Note:

Adult community learning statistics have been removed from this release due to data quality issues. Please see the Quality and Methodology information for details on how the data quality issues are being investigated and will be handled.

Main points

• The success rate of apprenticeships increased in 2023/24 to 74%, it is still lower than before the Covid-19 pandemic.
• Foundation level apprenticeships showed the strongest recovery in 2023/24.
• The success rate for higher apprenticeships is much lower than for other levels and has recovered the least since the pandemic.
• Higher apprentices passed only a little over of half of the application of number essential skills activities they took.
• There were large increases in the overall success rate in the sectors of:
  • Health Care and Public Services;
  • Hospitality;
  • Leisure, Sport and Travel.
• Among the larger sectors, the success rate fell in:
  • Construction;
  • Management and Professional.
• The success rate gap between learners in the most deprived areas and least deprived areas is closing.
• There were large increases in the success rate for learners across minority ethnic backgrounds.
• Apprenticeship activities completed entirely in Welsh had a higher than average success rate.

Apprenticeship success rate by academic year

Description: The apprenticeship success rate continues to recover post-pandemic, a gap still exists between the current success rate and pre-pandemic success rates.

Data on StatsWales

Note

Local authority community learning statistics have been removed from this release due to data quality issues. Please see the Quality and methodology information for details on how the data quality issues are being investigated and will be handled.

The data quality issues don’t apply to any community learning data submitted by colleges. Community learning where colleges are the lead provider is still included in this report as part of part-time further education.

Main points

• There were 155,580 learners in further education, apprenticeships or other work-based learning during the 2023/24 academic year.
• Part-time learning numbers are recovering, after a long decline.
• The number of apprenticeships started fell by 5%, compared to the previous year.
• Level 3 apprenticeships are rising, foundation apprenticeships are falling, compared to the previous year.
• More learners are studying at least partly in Welsh.
• There has been an increase in Preparation for Life and Work activities.
• There has been an increase in the percentage of work-based learning taken by learners with ethnic minority backgrounds other than White.
• A levels are less likely to be taken by learners who had experience of deprivation during secondary school.

Learners by learning and provider type

• Description: There were 130,745 learners in colleges. There were 47,855 apprentices, split between colleges and other training providers.
• [Note 1]: Some learners will have studied at multiple provider types.
• Data in Table 1.1 of the accompanying spreadsheet

Further education includes learners studying A levels and other general qualifications, as well as learners studying vocational qualifications (for example BTECs).

‘Other work-based learning’ is made up of transition qualifications for people who work with children in play or childcare settings.

Introduction

1. This report presents an estimate of initial participation in higher education (HE) for the 17 to 30 year old Welsh population for the academic years from 2016/17 until 2022/23.

2. The Higher Education Initial Participation (HEIP) measure is an estimate of the probability that a Welsh domiciled person will participate in HE by the age of 30. The analysis also looks at the difference in the HEIP between males and females. A full explanation of the methodology and data sources is in the methodology section.

3. The statistics in this publication are Official Statistics in Development as we are developing this measure and recognise that there are limitations to the methodology used. By publishing this information as Official Statistics in Development users can be involved in the development of these statistics and to contribute in making them as useful and relevant as possible.

4. We would welcome any feedback on the content of this publication whether relating to the methodology or what information could be included to make this useful for you. To provide feedback please email us at [email protected].

Why we are publishing these statistics

5. One of the strategic duties of Medr as set out in the Tertiary Education and Research (Wales) Act 2022 is to “encourage individuals who are ordinarily resident in Wales, particularly those who have additional learning needs, to participate in tertiary education.” The intention in publishing this measure is to provide some evidence about participation in HE, feeding into the overall information for participation in the wider tertiary education sector.

6. Another strategic duty of Medr is to “promote increased participation in Welsh tertiary education by persons who are members of under-represented groups”. As well as an overall HEIP measure for Wales, this publication also includes a split by sex to compare the initial participation in HE of males and females. While this is the only personal characteristic included here, part of the development of this measure will be to investigate if other characteristics could be included to provide a greater insight into the differences in participation in HE from different groups of the Welsh population.

7. Participation in tertiary education has been an area of increasing focus within the wider Welsh policy environment. In 2022, the Welsh Government commissioned the Welsh Centre for Public Policy to undertake a review evidence and best practice on inequity in tertiary education in Wales. The subsequent report was published in October 2024. In November 2024, the Senedd’s Children, Young People and Education Committee commenced an inquiry into routes into post-16 education and training with a particular focus on participation. The inquiry is ongoing.

8. A measure of initial participation in HE for Wales has not been published since 2016 when the Higher Education Funding Council for Wales (HEFCW) published statistics for the 2012/13 academic year. During this time participation measures for England, Scotland and Northern Ireland have still been produced meaning that there was a gap in evidence for Wales. However methodological differences limit how comparable the different measures across the UK are. Information on what is published in the rest of the UK is included in a later section.

Methodology

9. The HEIP measure is the sum of the initial participation rates for each age from 17 to 30 inclusive. The initial participation rates are the proportion of each age group that is participating in HE for the first time and to calculate this we need two pieces of information. The first piece of information is the number of students of each age who are participating in HE for the first time and the second is the overall population of that age in Wales.

