School staff recruitment during the pandemic

21st October 2021 by Timo Hannay [link]

When it comes to the impacts of the pandemic on schools, attention has understandably focused on infection rates, lost learning and mental health. But another, perhaps underappreciated effect has been the huge change in the patterns of school staff recruitment. Under various levels of lockdown, it has proved somewhere between difficult and impossible to either switch jobs or fill vacancies, resulting a highly disrupted school jobs market.

Last summer, together with the Gatsby Foundation and Teacher Tapp, we analysed the impacts of the first lockdown on recruitment of school teachers and technicians. This post and the accompanying paper – once again generously supported by the Gatsby Foundation – bring that picture up to date by analysing activity during the 2020-2021 academic year as well as the first month of the new academic year, September 2021. See also the related blog posts from Teacher Tapp and the Gatsby Foundation.

Although schools in England have now almost entirely reopened, we see ongoing disparities relative to pre-pandemic years. Specifically:

• Teacher recruitment activity at secondary schools in England was even lower in 2020-2021 than in 2019-2020, with a shortfall in online advertisements of more than 7,000 (-22%) compared to the last pre-pandemic year.
• The largest percentage declines were seen in English (-31%), Maths (-27%) and Science (-25%). These same subjects also showed the largest absolute decreases in numbers of advertisements (more than 4,000 in total).
• Technician recruitment showed a very different pattern that seems more in step with the rest of the economy. Strong growth since March 2021 resulted in more or less normal levels of recruitment for the 2020-2021 academic year as a whole. Recent hiring of technicians in subjects such as Computing or Design and Technology has been especially high, easily exceeding pre-pandemic levels.
• These trends – depressed teacher recruitment activity coupled with buoyant recruitment of technicians – have so far continued into the early part of the 2021-2022 academic year.
• In contrast to teachers, headteacher turnover did not decline in 2019-2020 or 2020-2021. However, the most recent academic year did show a small increase among secondary schools as well as considerable rises in out-of-season turnover during the winter and spring.
• The accompanying paper includes survey results from our collaborators at Teacher Tapp, which provide insights into the underlying thinking and expectations of teachers and school leaders.

 

Teacher turnover tumbles

Since 2017, SchoolDash has been indexing the websites of secondary schools, sixth-form colleges and further education (FE) colleges in England in order to track staff vacancies. Figure 1 shows the numbers of advertisements for teaching vacancies found during each week over the last three academic years: 2018-2019 (green line; the last full year before the pandemic), 2019-2020 (blue; the year during which COVID-19 struck), 2020-2021 (red; the school year just ended) and 2021-2022 (purple; the current school year).

Before the pandemic, the seasonality of teacher recruitment was highly predictable, with only minor variations such as differences in the date of the Easter holiday. The weekly pattern seen in 2018-2019, which rose to a peak in late April, was typical of pre-pandemic years. By comparison, 2019-2020 was relatively buoyant until the lockdown in March, when recruitment activity collapsed at a time of year when it would normally be rising strongly. During 2020-2021, activity did pick up throughout the spring, but from a low base and not to anything like pre-pandemic levels.

Looking at all years together, it is informative to see the cumulative data. Numbers of teacher advertisements in 2019-2020 were about 4,500 (14%) lower than in 2018-2019, but in 2020-2021 they were lower still – more than 7,000 (22%) below a 'normal' year. So far, activity in 2021-2022 is much closer to 2020-2021 (ie, the worst-affected year) than to pre-pandemic years. While these patterns are evident across all subjects, recent declines in Languages and Maths seem to have been particularly large compared to those at the start of the pandemic.

(Use the menus below to view weekly or cumulative data, and to select different subject areas. Click on the figure legend to hide or view individual academic years. Hover over the lines to see corresponding data values.)

Figure 2 makes this even clearer by showing the difference in the number of advertisements compared to the last pre-pandemic year in 2018-2019. Looking at the cumulative data for all subjects, we can see that until March 2020, recruiting activity in 2019-2020 (blue line) was ahead of the previous year by more than 1,000 advertisements, but then fell off a proverbial cliff at the start of the first lockdown. In contrast, recruiting during 2020-2021 (red) has been in relative decline all year, only flattening out in May, when most schools had stopped hiring teachers anyway. The net result is a much bigger cumulative decline in 2020-2021 than in 2019-2020. So far, the new 2021-2022 academic year (purple) is on a very similar (ie, depressed) track to the year just gone even though most educational and social restrictions have now been lifted.

Note that there is considerable variation by subject: the cumulative net effect for Arts showed little year-on-year variation, while the gap in Maths increased greatly.

(Use the menus below to view weekly or cumulative, and to select different subject areas. Click on the figure legend to hide or view individual academic years. Hover over the lines to see corresponding data values.)

Figure 3 shows these subject-specific variations compared to a 'normal' year, both in terms of percentage changes and absolute numbers of advertisements. In both cases, English, Maths and Science showed the biggest falls in 2020-2021

(Use the menu below to switch between percentages and numbers of advertisements. Click on the figure legend to hide or view individual academic years. Hover over the columns to see corresponding data values.)

If certain subjects showed larger declines than others, what about certain schools? Or were the effect spread more or less evenly across the system? Figure 4 sheds some light on this by showing the distribution of schools by total number of teacher advertisements issued in each academic year.

Looking by number of schools, we can see that the pandemic years of 2019-2020 and 2020-2021 tended to have fewer schools with high numbers of advertisements (12 or more), but more with lower numbers of advertisements (6 or fewer). A very similar pattern emerges when looking by proportion of schools.

