
The Report on PISA 2012 (OECD 2013) retains the more demanding definition of resilience, but dispenses with multiplication by 4, so these results need to be so multiplied to be comparable with those for 2009.
This time round, Shanghai is at 19.2% (76.8%) and Hong Kong at 18.1% (72.4%). The OECD average is 6.4% (25.6%), the UK at 5.8% (23.2%) and the US at 5.2% (20.8%).
So the UK has lost a little ground compared with 2009, but is much close to the OECD average and has overtaken the US, which has fallen back by some seven percentage points.
I could find no commentary on these changes.
NFER has undertaken some work on resilience in Northern Ireland, using PISA 2009 reading results (and the original ‘one third’ methodology) as a base. This includes odds ratios for different characteristics of being resilient. This could be replicated for England using PISA 2012 data and the latest definition of resilience.
Research on socio-economic gradients
The Socio-Economic Gradient in Teenagers’ Reading Skills: How Does England Compare with Other Countries? (Jerrim 2012) compares the performance of students within the highest and lowest quintiles of the ISEI Index of Occupational Status on the PISA 2009 reading tests.
It quantifies the proportion of these two populations within each decile of achievement, so generating a gradient, before reviewing how this gradient has changed between PISA 2000 and PISA 2009, comparing outcomes for England, Australia, Canada, Finland, Germany and the US.
Jerrim summarises his findings thus:
‘The difference between advantaged and disadvantaged children’s PISA 2009 reading test scores in England is similar (on average) to that in most other developed countries (including Australia, Germany and, to some extent, the US). This is in contrast to previous studies from the 1990s, which suggested that there was a particularly large socio-economic gap in English pupils’ academic achievement.
Yet the association between family background and high achievement seems to be stronger in England than elsewhere.
There is some evidence that the socio-economic achievement gradient has been reduced in England over the last decade, although not amongst the most able pupils from advantaged and disadvantaged homes.’
Jerrim finds that the link in England between family background and high achievement is stronger than in most other OECD countries, whereas this is not the case at the other end of the distribution.
He hypothises that this might be attributable to recent policy focus on reducing the ‘long tail’ while:
‘much less attention seems to be paid to helping disadvantaged children who are already doing reasonably well to push on and reach the top grades’.
He dismisses the notion that the difference is associated with the fact that disadvantaged children are concentrated in lower-performing schools, since it persists even when controls for school effects are introduced.
In considering why PISA scores show the achievement gap in reading has reduced between 2000 and 2009 at the lower end of the attainment distribution but not at the top, he cites two possibilities: that Government policy has been disproportionately successful at the lower end; and that there has been a more substantial decline in achievement amongst learners from advantaged backgrounds than amongst their disadvantaged peers. He is unable to rule out the latter possibility.
He also notes in passing that PISA scores in maths do not generate the same pattern.
These arguments are further developed in ‘The Reading Gap: The socio-economic gap in children’s reading skills: A cross-national comparison using PISA 2009’ (Jerrim, 2013) which applies the same methodology.
This finds that high-achieving (top decile of the test distribution) boys from the most advantaged quintile in England are two years and seven months ahead of high-achieving boys from the most disadvantaged quintile, while the comparable gap for girls is slightly lower, at two years and four months.
The chart reproduced below illustrates international comparisons for boys. It shows that only Scotland has a larger high achievement gap than England. (The black lines indicate 99% confidence intervals – he associates the uncertainty to ‘sampling variation’.)
Gaps in countries at the bottom of the table are approximately half the size of those in England and Scotland.
One of the report’s recommendations is that:
‘The coalition government has demonstrated its commitment to disadvantaged pupils by establishing the Education Endowment Foundation… A key part of this Foundation’s future work should be to ensure highly able children from disadvantaged backgrounds succeed in school and have the opportunity to enter top universities and professional jobs. The government should provide additional resources to the foundation to trial interventions that specifically target already high achieving children from disadvantaged homes. These should be evaluated using robust evaluation methodologies (e.g. randomised control trials) so that policymakers develop a better understanding of what schemes really have the potential to work.’
The study is published by the Sutton Trust whose Chairman – Sir Peter Lampl – is also chairman of the EEF.
In ‘Family background and access to high ‘status’ universities’ (2013) Jerrim provides a different chart showing estimates by country of disadvantaged high achieving learners. The measure of achievement is PISA Level 5 in reading and the measure of disadvantage remains quintiles derived from the ISEI index.
The underlying figures are not supplied.
