Academic year 2023/24

Postgraduate initial teacher training targets

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Target number of trainees to start postgraduate initial teacher training (PGITT) in 2023/24, as estimated using the Teacher Workforce Model (TWM).

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The Teacher Workforce Model

What is the Teacher Workforce Model? 

From 2021/22 onward, the department’s annual postgraduate initial teacher training (PGITT) targets have been set using analysis from the Teacher Workforce Model (TWM) (opens in a new tab)

The Teacher Workforce Model is a national, stocks & flows model covering all state-funded primary (including maintained nurseries attached to schools) and secondary schools (including post-16 provision within such schools), academies, and free schools[1] in England.  

The model estimates the number of qualified teachers required by such schools in future (beyond 2021/22) for both primary and each secondary subject; and by considering the number of teachers that will leave or enter service in future, estimates the 2023/24 PGITT targets needed to supply sufficient numbers of teachers in 2024/25. 

The TWM is updated annually to use the latest available data. The school workforce census (SWC) is the key data source for the model, providing information on the composition of the current (2021/22) teacher workforce, teacher inflows/outflows, and the curriculum taught in secondary schools. 

The text below provides a high-level explanation of how PGITT targets have been calculated this year. However, we have also this year, for the first time, published the actual calculations used to derive these targets as part of our ‘Calculation of 2023 to 2024 PGITT targets’ Excel workbook. This may be found on the main webpage of the publication, alongside a methodological annex that provides further details on the calculations within the model.

How did the Teacher Workforce Model estimate PGITT targets for 2023/24? 

Firstly, the TWM estimated future teacher demand from a starting 2021/22 teacher stock (as measured by the SWC in November 2021) by considering projections of pupil numbers and by estimating the national pupil:teacher ratios needed to meet demand as pupil numbers change.

 The TWM then estimated the total number of teachers (in FTE, full time equivalent) needed to join the workforce in 2024/25 to fully meet this demand. The model focussed on entrants needed in 2024/25 as these would include the newly qualified entrants trained via PGITT in 2023/24.

 This 2024/25 ‘entrant need’ comprised three parts: 

  1. The number of leavers expected in 2024/25; which the model assumes must be replaced by other teachers entering the workforce in 2024/25. 
  2. The extra number of teachers needed in 2024/25 because of increases in teacher demand compared to 2023/24 due to pupil number growth. Note, if pupil numbers are forecast to fall between 2023/24 and 2024/25, the model assumes that some teachers could leave without being replaced, as teacher demand would fall in line with pupil numbers. 
  3. Finally, the model assesses whether we have under recruited in the two ITT cycles prior to 2023/24. The model does not only consider the impacts of ITT recruitment, it also considers the impacts of teacher retention and the recruitment of teachers by other routes (e.g. returners). If the model estimates an overall under-recruitment impact, the model corrects for this by assuming that additional teachers should be recruited to counteract it.  

The model takes this ‘entrant need’ and subtracts the number of entrants expected to join the workforce in 2024/25 through routes other than newly qualified entrants (NQEs) that have just completed PGITT. These include: returners, those teachers that are new to the state-funded schools sector, and those NQEs that gained qualified teacher status via an assessment only route or via undergraduate ITT. The residual figure is the number of NQEs needed (in FTE form) in 2024/25 having been trained via PGITT in 2023/24. 

Finally, the model upscales this number of 2024/25 NQEs into a 2023/24 PGITT target (in the form of trainee headcount) by: 

  • Applying an FTE to headcount conversion rate that is specific to NQEs, to reflect that not all NQEs enter service working full-time, and  
  • Applying ITT completion and post-ITT employment rates to reflect that not all individuals who commence ITT both complete it and gain employment as an NQE in state-funded schools in England within six months of completing training.  

Further information on the specific steps of this process are in the next section. 





[1]. Whilst special schools, pupil referral units, early years, independent schools, and further education/sixth-form colleges are considered as being out of scope of the TWM, the PGITT targets set using the model do make an indirect provision for teachers required in those sectors. 

