Academic year 2017/18

Progression to higher education or training

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These statistics show the percentage of level 3 pupils continuing to a sustained education or training destination at level 4 or higher in the year after completing 16 to 18 study.

The release also provides information on destination outcomes for different groups of pupils and education providers.

Headline facts and figures - 2017/18

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Background and context

Background and context 

Destination measures provide clear and comparable information on the success of schools and colleges in helping their young people continue in education, employment or apprenticeships. This measure focuses on progression from level 3 qualifications at 16 to 18 study to further education or training at level 4 or higher. 

Timeliness of data 

There is a time lag between students completing their 16 to 18 study and this measure being published. Two years have to elapse during which young people are participating in their chosen destination, and datasets have to be combined before measuring sustained participation in education or apprenticeships. 


We welcome feedback from users on the methodology and presentation of these statistics. Please direct all comments and queries to:

What is progression to higher education or training?

Progression to higher education or training shows the percentage of students that sustain an education course or apprenticeship at level 4 or higher in the two years following their 16 to 18 study. The most recent data reports on students who completed 16 to 18 study in the 2015/16 academic year and identifies their education and/or apprenticeship destinations in the two years following their last attendance at a 16 to 18 institution. The measure is designed to complement the existing destination measures (Destinations after KS4 and 16-18 study) which provide more information on the destinations that are not featured here such as employment and further study at level 3 or below. It differs from the original measures in that it uses a two-year destination window (rather than one) and calculates value-added scores for state-funded mainstream institutions which take prior attainment at GCSE and main qualification type into account. 

What is a ‘sustained’ destination? 

To be counted in a level 4 or higher destination, students have to be recorded as having sustained participation for a 6 month period in the two-year destination window. This participation can include activity in a single destination or a combination, as long as there are six consecutive months at level 4 or higher. Specific destinations such as degree, level 4/5 courses or apprenticeships are reported for these students. The two-year destination window used in this measure differs from the one-year window used in the standard destination measures in order to better report students that take gap years or similar breaks, but means that the cohort is one year further back than that published in the standard destination measures.

Who is included in the cohort? 

This measure is restricted to students that studied level 3 qualifications as there is less expectation for students studying qualifications at lower levels to progress to level 4 or higher. It thus includes students that studied academic qualifications such as A levels, applied general qualifications, technical levels, or other qualifications that have not been included in performance tables but are notionally level 3. State-funded mainstream schools and colleges are included. The cohort includes students who completed their 16 to 18 study in 2015/16, and focuses on activity during the two years after they last attended a 16 to 18 provider. 

How does the value-added (VA) score work? 

The probability of a student progressing to a level 4 or higher destination is strongly correlated with their prior attainment at KS4 (GCSE) and the qualification type they study at 16 to 18. An institution that starts with an intake of high-prior-attainment pupils will naturally have a higher rate of progression to level 4 or higher than an institution with an intake of low-prior-attainment pupils. For this reason we calculate a “value-added” score which is presented alongside the progression rate, and is an indication as to how the institution has performed once prior attainment and qualification types are taken into account. The score is calculated by comparing each individual student’s outcome (a 1 if they progress to level 4 or higher, a 0 if they do not) against the national average for the group of students with similar prior attainment and qualification type. If, for example, 85% of the highest-prior-attainment academic students progressed to higher education or training nationwide, then an individual student in that group will score 1 – 0.85 = +0.15 if they progress, but 0 – 0.85 = -0.85 if they do not.

These individual student scores are then averaged for the institution and multiplied by 100 to obtain the VA score. A VA score of +10 thus represents a ten percentage point increase on progression into level 4 or higher destinations for that institution than similar students nationally. Qualification-type groups are academic/AGQ, tech level, and other level 3 qualifications. Academic and applied general qualifications have been grouped together as they have the same expectation for progression. Bands have been determined for each institution to help put the score in context. These take into account confidence intervals, as the score is likely to be a more accurate representation of the value added by the institution for larger cohorts than small ones. Individual student scores have also been averaged at local authority level, parliamentary constituency level, national level, and for various characteristics. Bands are not applied at these levels, and the score is referred to as a “Progression score” rather than a “Value-added score”.

Progression to higher education or training after 16 to 18 study

The proportion of students studying degrees or level 4/5 courses (61%) is higher than was reported for the 2015/16 cohort in last year’s 16-18 measure (50%). This is due to the increased destination window length from one year to two years, which allows study to be included after a gap year or similar. The proportion studying higher apprenticeships shows a similar proportional increase. “Other or unsustained destination” includes students that went in to employment, further study at level 3 and below, students that didn’t sustain a level 4 or higher destination for six consecutive months, NEET destinations (not in education, employment or training), and those for whom destination data could not be found, for example if they moved abroad. More detailed information on these destination categories is provided in the 16-18 destination measures.