Also in 2013, in ‘The mathematical skills of school children: how does England compare to the high-performing East Asian jurisdictions?’ Jerrim and Choi construct a similar gradient for maths, drawing on a mix of PISA and TIMSS assessments conducted between 2003 and 2009, so enabling them to consider variation according to the age at which assessment takes place.
The international tests selected are TIMSS 2003, 4th grade; TIMSS 2007, 8th grade and PISA 2009. The differences between what these tests measure are described as ‘slight’. The analysis of achievement relies on deciles of the achievement distribution.
Thirteen comparator countries are included, including six wealthy western economies, three ‘middle income’ western economies and four Asian Tigers (Hong Kong, Japan, Singapore and Taiwan).
This study applies as the best available proxy for socio-economic status the number of books in the family home, comparing the most advantaged (over 200 books) with the least (under 25 books). It acknowledges the limitations of this proxy, which Jerrim discusses elsewhere.
The evidence suggests that:
‘between primary school and the end of secondary school, the gap between the lowest achieving children in England and the lowest achieving children in East Asian countries is reduced’
but remains significant.
Conversely, results for the top 10% of the distribution:
‘suggest that the gap between the highest achieving children in England and the highest achieving children in East Asia increases between the end of primary school and the end of secondary school’.
The latter outcome is illustrated in the chart reproduced below
The authors do not consider variation by socio-economic background amongst the high-achieving cohort, presumably because the data still does not support the pattern they previously identified for reading.
In 2007 the Jack Kent Cooke Foundation published ‘Achievement Trap: How America is Failing Millions of High-Achieving Students from Low Income Backgrounds’ (Wyner, Bridgeland, Diiulio) The text was subsequently revised in 2009.
This focuses exclusively on gaps attributable to socio-economic status, by comparing the performance of those in the top and bottom halves of the family income distribution in the US, as adjusted for family size.
The achievement measure is top quartile performance on nationally normalised exams administered within two longitudinal studies: The National Education Longitudinal Study (NELS) and the Baccalaureate and Beyond Longitudinal Study (B&B).
The study reports that relatively few lower income students remain high achievers throughout their time in elementary and high school:
- 56% remain high achievers in reading by Grade 5, compared with 69% of higher income students.
- 25 percent fall out of the high achiever cohort in high school, compared with 16% of higher income students.
- Higher income learners who are not high achievers in Grade 1 are more than twice as likely to be high achievers by Grade 5. The same is true between Grades 8 and 12.
2007 also saw the publication of ‘Overlooked Gems: A national perspective on low income promising learners’ (Van Tassel-Baska and Stambaugh). This is a compilation of the proceedings of a 2006 conference which does not attempt a single definition of the target group, but draws on a variety of different research studies and programmes, each with different starting points.
An influential 2009 McKinsey study ‘The Economic Impact of the Achievement Gap in America’s Schools’ acknowledges the existence of what it calls a ‘top gap’. They use this term with reference to:
- the number of top performers and the level of top performance in the US compared with other countries and
- the gap in the US between the proportion of Black/Latino students and the proportion of all students achieving top levels of performance.
The authors discuss the colossal economic costs of achievement gaps more generally, but fail to extend this analysis to the ‘top gap’ specifically.
In 2010 ‘Mind the Other Gap: The Growing Excellence Gap in K-12 Education’ (Plucker, Burroughs and Song) was published – and seems to have been the first study to use this term.
The authors define such gaps straightforwardly as
‘Differences between subgroups of students performing at the highest levels of achievement’
The measures of high achievement deployed are the advanced standards on US NAEP maths and reading tests, at Grades 4 and 8 respectively.
The study identifies gaps based on four sets of learner characteristics:
- Socio-economic status (eligible or not for free or reduced price lunch).
- Ethnic background (White versus Black and/or Hispanic).
- English language proficiency (what we in England would call EAL, compared with non-EAL).
- Gender (girls versus boys).
Each characteristic is dealt with in isolation, so there is no discussion of the gaps between – for example – disadvantaged Black/Hispanic and disadvantaged White boys.
In relation to socio-economic achievement gaps, Plucker et al find that:
- In Grade 4 maths, from 1996 to 2007, the proportion of advantaged learners achieving the advanced level increased by 5.6 percentage points, while the proportion of disadvantaged learners doing so increased by 1.2 percentage points. In Grade 8 maths, these percentage point changes were 5.7 and 0.8 percentage points respectively. Allowing for changes in the size of the advantaged and disadvantaged cohorts, excellence gaps are estimated to have widened by 4.1 percentage points in Grade 4 (to 7.3%) and 4.9 percentage points in Grade 8 (to 8.2%).