Further methodological details and the drivers of 2023/24 PGITT targets

Estimating teacher demand

To estimate future teacher demand, the model considers the Department’s National Pupil Projections by school phase and uses assumptions on how national pupil:teacher ratios (PTRs) will rise and fall with projected pupil numbers based upon historical trends.

The model assumes that as pupil numbers grow, PTRs will grow in line with the historical relationship between pupil numbers and PTRs. Similarly, the model assumes that PTRs will fall if pupil numbers fall.

The demand for individual secondary subjects is based upon the current split of teaching time across subjects as recorded within the school workforce census.

Pupil projections are a key driver of the future demand for new teachers. All else being constant, if pupil numbers start to grow, or begin to grow at a faster rate year-on-year, then teacher numbers would also need to grow at a faster rate. Similarly, if pupil numbers were to fall, or to grow at a slower rate year-on-year, this would lead to a fall in the demand for new teachers. 

The impact of pupil projections upon 2023/24 PGITT targets (all else being equal) compared to 2022/23 is downward for both primary and secondary, despite pupil populations moving in opposite directions: 

  • The primary pupil population is forecast to fall by 2.0% in 2024/25, falling faster than in preceding years. If pupil numbers are falling more rapidly than in previous years, the demand for PGITT trainees will fall too.  
  • By contrast, the secondary pupil population is forecast to grow by 0.4% in 2024/25. However, this is a slower rate of growth than in preceding years, i.e. secondary pupil numbers are still growing, but are doing so more slowly than in the previous year.  
  • Whilst the model still assumes that the secondary workforce needs to grow with growing pupil numbers, it assumes it can grow less rapidly year-on-year because pupil numbers aren’t growing as quickly. In isolation of other drivers, this acts to reduce the demand for PGITT trainees in 2023/24. 

Estimating future teacher leaver numbers 

The TWM estimates the number of qualified teachers who will leave the workforce between 2021/22 and 2024/25 and assumes that all leavers will need to be replaced by teachers entering the workforce.

The TWM uses forecasts of leaver rates, as the absolute number of leavers will vary depending on the size of the workforce. Separate forecasts are produced for leavers aged over- and under-55 years old respectively, reflecting that the likelihood of teachers leaving service is driven by different factors for older and younger teachers. Separate forecasts are produced for primary and each individual secondary subject, reflecting differences in teacher retention levels between the teacher cohorts of different subjects. 

In 2020/21, there was an unprecedented decrease in the number of teachers leaving the state-funded sector, with leaver rates falling to the lowest level observed since the school workforce census started in 2010. This fall was likely because of the impact of COVID-19.

In 2021/22, the latest year for which data was available, both primary and secondary leaver rates increased slightly but remained below their pre-pandemic levels. This was likely to be a result of the continuing effects of the COVID-19 pandemic. 

As the effects of the pandemic subside, we expect leaver rates to become more comparable with pre-pandemic levels.  

To develop estimates of future leaver rates, we accounted for the latest (as of December 2022) economic forecasts from the OBR, and any other known factors that might impact on future teacher numbers not yet reflected in the baseline data. For example, we factored in the effect of teacher pay relative to pay in the wider economy and the impact on retention. 

The model also accounts for existing teachers that stay in service but reduce their working hours between years; the reduction in capacity is expressed in terms of FTE teachers that need to be replaced[1]. 

Estimating future entrant numbers, excluding PGITT 

The TWM estimates the number of qualified entrants who will enter the workforce between 2021/22 and 2024/25. As with leaver numbers, future entrant numbers are forecast in the form of FTE (full time equivalent) rather than headcount, reflecting differences in working pattern between different types of inflow/outflow.  

Both the number of returners (those teachers returning to the state-funded schools sector in England) and those who are new to the sector (including newly trained teachers who do not join the workforce immediately after ITT) are estimated using forecasts that consider the latest workforce and economic data as of December 2022. 