Step 1: Estimating the number of students initially participating in HE

10. We use three data sources to estimate the number of students of each age who are participating in HE for the first time. These sources are the Higher Education Statistics Agency (HESA) Student Record, the HESA Student Alternative record (for the years 2014/15 to 2021/22) and the Lifelong Learning Wales Record (LLWR) from 2016/17 onwards collected by the Welsh Government.

11. For the HESA records we have linked data from 2004/05 to 2022/23 to identify when a person appears multiple times in the data. Details of this linking are provided in Annex A. With the records linked we find the earliest record for a student where they studied, or were still expected to study, for at least 6 months to ensure they have a considerable engagement in HE. We also check if they have previously obtained a HE level qualification and exclude those that have as they will have previously participated in HE.

12. For the LLWR data, we identify the first academic year where a student has either a learning programme or learning activity that is at the equivalent of  Level 4 or above in the Credit and Qualifications Framework for Wales (CQFW). As with the HESA  data we require that the relevant programme or activity lasts, or is expected to last, at least 6 months. Students who had a HE level qualification on entry are also excluded again.

13. The identification of students’ initial participation is performed separately for the HESA and LLWR data so the number of initial participants in each are combined to give the total number of initial participants in each academic year. The initial participants are divided into their age as at 31 August at the beginning of the academic year, e.g. for the 2022/23 academic year the students ages are calculated as at 31 August 2022.

Step 2: Estimating the overall population

14. Two data sources are used to estimate the population of Wales. These are the 2021 Census out-of-term population estimate and the mid-year population estimates for Wales from 2016 to 2022, both produced by the Office for National Statistics (ONS).

15. The base for the population estimate is the 2021 Census out-of-term population estimates. The out-of-term population is produced by the ONS as part of their census outputs, and is the usual resident population but with full-time schoolchildren and students counted at their out-of-term address. This population has been used as the base rather than using the mid-year estimates directly as we want to count students where they usually live rather than where they are studying.

16. The out-of-term population is based on the 2021 Census day of 21 March 2021 so an adjustment is made to age the population to 31 August 2021 to match the date used in the student data. For example, the number of 18 year olds is estimated as being a proportion of 17 year olds who have turned 18 since 21 March and the proportion of 18 year olds who have not yet turned 19 since 21 March.

17. A similar adjustment is made to the mid-year population estimates to age these populations from 30 June, the date of the mid-year estimates, to 31 August. We then calculate the percentage change between each adjusted mid-year estimate and the adjusted 2021 mid-year estimate for each age. These percentage changes are applied to the adjusted out-of-term population to produce at out of term-time population estimate as at 31 August for each year.

Step 3: Calculation of the initial participation rates and the HEIP measure

18. For each age from 17 to 30 years old we calculate the initial participation rate for that age by dividing the number of initial participants of that age from step 1 by the estimated population of that age from step 2.

19. The HEIP measure is calculated by summing the initial participation rates for each age. The idea behind this is that each individual participation rate represents the probability that someone of that age will participate in HE for the first time and by summing these you are building the probability that someone will participate in HE between the ages of 17 and 30 years old if these probabilities remain the same.

20. For clarity, the HEIP is not the same as dividing the total number of initial participants aged 17 to 30 in an academic year by the overall Welsh population of those ages. This would produce a much lower figure and would assume that someone is equally likely to be an initial participant in HE at any age, which is not the case.

Limitations

21. There are several limitations to note regarding the calculation of the HEIP used in this report.
a.) Initial participation in HE through studies that are not collected in the HESA records or LLWR are not be included in this measure. This would include any Welsh domiciled students studying at HE level at further education colleges in England, Scotland and Northern Ireland, some independent HE institutions in the UK or at higher education providers outside of the UK.
If someone obtained a HE level qualification via the above routes then any further HE studies that were recorded in the HESA or LLWR data would also not be included in the measure as they would be excluded due having a HE level qualification on entry.
This issue could be reduced by obtaining additional data sources that cover these other options for HE level studies.
b.) As the HESA and LLWR data are not linked together, it would be possible for someone to appear as an initial participant in both if they participated but did not obtain a HE level qualification. For example someone could appear in the HESA data but drop out after one year without obtaining any qualifications. They could then appear in the LLWR data and still be considered an initial participant. This issue would be reduced by linking the datasets prior to looking for initial participants.
c.) The measure assumes that the initial participation rates for each age will continue, however it doesn’t account for differences in participation between cohorts. For example, the levels of participation of the cohort of 18 year olds in 2022/23 when they reach the age of 30 may differ from what those who are 30 in 2022/23 for a variety of reasons including policy changes and the wider economic landscape.
d.) While the population estimates used for the overall populations are all accredited official statistics, there have been a number of assumptions made to adjust these to fit the purposes of this measure.
The first adjustment is to age the estimates to 31 August so the age is comparable to the age used from the student data and the age is relevant to the academic years. However, this adjustment uses the assumption that birth dates are equally distributed which is not the case.
The second adjustment is to ‘grow’ the adjusted out of term-time population to create a time series based on the percentage changes seen in the adjusted mid-year estimates. This assumes that the mid-year population and the out-of-term population change at the same rate.
e.) Domicile is not static. This means we are not following a specific group of people and estimating how many of them participate in HE. Instead the population that is being considered is always changing and the population is affected by inward and outward migration.
For example, someone could live in Wales until they are 24 before moving to England, if this person then participated in HE for the first time at the age of 25 they would not be included in the calculation as they would be English domiciled at that point. Conversely, someone living in England before moving to Wales and then participating in HE for the first time would be included.
f.) As this methodology does not follow specific cohorts of people, it is difficult to produce reliable figures on more detailed characteristics. This is particularly difficult if characteristics change over time, for example whether someone lives in a more deprived area, or it is difficult to get accurate population estimates.
g.) In the absence of a universal identifier to link records, algorithms are used to link the HESA student records and this will mean some incorrect links are made, or real links may be missed. In the case of incorrect links being made, then an individual’s initial participation could be discounted as we will believe they have participated in HE previously. In the case of a real link being missed then an individual could be counted as an initial participant twice, although this should be minimised by excluding those who have a prior HE level qualification recorded in the data.
These incorrect or missed links can occur due to data quality issues, such as incorrect information being recorded or digits being swapped in dates of birth. They can also occur when someone’s data is correct but varies over time, for example using different variations of their name or if someone changes their name.