- In Grade 4 reading, from 1998 to 2007, the proportion of advantaged learners achieving the advanced level increased by 1.2 percentage points, while the proportion of disadvantaged students doing so increased by 0.8 percentage points. In Grade 8 reading, these percentage point changes were almost negligible for both groups. The Grade 4 excellence gap is estimated to have increased slightly, by 0.4 percentage points (to 9.4%) whereas Grade 8 gaps have increased minimally by 0.2 percentage points (to 3.1%).
They observe that the size of excellence gaps are, at best, only moderately correlated with those at lower levels of achievement.
There is a weak relationship between gaps at basic and advanced level – indeed ‘smaller achievement gaps among minimally competent students is related to larger gaps among advanced students’ – but there is some inter-relationship between those at proficient and advanced level.
They conclude that, whereas No Child Left Behind (NCLB) helped to narrow achievement gaps, this does not extend to high achievers.
There is no substantive evidence that the NCLB focus on lower achievers has increased the excellence gap, although the majority of states surveyed by the NAGC felt that NCLB had diverted attention and resource away from gifted education.
In 2011 ‘Do High Fliers Maintain their Altitude?’ (Xiang et al 2011) provides a US analysis of whether individual students remain high achievers throughout their school careers.
They do not report outcomes for disadvantaged high achievers, but do consider briefly those attending schools with high and low proportions respectively of students eligible for free and reduced price lunches.
For this section of the report, high achievement is defined as ‘those whose math or reading scores placed them within the top ten per cent of their individual grades and schools’. Learners were tracked from Grades 3 to 5 and Grades 6 to 8.
It is described as exploratory, because the sample was not representative.
‘High-achieving students attending high-poverty schools made about the same amount of academic growth over time as their high-achieving peers in low-poverty schools…It appears that the relationship between a school’s poverty rate and the growth of its highest-achieving students is weak. In other words, attending a low-poverty school adds little to the average high achiever’s prospects for growth.’
The wider study was criticised in a review by the NEPC, in part on the grounds that the results may have been distorted by regression to the mean, a shortcoming only briefly discussed in an appendix..
The following year saw the publication of Unlocking Emergent Talent: Supporting High Achievement of Low-Income, High-Ability Students (Olszewski-Kubilius and Clarenbach, 2012).
This is the report of a national summit on the issue convened in that year by the NAGC.
It follows Plucker (one of the summit participants) in using as its starting point,the achievement of advanced level on selected NAEP assessments by learners eligible for free and reduced price lunches.
But it also reports some additional outcomes for Grade 12 and for assessments of civics and writing:
- ‘Since 1998, 1% or fewer of 4th-, 8th-, and 12th-grade free or reduced lunch students, compared to between 5% and 6% of non-eligible students scored at the advanced level on the NAEP civics exam.
- Since 1998, 1% or fewer of free and reduced lunch program-eligible students scored at the advanced level on the eighth-grade NAEP writing exam while the percentage of non-eligible students who achieved advanced scores increased from 1% to 3%.’
The bulk of the report is devoted to identifying barriers to progress and offering recommendations for improving policy, practice and research. I provided an extended analysis in this post from May 2013.
Finally, ‘Talent on the Sidelines: Excellence Gaps and America’s Persistent Talent Underclass’ (Plucker, Hardesty and Burroughs 2013) is a follow-up to ‘Mind the Other Gap’.
It updates the findings in that report, as set out above:
- In Grade 4 maths, from 1996 to 2011, the proportion of advantaged students scoring at the advanced level increased by 8.3 percentage points, while the proportion of disadvantaged learners doing so increased by 1.5 percentage points. At Grade 8, the comparable changes were 8.5 percentage points and 1.5 percentage points respectively. Excellence gaps have increased by 6.8 percentage points at Grade 4 (to 9.6%) and by 7 percentage points at Grade 8 (to 10.3%).
- In Grade 4 reading, from 1998 to 2011, the proportion of advantaged students scoring at the advanced level increased by 2.6 percentage points, compared with an increase of 0.9 percentage points amongst disadvantaged learners. Grade 8 saw equivalent increases of 1.8 and 0.9 percentage points respectively. Excellence gaps are estimated to have increased at Grade 4 by 1.7 percentage points (to 10.7%) and marginally increased at Grade 8 by 0.9 percentage points (to 4.2%).