The model then estimates the number of teachers who will enter service having just gained qualified teacher status (QTS) via either the assessment only route or ITT using the latest ITT recruitment data. As some trainees will not complete ITT and immediately enter service after training, assumed ITT completion and post-ITT employment rates are applied to the numbers of trainees previously recruited to estimate the number of newly qualified entrants (NQEs).  

Adjustment to counter under-recruitment from previous ITT rounds 

One of the key drivers behind changes in 2023/24 PGITT targets for specific subjects is an adjustment included within the TWM to build in the estimated impact of recruitment being below target in the two ITT rounds prior to 2023/24. The process to assess whether to make an adjustment is shown below.  

A diagram to show the process to decide if an adjustment is required when calculating postgraduate ITT targets. 

The TWM uses ITT recruitment data, and ITT completion & post-ITT employment rates to estimate the number of NQEs entering the workforce having trained via PGITT (both mainstream PGITT and high potential ITT routes) from the two ITT cycles immediately before 2023/24, for primary and each secondary subject. 

The model uses these PGITT NQE figures for 2022/23 and 2023/24 respectively along with estimates for both the corresponding numbers of entrants into the stock via other routes (e.g. returners) and leavers, to estimate the size of the workforce in 2023/24. This 2023/24 stock size is then compared to the previously estimated teacher demand for that year to identify whether we have recruited the teachers we needed from the two PGITT rounds prior to 2023/24, accounting for both retention and wider recruitment. 

If this comparison shows that we have under recruited in specific subjects, then an adjustment is applied by increasing the 2023/24 PGITT target for those subjects. No adjustment is required for subjects where there is no under-recruitment impact. This action is taken as the recruitment impacts of the 2021/22 and 2022/23 PGITT cycles had not yet fed into the most recently published SWC from November 2021 - which we use as the baseline in the model. 

This year, the two ITT recruitment rounds that were relevant for developing 2023/24 PGITT targets were those for 2021/22 and 2022/23. Last year, the 2022/23 targets were developed by considering the workforce impacts resulting from the 2020/21 and 2021/22 ITT recruitment rounds.  

As reported within the ITT census publication, the number of ITT trainees recruited in 2020/21 was significantly boosted by the economic impacts of the COVID-19 pandemic. This led to 4,301 additional PGITT trainees being recruited in 2020/21 than in 2021/22. When developing the 2023/24 PGITT targets we assumed that the increased numbers of PGITT trainees recruited in 2020/21 had already entered the workforce as newly qualified entrants, and so were not captured within the under-recruitment adjustment calculation. By contrast, when developing the 2022/23 PGITT targets last year, we assumed that the 2020/21 trainees were yet to enter the workforce, and so they were captured within the under-recruitment adjustment calculation. 

As the two most recent ITT recruitment rounds (2021/22 and 2022/23) recruited fewer trainees than the two most recent rounds that we considered last year (2020/21 and 2021/22), all but one of the adjustments (primary) used within the Teacher Workforce Model last year were larger in scale this year.  

As a consequence, this adjustment is a key driver of the subject level changes in PGITT targets this year:  

  • An increased adjustment this year led to increased targets for business studies, chemistry, computing, design & technology, geography, modern languages, music, physics, and the group of subjects known as ‘others’. 
  • Similarly, several subjects that did not require an adjustment last year (when developing 2022/23 targets) did require one this year, leading to increased 2023/24 targets for: art & design, biology, English, mathematics, and religious education. 
  • Targets fell for three secondary subjects this year: classics, history, and physical education. In all three cases, no adjustment was necessary, either this year or last, with wider recruitment factors helping to reduce targets such as more favourable returner recruitment forecasts.  
  • The primary target is also lower this year, in part because recruitment and retention forecasts were more favourable this year than last. Whilst this led to a reduced need for ITT trainees to meet future demand, it also led to the removal of the adjustment that was used last year, helping to reduce targets further. 



[1]. Some existing teachers that stay in service increase their working hours between years. However, the model estimates and accounts for the net impact of teachers changing their working hours between years, which is a reduction in FTE teacher numbers. 

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