Results

22. The HEIP measure is the sum of the initial participation rates for each age from 17 to 30 years old in a given academic year. The HEIP measure is not the percentage of 17 to 30 year olds who are participating in HE in that particular year. Instead the HEIP measure is an estimate of the probability that a Welsh domiciled person will participate in HE by the time they are 30 based on the initial participation rates in that year.

23. The HEIP measure in 2022/23 was 54.6%. This means that the estimated probability of a Welsh domiciled person participating in HE by the age of 30 is 54.6% based on the initial participation rates for each age from 17 to 30 in 2022/23.

24. After a drop between 2016/17 and 2017/18, the HEIP measure increased every year from 2017/18 to 2020/21 reaching a high of 58.9%. From this peak in 2020/21 there has been a decline in the following two years down to the figure of 54.6% in 2022/23. The Covid-19 pandemic will have been a factor on the levels of participation in the most recent years.

By Age

Table 1: Initial entry percentages by age – 2016/17 to 2022/23

Age	2016/17	2017/18	2018/19	2019/20	2020/21	2021/22	2022/23
17	0.8%	0.4%	0.5%	0.6%	0.3%	0.2%	0.2%
18	27.5%	27.4%	27.0%	28.1%	28.4%	29.5%	29.6%
19	10.4%	10.1%	10.3%	10.7%	11.0%	10.2%	9.4%
20	3.4%	3.5%	3.5%	3.5%	3.8%	3.4%	3.3%
21	1.9%	1.9%	2.2%	2.1%	2.4%	2.2%	1.8%
22	1.4%	1.5%	1.6%	1.6%	2.0%	1.7%	1.6%
23	1.2%	1.1%	1.3%	1.5%	1.7%	1.5%	1.3%
24	1.2%	1.2%	1.3%	1.4%	1.6%	1.3%	1.2%
25	1.1%	1.1%	1.2%	1.3%	1.5%	1.3%	1.1%
26	1.0%	1.0%	1.2%	1.3%	1.4%	1.2%	1.0%
27	1.0%	1.0%	1.1%	1.3%	1.3%	1.2%	1.2%
28	1.0%	0.9%	1.1%	1.1%	1.3%	1.1%	1.0%
29	1.1%	0.9%	0.9%	1.1%	1.2%	1.1%	0.9%
30	0.9%	0.8%	1.0%	1.1%	1.2%	1.0%	1.0%
HEIP measure	53.9%	52.8%	54.2%	56.6%	58.9%	56.8%	54.6%

25. The largest contribution to the HEIP measure comes from 18 and 19 year olds. In 2022/23 the initial participation rates for these two ages contribute 38.9 percentage points to the overall HEIP measure of 54.6%.

26. The initial participation rate of 18 year olds has increased in every year since 2018/19.

27. For other ages the initial participation rates generally increased between 2017/18 to 2020/21, before falling in the following two years.

By Sex

28. As with the overall HEIP measure, the HEIP measure for males and females decreased between 2016/17 and 2017/18 before increasing every year until 2020/21. There was then a drop in each of the following two years.

29. The HEIP measure is considerably higher for females than for males, with the gap widening across the period. In 2016/17 there was a difference of 16.5 percentage points while in 2022/23 there was a 21.6 percentage point difference.

30. The HEIP measure for females peaked at 69.8% in 2020/21 compared to 48.3% for males in the same year. The HEIP has since dropped to 65.3% and 43.7% for females and males respectively in 2022/23.

By Age and Sex

Age	Females 2021/22	Females 2022/23	Males 2021/22	Males 2022/23
17	0.2%	0.3%	0.1%	0.2%
18	35.9%	35.1%	23.5%	24.0%
19	11.8%	11.4%	8.5%	7.4%
20	3.9%	3.7%	2.9%	2.8%
21	2.4%	2.1%	2.0%	1.5%
22	2.0%	1.8%	1.4%	1.3%
23	1.9%	1.6%	1.1%	1.0%
24	1.7%	1.5%	1.0%	0.9%
25	1.6%	1.4%	1.0%	0.8%
26	1.4%	1.4%	0.9%	0.7%
27	1.4%	1.4%	0.9%	1.1%
28	1.3%	1.3%	0.8%	0.7%
29	1.4%	1.1%	0.9%	0.7%
30	1.2%	1.2%	0.8%	0.8%
HEIP measure	68.0%	65.3%	45.8%	43.7%

31. Table 2 shows that the initial participation rates are higher for females than males at every age from 17 to 30 years old for 2021/22 and 2022/23. This is also the case when looking back to 2016/17, with the exception of 17 year olds between 2017/18 and 2019/20 where the rates were level.