In short, many excellence gaps remain large and most continue to grow. The report’s recommendations are substantively the same as those put forward in 2010.
How Government education policy impacts on excellence gaps
Although many aspects of Government education policy may be expected to have some longer-term impact on raising the achievement of all learners, advantaged and disadvantaged alike, relatively few interventions are focused exclusively and directly on closing attainment gaps between advantaged and disadvantaged learners – and so have the potential to makes a significant difference to excellence gaps.
The most significant of these include:
The Pupil Premium:
In November 2010, the IPPR voiced concerns that the benefits of the pupil premium might not reach all those learners who attract it.
Accordingly they recommended that pupil premium should be allocated directly to those learners through an individual Pupil Premium Entitlement which might be used to support a menu of approved activities, including ‘one-to-one teaching to stretch the most able low income pupils’.
The recommendation has not been repeated and the present Government shows no sign of restricting schools’ freedom to use the premium in this manner.
However, the Blunkett Labour Policy Review ‘Putting students and parents first’ recommends that Labour in government should:
‘Assess the level and use of the Pupil Premium to ensure value for money, and that it is targeted to enhance the life chances of children facing the biggest challenges, whether from special needs or from the nature of the background and societal impact they have experienced.’
In February 2013 Ofsted reported that schools spending the pupil premium successfully to improve achievement:
‘Never confused eligibility for the Pupil Premium with low ability, and focused on supporting their disadvantaged pupils to achieve the highest levels’.
Conversely, where schools were less successful in spending the funding, they:
‘focused on pupils attaining the nationally expected level at the end of the key stage…but did not go beyond these expectations, so some more able eligible pupils underachieved.’
In July 2013, DfE’s Evaluation of Pupil Premium reported that, when deciding which disadvantaged pupils to target for support, the top criterion was ‘low attainment’ and was applied in 91% of primary schools and 88% of secondary schools.
In June 2013, in ‘The Most Able Students’, Ofsted reported that:
‘Pupil Premium funding was used in only a few instances to support the most able students who were known to be eligible for free school meals. The funding was generally spent on providing support for all underachieving and low-attaining students rather than on the most able students from disadvantaged backgrounds.’
Accordingly, it gave a commitment that:
‘Ofsted will… consider in more detail during inspection how well the pupil premium is used to support the most able students from disadvantaged backgrounds.’
However, this was not translated into the school inspection guidance.
The latest edition of the School Inspection Handbook says only:
‘Inspectors should pay particular attention to whether more able pupils in general and the most able pupils in particular are achieving as well as they should. For example, does a large enough proportion of those pupils who had the highest attainment at the end of Key Stage 2 in English and mathematics achieve A*/A GCSE grades in these subjects by the age of 16?
Inspectors should summarise the achievements of the most able pupils in a separate paragraph of the inspection report.’
There is no reference to the most able in parallel references to the pupil premium.
There has, however, been some progress in giving learners eligible for the pupil premium priority in admission to selective schools.
In May 2014, the TES reported that:
‘Thirty [grammar] schools have been given permission by the Department for Education to change their admissions policies already. The vast majority of these will introduce the changes for children starting school in September 2015…A small number – five or six – have already introduced the reform.’
The National Grammar Schools Association confirmed that:
‘A significant number of schools 38 have either adopted an FSM priority or consulted about doing so in the last admissions round. A further 59 are considering doing so in the next admissions round.’
In July 2014, the Government launched a consultation on the School Admissions Code which proposes extending to all state-funded schools the option to give priority in their admission arrangements to learners eligible for the pupil premium. This was previously open to academies and free schools via their funding agreements.
The Education Endowment Foundation (EEF)
The EEF describes itself as:
‘An independent grant-making charity dedicated to breaking the link between family income and educational achievement, ensuring that children from all backgrounds can fulfil their potential and make the most of their talents.’
The 2010 press release announcing its formation emphasised its role in raising standards in underperforming schools. This was reinforced by the Chairman in a TES article from June 2011:
‘So the target group for EEF-funded projects in its first couple of years are pupils eligible for free school meals in primary and secondary schools underneath the Government’s floor standards at key stages 2 and 4. That’s roughly 1,500 schools up and down the country. Projects can benefit other schools and pupils, as long as there is a significant focus on this core target group of the most needy young people in the most challenging schools.’