Qualification type

The majority of the level 3 cohort predominantly or entirely studied academic or applied general qualifications (82%). Tech levels were the main or only qualification type of 15% of the 2015/16 cohort, while just 3% of students fell into the other level 3 category. This was reserved for those students who had not studied any qualifications that are included in the performance tables, but spent more time on other courses with a notional level of 3 than on lower-level qualifications. 

The right-hand side of the chart above shows the large difference in progression rate for these three qualification types, with 68% of academic/AGQ students progressing, compared to 39% of tech level students and 24% of other level 3 students. This might be partly explained by the higher proportion of tech level students progressing into sustained employment than their academic-qualification peers. In the experimental destination measures published in October 2018 it was seen that 33% of tech level students went to an employment destination, compared to 18% of academic qualification students (the experimental publication was based around the 2015/16 cohort, but used a different methodology). 

Individual insitution value-added scores and band distribution

An institution that progresses the same proportion of its level 3 cohort into higher education or training as would have been expected according to the national average for its type of students (i.e. those with similar prior attainment at GCSE and studying the same qualification types) would receive a VA score of zero. Institutions that have more of their cohort progress get a positive VA score, while those who send fewer students on to higher education or training receive a negative score. 

Figure 3 shows the distribution of institution VA scores. Note that it does not include scores of institutions that had cohorts of fewer than 6 as these scores are suppressed in the accompanying tables. It includes consortia scores but their feeder institutions have been excluded to prevent duplication. The distribution has a mean of +0.17, a median score of +1, and a modal band of +1.5 to +4.5. A negative score was given to 44% of institutions, 52% received a positive score, and the remaining 3% scored zero. This occurs despite the national average of individual student scores being zero as the average level 3 cohort size was slightly larger for institutions receiving negative scores (180 students) than for institutions receiving scores greater than or equal to zero (157 students). 

Table 1 shows the distribution of institutional bands and the criteria under which they were obtained. VA scores are calculated for a school based on a specific cohort of pupils, but a school may have been just as effective and performed differently with a different set of pupils. To account for this natural uncertainty 95% confidence intervals (CI) around the scores are used as a proxy for the range of scores within which each school’s underlying performance measure can be confidently said to lie. Bands were derived from a combination of the VA score and these 95% confidence intervals.

Well below averageBelow averageAbout averageAbove averageWell above average
Proportion of institutions5%13%64%13%5%
CriteriaAn upper confidence interval < 0 and a score < -18An upper confidence interval < 0 and a score ≥ -18An upper confidence interval ≥ 0 and a lower confidence interval ≤ 0A lower confidence interval > 0 and a score ≤ +18A lower confidence interval > 0 and a score > +18

Note that the progression rates shown in the following tables are calculated as an average over all students that attended a relevant institution rather than an average over the relevant institution progression rates. Similarly, the scores shown are an average of the individual student scores rather than an average of the institution scores. For example, the “London” progression score is an average of all the students that studied at an institution in London, and not an average of the London institutional scores.

School and College type

State-funded mainstream (SFM) schools tend to see higher progression to higher education or training than SFM colleges. This is unsurprising given that the 16-18 destination measures show that when compared to schools, students at colleges are less likely to sustain an education destination but more likely to have an employment, apprenticeship, or unsustained destination. Sixth form colleges outperform other FE colleges in progression to higher education or training and progression score. The disparity in progression scores between schools and colleges, and between sixth form and other FE colleges, perhaps reflects a divergence in destination focus of these different institution types. There may also be a minor “London effect” in that London, a region representing 15% of the cohort and with by far the highest progression, also has a very high ratio of school to college students. 

Selective schools show a very high progression rate (88%) to higher education or training. This itself is unsurprising given that they are accepting the highest-attaining students who might well have been expected to progress into higher education or training anyway. However, selective schools still achieve a progression score of +3.3, showing that even when compared to students studying the same qualification types and with similar prior attainment across the country, they have a higher rate of progression to higher education or training. 

Non-selective schools in highly-selective areas (such as Buckinghamshire, Kent, Lincolnshire etc.) show a much lower progression rate of 56%. This is lower than expected even after taking prior attainment into account, with students at these schools progressing at a rate that is 3.5 percentage points lower than similar students nationwide (i.e. a progression score of -3.5). A possible explanation might be that students in these institutions see fewer of their peers progressing to higher education/training than the students in the selective schools, making it less of an assumed destination. Alternatively, selective schools might select on both attainment and intention to progress to higher education. 

Within schools, Local Authority maintained mainstream institutions achieved a similar progression rate (71%) to academies and free schools (72%) but a higher score (which takes prior attainment and qualification type into account). Sponsored academies had a lower progression rate than converter academies, but a similar score.


The most striking feature of the figure is the disparity between the London progression rate and score with the rates and scores of the East of England, South East and South West. 16-18 Students in London are 17 percentage points more likely to progress to higher education or training than students in the South West, and this difference remains at 17 percentage points once prior attainment and qualification type are taken into account (i.e., the score). Part of the reason for the success of London students in this measure might be that London contains a large number of higher education institutions, and so London residents may find it easier to access higher education without having to travel far (and possibly while living at home). By contrast students in, e.g., the South West may find it more expensive to access higher education. 