32. The overall initial participation rate for 18 year olds increased between 2021/22 and 2022/23, however when looking at the measure by sex this was only the case for males. The initial participation rate for female 18 year olds dropped by 0.8 percentage points between 2021/22 and 2022/23 while there was a 0.5 percentage point increase for male 18 year olds.

Participation measures in the rest of the UK

33. There is no single measure of participation across the UK making difficult to make comparisons. This section covers the differences and similarities in other participation measures across the UK.

England

34. The Department for Education (DfE) have a statistical series called ‘Participation measures in higher education’. The methodology for this series was similar to what has been used here up to the academic year 2019/20 release of the DfE statistics.

35. A new methodology called the Cohort-based Higher Education Participation (CHEP) measure was introduced for the 2020/21 academic year. Instead of estimating future participation by age 30 using current participation levels as the HEIP methodology does, the CHEP tracks cohorts of school pupils to measure participation.

36. While CHEP is quite different from the HEIP methodology, the 2021/22 release does have a section ‘Projecting future HE participation’ that uses the cohort data to produce a projection that is more similar to how the HEIP measure is constructed.

37. The rationale for changing methodology was that while the HEIP produced a timely measure there were some known limitations such as:

• estimating a higher participation rate than the real rate for a particular entry cohort when there is steady growth in entry rates for younger age groups.
• not being able to create reliable figures by region and key demographics.

38. DfE felt the CHEP methodology lessened the impact of inward and outward migration flows over time and that it would also not be affected by revisions to the ONS population estimates that occur following each Census.

39. The other benefit was that the CHEP approach would allow them to analyse participation by pupil characteristics taken from the school census such as breakdowns by gender and region of school attended.

40. One drawback of the new methodology is that it is less timely than the HEIP as it requires each 15-year-old school cohort to reach a particular age before reporting on it. In other words you would only report on the percentage participating in HE by the age of 25 for those aged 15 in the 2024/25 academic year, once the 2034/35 academic year data are available.

Scotland

41. The Scottish Funding Council (SFC) include a Higher Education Initial Participation Rate (HEIPR) in the background tables of their ‘HE Students and Qualifiers at Scottish Institutions’ statistical publication.

42. This is produced using a similar methodology to what has been presented for Wales in this publication. Although there will be differences in the exact methodology for how initial participation is identified. One difference is that it covers those aged 16 to 30 rather than 17 to 30.

43. One similarity to note is that the HEIPR for Scotland also reaches a peak in 2020/21. However unlike the HEIP for Wales, after falling in 2021/22 it then increased again in 2022/23.

Northern Ireland

44. The Northern Ireland Statistics and Research Agency (NISRA) have produced an ‘Age Participation Index for Northern Ireland’ for 1998/99 to 2021/22. This is the number of Northern Irish domiciled young entrants (aged under 21) to full-time Higher Education in the UK or Republic of Ireland as a percentage of the 18-year-old population in Northern Ireland.

Future developments

45. Any feedback received will help direct how the HEIP could be improved. Developments will be informed by the discussions we have with those with an interest in this area, but possible developments include:

• Extending the coverage of HE activity by obtaining data on Welsh domiciled initial participants studying at HE level in Further Education Providers in England, Scotland and Northern Ireland.
• Investigating whether it would be possible to robustly report on a wider range of characteristics. For example ethnicity, disability and living in more deprived areas.
• Investigate whether there are possibilities to produce initial participation rates using a cohort based methodology as the DfE do for England. When the work on this HEIP was started in the Higher Education Funding Council (HEFCW) a cohort methodology was not feasible due to the lack of availability of longitudinal data. However the establishment of Medr may provide new opportunities.
• Look at how the measure could be adapted for the wider tertiary education sector instead of only focusing on HE.

Summary

This analysis builds on that previously published as part of the Welsh Government statistical article ‘outcomes for learners in post-16 education affected by the coronavirus (Covid-19) pandemic: August 2020 to July 2021‘. It aims to provide an up to date picture of progression from Year 11 to tertiary education.

The Year 11 cohorts in this analysis are based on all learners enrolled in Year 11 in maintained secondary, middle and special schools in Wales.

The tertiary education destinations considered in this analysis are publicly funded provision in maintained school sixth forms, further education colleges (excluding adult community learning) and work-based learning providers in Wales. Also included is post-16 learning in maintained special schools and the Welsh Government’s Jobs Growth Wales+ / Traineeships employability programmes.

The analysis does not include tertiary destinations in independent schools, other independent or specialist learning providers, tertiary education outside of Wales or any other post-16 EOTAS (Educated Other Than at School) provision.

Main points

• The provisional proportion of learners progressing from Year 11 to tertiary education was 90% in 2024/25, unchanged from the previous three years.
• The number of learners progressing has increased steadily since 2018/19.
• Of the learners that progressed from Year 11 to tertiary education:
  • An increasing proportion are progressing to further education colleges, with a corresponding decrease in those progressing to sixth forms.
  • There have been recent decreases in the proportion of learners studying at level 3 (including AS levels).
• There are differences in progression between different groups of learners. The proportion progressing was higher for learners who are:
  • Female
  • Living in the least deprived neighbourhoods
  • Not eligible for Free School Meals
  • Not accessing special educational needs or additional learning needs provision
  • From Asian, Asian British, Asian Welsh ethnic groups
  • Competent or fluent in their acquisition of English as an additional language
  • Attending Welsh medium schools in Year 11, or are fluent in Welsh.
• There was substantial variation in the type and level of tertiary education provision between different groups of learners and geographically.