I have been unable to trace any formal departure from this position, though it no longer appears in this form in the Foundation’s guidance. The Funding FAQs say only:
‘In the case of projects involving the whole school, rather than targeted interventions, we would expect applicants to be willing to work with schools where the proportion of FSM-eligible pupils is well above the national average and/or with schools where FSM-eligible pupils are under-performing academically.’
I can find no EEF-funded projects that are exclusively or primarily focused on high-attaining disadvantaged learners, though a handful of its reports do refer to the impact on this group.
Changes to School Accountability Measures
As we have seen in Part one, the School Performance Tables currently provide very limited information about the performance of disadvantaged high achievers.
The July 2013 consultation document on primary assessment and accountability reform included a commitment to publish a series of headline measures in the tables including:
‘How many of the school’s pupils are among the highest-attaining nationally, by…showing the percentage of pupils attaining a high scaled score in each subject.’
Moreover, it added:
‘We will publish all the headline measures to show the attainment and progress of pupils for whom the school is in receipt of the pupil premium.’
Putting two and two together, this should mean that, from 2016, we will be able to see the percentage of pupil premium-eligible students achieving a high scaled score, though we do not yet know what ‘high scaled score’ means, nor do we know whether the data will be for English and maths separately or combined.
The October 2013 response to the secondary assessment and accountability consultation document fails to say explicitly whether excellence gap measures will be published in School Performance Tables.
It mentions that:
‘Schools will now be held to account for (a) the attainment of their disadvantaged pupils, (b) the progress made by their disadvantaged pupils, and (c) the in-school gap in attainment between disadvantaged pupils and their peers.’
Meanwhile a planned data portal will contain:
‘the percentage of pupils achieving the top grades in GCSEs’
but the interaction between these two elements, if any, remains unclear.
The March 2014 response to the consultation on post-16 accountability and assessment says:
‘We intend to develop measures covering all five headline indicators for students in 16-19 education who were in receipt of pupil premium funding in year 11.’
The post-16 headline measures include a new progress measure and an attainment measure showing the average points score across all level 3 qualifications.
It is expected that a destination measure will also be provided, as long as the methodology can be made sufficiently robust. The response says:
‘A more detailed breakdown of destinations data, such as entry to particular groups of universities, will continue to be published below the headline. This will include data at local authority level, so that destinations for students in the same area can be compared.’
and this should continue to distinguish the destinations of disadvantaged students.
Additional A level attainment measures – the average grade across the best three A levels and the achievement of AAB grades with at least two in facilitating subjects seem unlikely to be differentiated according to disadvantage.
There remains a possibility that much more excellence gap data, for primary, secondary and post-16, will be made available through the planned school portal, but no specification had been made public at the time of writing.
More worryingly, recent news reports have suggested that the IT project developing the portal and the ‘data warehouse’ behind it has been abandoned. The statements refer to coninuing to deliver ‘the school performance tables and associated services’ but there is no clarification of whether this latter phrase includes the portal. Given the absence of an official statement, one suspects the worst.
The Social Mobility and Child Poverty Commission (SMCPC)
The Commission was established with the expectation that it would ‘hold the Government’s feet to the fire’ to encourage progress on these two topics.
It publishes annual ‘state of the nation’ reports that are laid before Parliament and also undertakes ‘social mobility advocacy’.
The first annual report – already referenced in Part one – was published in November 2013. The second is due in October 2014.
The Chairman of the Commission was less than complimentary about the quality of the Government’s response to its first report, which made no reference to its comments about attainment gaps at higher grades. It remains to be seen whether the second will be taken any more seriously.
The Commission has already shown significant interest in disadvantaged high achievers – in June 2014 it published the study ‘Progress made by high-attaining children from disadvantaged backgrounds’ referenced above – so there is every chance that the topic will feature again in the 2014 annual report.
The Commission is of course strongly interested in the social mobility indicators and progress made against them, so may also include recommendations for how they might be adjusted to reflect changes to the schools accountability regime set out above.
Recommended reforms to close excellence gaps
Several proposals emerge from the commentary on current Government policy above:
- It would be helpful to have further evaluation of the pupil premium to check whether high-achieving disadvantaged learners are receiving commensurate support. Schools need further guidance on ways in which they can use the premium to support high achievers. This should also be a focus for the pupil premium Champion and in pupil premium reviews.
- Ofsted’s school inspection handbook requires revision to fulfil its commitment to focus on the most able in receipt of the premium. Inspectors also need guidance (published so schools can see it) to ensure common expectations are applied across institutions. These provisions should be extended to the post-16 inspection regime.