The North East shows a lower progression rate than the national average, but a progression score of zero which implies that it had started with lower prior attainment or had more students studying qualifications that weren’t in the academic/AGQ group. The North West, Yorkshire and the Humber, East Midlands and West Midlands all have similar progression rates to the national average (62%) and zero or slightly positive scores

Student characteristics


In the gender breakdown, it can be seen that female students progress to higher education or training at a rate that is 6 percentage points higher than male students. However, once prior attainment and qualification type is factored in, this difference drops markedly with both progression scores being very close to zero (+0.3 for females, -0.3 for males). 

The gender progression score difference is more pronounced for academic/AGQ students than the all-qualification-types total, with female students achieving a score 1.8 percentage points higher than male students. 

Interestingly, this trend reverses for tech level students, with female students 6.9 percentage points less likely to progress and scoring -4.1, much lower than male students on +2.8. A possible explanation for this reversal might be that there are gender biases in the tech level subjects being chosen by the students, with some subjects more inclined to lead to higher education or training than others.


When looking at the ethnicity breakdown it can be seen that students in the white major ethnic group progress to higher education or training at a lower rate (58%) than all other ethnic groups besides unclassified, and they are 30 percentage points behind the highest-progressing group (Chinese, although this is a relatively small major ethnic group at 16 to 18 study with fewer than 2,000 students). Once prior attainment and qualification type are taken into account, students in the white major ethnic group achieve a progression score of -4.2. Students in all other ethnic groups (again with the exception of unclassified) achieve positive progression scores, with students in the black major ethnic group scoring by far the highest, +20.9. 

Part of the explanation for this difference might be regional demographics. Students in the white major ethnic group, the lowest scoring, were more likely than other major ethnic groups to be completing their 16 to 18 study in regions that had negative progression scores (East Midlands, East of England, South East and South West). However, while 59% of the highest-scoring major ethnic group (black students) completed their 16 to 18 study at an institution in high-scoring London, region is unlikely to be the only explanation as students in the black, Asian and Chinese major ethnic groups progressed at a very high rate in regions outside of London too. It might be that part of the reason London performs so well in this measure is because it has high proportions of these high-progressing groups studying there.

Disadvantage, FSM, SEN and LLDD

Students of disadvantaged status are defined as being those eligible for pupil premium in year 11, including those receiving free school meals (FSM) and looked-after students. Students with no KS4 record are placed in “all other students”. Students with special education needs (SEN) only applies to students at schools and are categorised as 'SEN with a statement or Education, health and care (EHC) plan' and 'SEN support'. A similar category for college students but with different definitions is learners with learning difficulties and disabilities (LLDD).

Students of disadvantaged status were less likely than other students to progress to higher education or training (56% vs 63%). However the score shows that after taking prior attainment and qualification type into account, students with disadvantaged status are actually 2 percentage points more likely to progress than their peers. 

This pattern is also seen in students with special educational needs (SEN, schools only), learners with learning difficulties and disabilities (LLDD, colleges only), and those who received free school meals in year 11 (FSM), i.e. students with the characteristic progressed at a lower rate than students without the characteristic, but at a higher rate once prior attainment and qualification type are taken into account.

As was postulated in the ethnicity discussion, part of the explanation for these differences in progression score might be geographical. Students in London are twice as likely to have had disadvantaged status (32%) than those elsewhere in the country (16%). Similarly they are more likely to have received free school meals (17% of London school students vs 8% elsewhere) and to have been SEN (7% of London school students vs 5% elsewhere). If London students are removed from the analysis, then the disadvantage progression score drops from +1.6 to -0.5. It is therefore possible that the increases in progression score seen here are actually just manifestations of the London effect, although there may be other factors. For example it might be that fewer of these students go in to 16 to 18 study to start with, and so those that do are more likely to be focused on a particular destination. 

The LLDD increase (from -2.3 for other students to -1.5 for LLDD students) is the only characteristic that bucks this trend with London college students less likely to have been LLDD (11%) than elsewhere (17%). However as London also had the lowest college/school ratio (32% of London state-funded-mainstream students studied at a college, compared with 51% elsewhere), it would have made a smaller contribution to the LLDD figures.

Future developments

The statistics in this measure featured in the school performance tables in January 2020. We will listen to feedback when considering future developments of the measure. 

Data sources 

We are continuing to work with other government departments and with analysts developing the Longitudinal Education Outcomes dataset to improve the scope of activity that can be captured. 

Strands under development include linking to information on Scottish and Welsh schools and colleges. We are hopeful that this will increase our destination coverage in future years and more fairly reflect the outcomes of certain institutions.

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Find out how and why we collect, process and publish these statistics.

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