You can find the full data in the PDF Sta/Medr/04/2025.

Quality and methodology

Data sources

The data sources used in this release are:

• Pupil Level Annual School Census (PLASC): an electronic collection of pupil and school level data provided to Welsh Government by all maintained sector primary, middle, secondary, nursery and special schools. The data collected is based on a January census date.
• Post-16 Data Collection: every autumn, all maintained schools with sixth forms are required to report all learning programmes and activities undertaken by pupils in the previous academic year.
• Lifelong Learning Wales Record (LLWR): data on further education, work-based learning and adult community learning. It’s collected on a ‘rolling’ basis throughout the year with regular statistical freezes. It is the official source of statistics in Wales for these sectors.
• School attendance weekly management information data collection: weekly data extracted directly from school management information systems started in Autumn 2020. The data is collected from all maintained nursery, primary, middle, secondary and special schools and any pupil referral units that have such management information systems and routinely record their information electronically.

Methodology

The main changes to the methodology used in the analysis previously published in the Welsh Government statistical article ‘outcomes for learners in post-16 education affected by the coronavirus (Covid-19) pandemic: August 2020 to July 2021‘ are:

• For academic years 2022/23 and previous, final datasets are used to identify tertiary education destinations rather than in-year datasets subject to further change.
• The Post-16 Data Collection is used for sixth form destinations as far as possible, providing information on the type of learning programme being studied. Weekly management information on school attendance is used for 2023/24 and 2024/25 as the Post-16 Data Collection is not yet available for these years.
• Post-16 learning destinations in maintained special schools are reported.

Year 11 cohorts are defined as any learner on roll in a maintained secondary, middle or special school in Wales on the PLASC census date.

For academic years 2017/18 to 2022/23, the Post-16 Data Collection and LLWR are used to identify tertiary education programmes of study that were active at any point during the year. Programmes included in this analysis include the following publicly funded learning:

• Any programme of study in school sixth forms.
• Further education undertaken in further education colleges.
• Work-based learning, either undertaken in further education colleges or private training providers including apprenticeships, Jobs Growth Wales+ and traineeships.

PLASC data is also used to identify any learners undertaking post-16 provision in maintained special schools.

For academic years 2023/24 and 2024/25, LLWR data is used as above. The Post-16 Data Collection is not currently available for these years, therefore weekly management information on school attendance is used to identify learners in school sixth forms and undertaking post-16 provision in maintained special schools. There are a number of limitations as a result of using this management information.

Based on comparisons for the 2021/22 and 2022/23 academic years, the weekly management information on school attendance over-estimates overall progression by around half a percentage point compared to the Post-16 Data Collection. It also causes over-estimates in the proportion of learners switching their tertiary education programme and leaving their tertiary education programme without completing it.

Of the learners who progressed, the proportions attending sixth forms are over-estimated by between 1.5 and 3 percentage points, with an under-estimate in proportions attending FE colleges.

Year 11 cohorts are then linked to the various datasets containing information on tertiary education – initially on the Unique Pupil Number and Unique Learner Numbers, with further linkage on unmatched records based on names and dates of birth.

Limitations

Figures for 2024/25 are provisional as they are based on in-year data. Tertiary programmes of study have been drawn from the January 2025 LLWR freeze. The data may not fully reflect all learning up to the point the freeze was taken and will be subject to change in the future. Data for the remainder of the academic year is not included, which may affect statistics for 2024/25. A relatively small number of learners may start their first tertiary programme of study after January, most commonly in work-based learning.

For 2024/25, weekly management information on school attendance is available up to the end of the winter term.

Figures for 2023/24 are also provisional as the Post-16 Data Collection will replace the weekly management information on school attendance once it is available.

The weekly management information on school attendance has not undergone the same level of quality assurance as accredited official statistics and the data may be subject to future revisions. It does not provide any information on the learner’s programme of study.

This analysis does not include tertiary education destinations outside of Wales, or any independent or specialist tertiary education. The proportion of learners progressing from Year 11 to tertiary education in local authorities that border England (Flintshire, Wrexham, Powys, Monmouthshire) is likely to be affected.

Definitions

The tertiary education destinations reported in this analysis are based on the first programme of study undertaken by the learner. When identifying a learner’s first programme the following programmes are prioritised over other FE programmes: AS level, A2 level, vocational, apprenticeships and Jobs Growth Wales+/traineeships. The most common programmes they’re prioritised over are GCSEs which are often taken as supplemental courses.

Only enrolment into the academic year immediately following Year 11 is included. Learners who started tertiary education in a later academic year are not included in this analysis.

Where weekly management information on school attendance is used, learners are considered to be still enrolled in tertiary education if they have an attendance or authorised absence record within 2 weeks of the following dates:

• 31May 2024 for the 2023/24 academic year, as the attendance data becomes more unreliable during the summer examination period.
• 20 December 2024 for the 2024/25 academic year, the final data of the winter term as data for only part of the academic year is available.