- All selective secondary schools should be invited to prioritise pupil premium recipients in their admissions criteria, with the Government reserving the right to impose this on schools that do not comply voluntarily.
- The Education Endowment Foundation should undertake targeted studies of interventions to close excellence gaps, but should also ensure that the impact on excellence gaps is mainstreamed in all the studies they fund. (This should be straightforward since their Chairman has already called for action on this front.)
- The Government should consider the case for the inclusion of data on excellence gaps in all the headline measures in the primary, secondary and post-16 performance tables. Failing that, such data (percentages and numbers) should be readily accessible from a new data portal as soon as feasible, together with historical data of the same nature. (If the full-scale portal is no longer deliverable, a suitable alternative openly accessible database should be provided.) It should also publish annually a statistical analysis of all excellence gaps and the progress made towards closing them. As much progress as possible should be made before the new assessment and accountability regime is introduced. At least one excellence gap measure should be incorporated into revised DfE impact indicators and the social mobility indicators.
- The Social Mobility and Child Poverty Commission (SMCPC) should routinely consider the progress made in closing excellence gaps within its annual report – and the Government should commit to consider seriously any recommendations they offer to improve such progress.
This leaves the question whether there should be a national programme dedicated to closing excellence gaps, and so improving fair access to competitive universities. (It makes excellent sense to combine these twin objectives and to draw on the resources available to support the latter.)
Much of the research above – whether it originates in the US or UK – argues for dedicated state/national programmes to tackle excellence gaps.
More recently, the Sutton Trust has published a Social Mobility Manifesto for 2015 which recommends that the next government should:
‘Reintroduce ring-fenced government funding to support the most able learners (roughly the top ten per cent) in maintained schools and academies from key stage three upwards. This funding could go further if schools were required to provide some level of match funding.
Develop an evidence base of effective approaches for highly able pupils and ensure training and development for teachers on how to challenge their most able pupils most effectively.
Make a concerted effort to lever in additional support from universities and other partners with expertise in catering for the brightest pupils, including through creating a national programme for highly able learners, delivered through a network of universities and accessible to every state-funded secondary school serving areas of disadvantage.’
This is not as clear as it might be about the balance between support for the most able and the most able disadvantaged respectively.
I have written extensively about what shape such a programme should have, most recently in the final section of ‘Digging Beneath the Destination Measures’ (July 2014).
The core would be:
‘A light touch framework that will supply the essential minimum scaffolding necessary to support effective market operation on the demand and supply sides simultaneously…
The centrepiece of the framework would be a structured typology or curriculum comprising the full range of knowledge, skills and understanding required by disadvantaged students to equip them for progression to selective higher education
- On the demand side this would enable educational settings to adopt a consistent approach to needs identification across the 11-19 age range. Provision from 11-14 might be open to any disadvantaged learner wishing it to access it, but provision from 14 onwards would depend on continued success against challenging attainment targets.
- On the supply side this would enable the full range of providers – including students’ own educational settings – to adopt a consistent approach to defining which knowledge, skills and understanding their various programmes and services are designed to impart. They would be able to qualify their definitions according to the age, characteristics, selectivity of intended destination and/or geographical location of the students they serve.
With advice from their educational settings, students would periodically identify their learning needs, reviewing the progress they had made towards personal targets and adjusting their priorities accordingly. They would select the programmes and services best matched to their needs….
…Each learner within the programme would have a personal budget dedicated to purchasing programmes and services with a cost attached. This would be fed from several sources including:
- Their annual Pupil Premium allocation (currently £935 per year) up to Year 11.
- A national fund fed by selective higher education institutions. This would collect a fixed minimum topslice from each institution’s outreach budget, supplemented by an annual levy on those failing to meet demanding new fair access targets. (Institutions would also be incentivised to offer programmes and services with no cost attached.)
- Philanthropic support, bursaries, scholarships, sponsorships and in-kind support sourced from business, charities, higher education, independent schools and parents. Economic conditions permitting, the Government might offer to match any income generated from these sources.’
We know far too little than we should about the size of excellence gaps in England – and whether or not progress is being made in closing them.
I hope that this post makes some small contribution towards rectifying matters, even though the key finding is that the picture is fragmented and extremely sketchy.
Rudimentary as it is, this survey should provide a baseline of sorts, enabling us to judge more easily what additional information is required and how we might begin to frame effective practice, whether at institutional or national level.