The school attendance dataset is taken directly from schools’ Management Information Systems. In some cases learners appear to be automatically rolled over from Year 11 into Year 12 when this was not the case. Because of this a learner is not listed as enrolled if they were:

• not listed as enrolled after 6 September,
• and had not attended the school or had a specific recognised absence before 6 September,
• and it was the same school that they were enrolled into in Year 11.

All analysis by characteristics are based on those recorded for the learner as part of their Year 11 PLASC record.

The deprivation decile of the learner’s home neighbourhood is based on the main index of the Welsh Index of Multiple Deprivation 2019.

‘AS level’ tertiary destinations here include both AS level and AS level equivalent programmes. AS level equivalent programmes consist of a mixture of AS levels and vocational qualifications, for example 2 AS levels and a BTEC National Certificate.

Rounding and suppression

All figures are rounded to the nearest 5. Numbers less than 5 are suppressed. Percentages are rounded to the nearest whole number. Percentages based on a denominator of less than 23 are suppressed.

Differences between values are calculated using unrounded values, so there may be small discrepancies when compared with the rounded figures.

Statement of compliance with the Code of Practice for Statistics

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to.

All of our statistics are produced and published in accordance with a number of statements and protocols to enhance trustworthiness, quality and value. These are set out in our Statement of Compliance with the Code of Practice for Statistics. You are welcome to contact us directly with any comments about how we meet these standards.

Alternatively, you can contact OSR by emailing [email protected] or via the OSR website.

Trustworthiness

These statistics have been published according to our Statement of Compliance with the Code of Practice for Statistics and pre-release access to official statistics policy.

Quality

The statistics in this release have largely been produced from final versions of recognised administrative data sources used to produce official statistics on education in Wales. These have been supplemented with weekly management information on school attendance to provide the most recent estimates of progression from Year 11 to tertiary education (for the 2023/24 and 2024/25 academic years). The limitations of using this management information have been explained and these estimates are marked as provisional.

Value

These official statistics in development aim to comply with the Code as far as possible. They have been produced rapidly in response to demands for better analysis on participation in tertiary education in Wales.

They are labelled as ‘official statistics in development’ to test whether they meet user needs and to reflect that the methodology is not fixed and could be further developed based on user feedback. We would welcome any comment on the usefulness of these statistics. Please contact [email protected].

Key points:

• There were 4,380 apprenticeship learning programmes started in 2023/24 Q4, compared with 5,715 starts in 2022/23 Q4.
• Foundation Apprenticeships and Higher Apprenticeships saw the largest falls compared to Q4 the previous year.
• Healthcare and Public Services apprenticeships were the most popular sector in 2023/24 Q4 with 2,005 programmes started. This accounted for 46% of all apprenticeship learning programmes started.
• 60% of apprenticeship learning programmes started were by female learners in Q4 2023/24, a five percentage point decrease from 2022/23 Q4.
• 41% of apprenticeship learning programmes started were by learners aged 25 to 39 in Q4 2023/24, compared to 42% in Q4 for the previous year.
• 14% of apprenticeship learning programmes started were by learners with ethnic minority backgrounds in Q4 2023/24, this is unchanged compared to Q4 for the previous year.
• 12% of apprenticeship learning programmes started in Q4 2023/24 were by learners identifying as having a disability and/or learning difficulty, compared to 11% in Q4 for the previous year.
• There have been 63,410 apprenticeship starts since Q4 2020/21, as part of progress towards Welsh Government’s target of 100,000 apprenticeships.
• The Programme for Government contained a target to create 125,000 all-age apprenticeships. During the Economy, Trade and Rural Affairs Committee meeting on 26 June 2024, the Cabinet Secretary for Economy, Energy and Welsh Language agreed a new target of 100,000 all-age apprenticeships to maintain the previous Senedd term’s target of 100,000.

Apprenticeship learning programmes started: interactive dashboard

Quality and Methodology

Provisional data

The statistics in this report are produced quarterly. Figures for the first three quarters in an academic year are provisional because they are based on earlier freezes of the Lifelong Learning Wales Record (LLWR). This data will continue to be updated until the final freeze in December after the end of the academic year.

The provisional figures for the year are finalised when quarter 4 (May to July) data are published in February/March each year, based on the December freeze.

Target measure starts

The statistics for the target measures use a more rigorous measure of apprenticeship programme starts than other statistics in this output. This measure takes account of early drop outs (within first 8 weeks) and transfers between apprenticeships.

Degree apprenticeships are now included in the current target measure. Degree apprenticeships in Wales provide the opportunity to combine working with part-time study at university. Data is sourced from the Higher Education Statistics Agency (HESA). Whilst statistics from HESA have been calculated to be as comparable as possible with statistics for other apprenticeship programmes sourced from the LLWR (for example, removing early drop outs), some methodological differences will remain. Unlike the LLWR, HESA data is only available annually and statistics for the latest available academic year will be included in every Q4 update.

More quality information

Other than the provisional data and the target measure, these statistics are produced in the same way as the statistics in the Further education, work-based learning and community learning annual reports. More information can be found in the quality section of those reports.

Statement of Compliance with the Code of Practice for Statistics

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to.

All of our statistics are produced and published in accordance with our Statement of Compliance with the Code of Practice for Statistics and other statistical policies.

These official statistics demonstrate the standards expected around trustworthiness, quality and public value in the following ways.

Trustworthiness

This is produced by professional statisticians complying to the Code of Practice for Statistics. Release dates are pre-announced, protocols around data confidentiality are followed.

Quality

The data is sourced from the Lifelong Learning Record Wales which is submitted by learning providers. This data is also used to determine funding for learning providers and is subject to audit.

When the data is submitted it must meet certain validation rules. When the statistics are being produced quality checks are undertaken by the statisticians.

Value

These statistics provide a quicker insight into the uptake of apprenticeships in Wales than the annually produced reports. They are used for monitoring and evaluating the sector. They report the progress against a target set by Welsh Government.

Contact: [email protected]

Date: Monday, 3 March 2025 – 14.00-15.00

Online webinar: view webinar slides

About REF 2029

The Research Excellence Framework (REF) is how the quality of research is assessed in higher education institutions in the UK. It’s a process of expert review, with panels of experts in individual academic subject areas assessing institutions’ research submissions. The next REF will report in 2029.

The Learned Society of Wales is the national academy for arts and sciences.

Our Fellowship brings together experts from across all academic fields and beyond. We use this collective knowledge to promote research, inspire learning, and provide independent policy advice.

Universities Wales  is a membership body representing the interests of Wales’ nine universities.

We develop higher education policy, deliver political and stakeholder engagement, and campaign on issues where our members have a shared interest.

Key Points

Students

• The proportion of students with a disability has increased every year from 2016/17 to 2022/23. The proportion has increased from 13% in 2016/17 to 17% in 2022/23.
• The proportion of students with an ethnic minority background has increased in every year from 2016/17 to 2022/23. The proportion has increased from 10% in 2016/17 to 14% in 2022/23.
• The majority of students are female. This size of this majority has increased from 55% in 2016/17 to 57% in 2022/23.

Staff

• The proportion of staff with a disability increased each year from 2016/17 to 2022/23. For academic staff the proportion increased from 4% to 7% and for non-academic staff the proportion increased from 6% to 10%.
• The proportion of staff with an ethnic minority background has increased each year from 2016/17 to 2022/23. For academic staff the proportion increased from 11% to 17% and for non-academic staff the proportion increased from 4% to 6%.
• The majority of academic staff are male, although the size of this majority has fallen slightly from 53% in 2016/17 to 52% in 2022/23. The majority of non-academic staff in this period were female. The size of this majority is 62% in 2022/23 which is the same as in 2016/17.

Methodology information

Data Sources

The data for this release come from the Higher Education Statistics Agency (HESA) Student and Staff records collected by Jisc.

In 2022/23 the student data was collected with the revised data collection delivered by the Data Futures programme. Jisc conducted a comprehensive quality assessment on the dataset and this is detailed in their 2022/23 student data quality report. A summary of the Student data collection process for 2022/23 covering timescales, validation and business rules and checking processes is included on the HESA website. Information about the earlier years of student data can also be found on the HESA website.

A summary of the Staff data collection process and associated quality rules can be found on the HESA Staff data collection page.

Coverage – Students

The statistics include students who are part of HESA’s higher education standard registration population. More information on this population can be found in the student definitions on the HESA website.

All uses of ‘students’ in this bulletin refer to ‘student enrolments’. This is a count of each enrolment for a course. In rare instances where a student was enrolled in two different courses in the same year, that student would be counted twice.

Coverage – Staff

These statistics include staff who are in the HESA staff contract population, which includes those individuals who have one or more contracts (which are not atypical) that are active on 1 December in the relevant HESA reporting period. Staff on a atypical contract are those members of staff whose contracts involve working arrangements that are not permanent, involve complex employment relationships and/or involve work away from the supervision of the normal work provider.

All figures on staff are the full-person equivalents (FPE). Individuals can hold more than one contract with a provider and each contract may involve more than one activity. In analyses staff counts have been divided amongst the activities in proportion to the declared full-time equivalent for each activity. This results in counts of FPE.

More information on this population can be found in the staff definitions on the HESA website.

Rounding Strategy

The data presented in this report follow the principles of the HESA Standard Rounding Methodology. The strategy is intended to prevent the disclosure of personal information about any individual.

This means that:

• Student and staff counts are rounded to the nearest multiple of 5.
• Percentages are calculated based on the unrounded counts and exclude unknowns. Percentages are not published if they are fractions of a small group of people (fewer than 22.5).
• Totals are also subject to this rounding methodology. As a result, the sum of numbers in each row or column may not match the total shown precisely.

Quality information

Statement of compliance with the Code of Practice for Statistics

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to.

All of our statistics are produced and published in accordance with a number of statements and protocols to enhance trustworthiness, quality and value. These are set out in Medr’s Statement of Compliance with the Code of Practice for Statistics.

These official statistics demonstrate the standards expected around trustworthiness, quality and value in the following ways.

Trustworthiness

These statistics have been published according to Medr’s Statement of Compliance and pre-release access to official statistics policy.

Quality and Value

This section provides a summary of information on this statistical release against five dimensions of quality: Relevance, Accuracy, Timeliness and Punctuality, Accessibility and Clarity, and Comparability and Coherence. These also cover the aspects of the Value pillar in the Code of Practice for Statistics.

1. Relevance
   The data in this report gives an overview of some equalities characteristics of students and staff in the higher education sector in Wales. This can be used to identify how effective particular policies related to equalities characteristics in higher education are, or to identify whether those with particular characteristics are under-represented in higher education.
   
2. Accuracy
   The HESA student and staff data are both censuses rather than surveys, as such there is no inaccuracy due to estimation. However, the accuracy of the data can be affected by errors in the data submitted. This is mitigated with a comprehensive set of quality checks, where potential issues are queried with providers so a suitable explanation for the data can be reached, or the data is corrected if necessary.
   The other factor affecting accuracy is where personal characteristics are returned as unknown. During the data collection process high levels of unknown values are queried with HE providers to minimise this where possible. The number of students and staff returned with unknown values are included in the spreadsheet and PowerBI dashboard so the scale of these are clear to users.
   
3. Timeliness and punctuality
   The data in this release refers to student and staff data up to the 2022/23 academic year. As the HESA student and staff data collections are retrospective collections there is a lag between the academic year and when the data can be made available. This lag has been extended for this publication due to two factors:
   * Delays to the student data collection as a result of the implementation of the Data Futures programme. This resulted in data being available later than usual.
   *The establishment of Medr. Prior to this release, these statistics were published by HEFCW. Unlike HEFCW, Medr is a producer of Official Statistics and setting up the appropriate processes for this, as well as the general establishment of Medr, contributed to an increased amount of time required to produce this analysis.
   The latter of these factors will not affect future versions of this release, and the delays associated with the Data Futures programme will reduce as the new data collection process becomes established.
   
4. Accessibility and clarity
   This statistical release was pre-announced on the Welsh Government’s statistical release calendar.
   This report is accompanied by a PowerBI dashboard and a spreadsheet which can both be accessed on the Medr website.
   
5. Comparability and coherence
   As the HESA student and staff data collections are UK-wide data collections, these statistics can be compared to similar analysis of equalities data for Higher Education providers across the UK which is available on the HESA Open Data website.

Introduction

This publication provides information about staff employed at higher education institutions in Wales as collected in the Higher Education Statistics Agency (HESA) Staff Record. Previous versions of this series were published by the Welsh Government and can be found on the Welsh Government website.

Main points

• Overall, there has been a 4% rise in the number of staff at Welsh universities from 21,815 in 2022/23 to 22,635 in 2023/24.
• Staff numbers were higher in 2023/24 than they were in 2022/23 for Cardiff University (10%), Wrexham University (9%), University of Wales Trinity Saint David (9%), Cardiff Metropolitan University (5%) and University of South Wales (4%).
• Staff numbers were lower in 2023/24 than they were in 2022/23 for Swansea University (1%), Aberystwyth University (4%) and Bangor University (8%).
• Cardiff University employed the most staff (7,760) followed by Swansea University (3,825).
• Wrexham University was the smallest university in terms of staff numbers, employing 585 staff in 2023/24.
• Staff are evenly split between academic and non-academic contracts across the sector, both accounting for 50% of all staff.
• 60% of academic contracts were full-time and 74% of non-academic contracts were full-time.
• Of those on non-academic contracts 5,130 (45%) were in professional or technical occupations, 3,745 (33%) were in administrative and secretarial occupations, 1,055 (9%) were managers, directors or senior officials and 735 (7%) were in elementary occupations. The definitions of these occupation groups come from the nine Major Groups of the Standard Occupational Classification (SOC) 2020.
• 56% of staff across the sector were female. However, only 49% of academic contracts were held by female staff. Two thirds of all part-time staff were female (65%).
• 9% of academic teaching staff reported that they were able to teach through Welsh and of those, 46% were known to be teaching in Welsh.

Staff numbers are calculated using the full-person equivalent for staff at 1 December of the reporting year. Staff on atypical contracts are not included. Atypical staff are those members of staff whose contracts involve working arrangements that are not permanent, involve complex employment relationships and/or involve work away from the supervision of the normal work provider.

Data

The data is available on StatsWales and HESA Open Data.

Quality and methodology information

Figures are based on the Higher Education Statistics Agency (HESA) Staff Record. For Welsh institutions submitting to the staff record data is required for all academic staff, and for non-academic staff if the contract is not atypical. Data also need not be returned for agency staff, self-employed staff, honorary contracts where the contract is not deemed to be a contract of employment and staff not employed by the HEI, but by a company consolidated into the HEI’s accounts.

Non-atypical staff full-person equivalent (FPE) counts are calculated on the basis of contract activities that were active on 1 December of the reporting period.  Atypical staff FPE counts are calculated on the basis of those individuals who have only atypical contracts that were active during the reporting period.

More information related to definitions used can be found at www.hesa.ac.uk/support/definitions/staff.

Statement of Compliance with the Code of Practice for Statistics

Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the Code of Practice for Statistics that all producers of official statistics should adhere to.

All of our statistics are produced and published in accordance with our Statement of Compliance with the Code of Practice for Statistics and other statistical policies.

These official statistics demonstrate the standards expected around trustworthiness, quality and public value in the following ways.

Trustworthiness

This is produced by professional statisticians complying to the Code of Practice for Statistics. Release dates are pre-announced, protocols around data confidentiality are followed.

Quality

The data is sourced from the HESA Staff Record which collects data from higher education providers across the UK. When the data is submitted it is checked against various quality rules with further quality checks undertaken by analysts producing analysis.

Value

These statistics provide information on the staff working at higher education institutions in Wales.

Contact

Email: [email protected]