It is also informative to note that the total numbers of schools for which at least one advertisement was found did not change as much as overall recruiting activity, declining from 3,535 in 2018-2019 to 3,497 (-1%) in 2019-2020 and 3,370 (-5%) in 2020-2021. Taken together, these observations seem consistent with the idea that the decline in activity was relatively evenly spread across a large number of schools rather than focused on a small subset.

(Use the menu below to switch between number of schools and proportion of schools. Click on the figure legend to turn individual years on or off. Hover over the graph to see corresponding values.)

Figure 5 shows the proportion of advertisements than mention newly qualified teachers (NQTs), which almost always means that the vacancy is either targeted at NQTs or at least suitable for them. The long-term mean is about 2.7%, though it can vary a lot from month to month, especially during the low seasons in December and August, when sample sizes are small.

Overall, there was little year-on-year in the proportions of advertisements mentioning of NQTs, indicating that opportunities for NQTs declined roughly in line with the overall market.

We have previously reported that advertisements for specialist, as opposed to generalist, science teachers are much more common among certain types of schools and locations. Despite other disruptions, these disparities have continued throughout the pandemic and into the current academic year. Figure 6 shows the proportions of science teacher advertisements that included mention of a particular specialty (biology, chemistry, physics or psychology). This varies greatly by deprivation level, Ofsted rating and region. Predictably, it also depends heavily on single-sex, grammar, and sixth-form status.

(Use the menu below to explore other school categorisations. Hover over the columns to see underlying values and sample sizes. Click on the figure legend to hide or display the different years.)

 

Technicians turn the tide

While less numerous that teachers, technicians represent another essential aspect of secondary school staffing. Their hiring displays a different seasonality, as shown in Figure 7. Once again, 2018-2019 (green line) represents a relatively 'normal' pre-pandemic year, with a peak in June for all subjects that reached about 140 new positions each week. (There was an even higher spike in September 2018, but this appears to be anomalous as we haven't seen it in any other year.) In 2019-2020 (blue), activity was greatly reduced, with no summer peak. But in 2020-2021 (red), technician recruitment bounced back strongly to levels even higher than those seen before the pandemic, especially during the spring and early summer.

This can be seen even more clearly in the cumulative data for all subjects and all years. Aggregate technician hiring returned to near normal levels by the end of the 2020-2021 academic year despite earlier shortfalls. These higher-than-usual levels of activity have also carried on into the current 2021-2022 academic year (purple). Note that this picture varies by subject, with technology rebounding particularly strongly.

(Use the menus below to view weekly or cumulative data, and to select different subject areas. Click on the figure legend to hide or view individual academic years. Hover over the lines to see corresponding data values.)

Figure 8 shows the difference in the number of advertisements relative to the last pre-pandemic year in 2018-2019. The cumulative data for all subjects highlights the stark difference between 2019-2020 (blue line), which ended with a deficit of more than 800 advertisements, and 2020-2021 (red), which came within a whisker of reaching normal levels across the year as a whole. Though it's still early days, 2021-2022 (purple) is so far on track to be an exceptionally active year for technician recruitment, with technology positions leading the pack.

(Use the menus below to view weekly or cumulative, and to select different subject areas. Click on the figure legend to hide or view individual academic years. Hover over the lines to see corresponding data values.)

Figure 9 shows variations compared to pre-pandemic level for each subject, both in terms of percentage changes and changes in the number of advertisements. On both measures, Science showed the biggest falls in recruiting activity during the pandemic to date, while, as noted above, technology showed a net increase in 2020-2021.

(Use the menu below to switch between percentages and numbers of advertisements. Click on the figure legend to hide or view individual academic years. Hover over the columns to see corresponding data values.)

 

Headhunters

Unlike subject teachers, headteacher changes are best tracked using data from the Department for Education (DfE), which publishes the names of school leaders, updating them when informed of new appointments. (Note that unlike vacancy advertisements, this is not a leading indicator of a new appointment but, if anything, a lagging one.)

Figure 10 shows the number of headteacher changes for each month over the last three academic years, and for the early part of the current one. By far the biggest annual peak is in September, with January a distant second. Overall headteacher turnover has so far not changed much during the pandemic, including in September 2021. However, this hides some underlying variations. In particular, out-of-season changes in January and (arguably) April were higher than usual in 2021. Also, turnover in 2020-2021 rose among secondary schools while falling among primary schools.

(Use the menu below to switch between all schools, primary schools and secondary schools. Click on the figure legend to hide or view individual academic years. Hover over the columns to see corresponding data values.)

 

Tumultuous times

Even as schools return to something approaching operational normality, we continue to see post-pandemic effects reverberating through the recruitment market. While the broader labour market experiences higher-than-usual turnover (sometimes referred to as the Great Resignation), teacher turnover currently remains depressed, at least for now. This is consistent with the results of recent more general vacancy surveys. Lower teacher turnover is probably a good thing for most schools, especially those that normally struggle to recruit, but creates potential challenges for newly qualified teachers or those who want to change jobs.

In contrast, technicians appear to be following a pattern more like that of the rest of the economy, with big increases in hiring. This is presumably either because existing staff have resigned to pursue other opportunities, or because they were laid off during lockdown and now need to be rehired. We will continue to monitor this evolving situation as the 'new normal' in school staffing takes shape.

For further details, see our accompanying paper as well as related blog posts from Teacher Tapp and the Gatsby Foundation. A more general analysis of school recruiting can be found in our Jobs section and the very latest data are available through our premium service, SchoolDash Insights.

We welcome your comments: [email protected]

How girls and boys differ in STEM subject choice

11th October 2021 by Timo Hannay [link]

(Note: This has been cross-posted by Maths4Girls.)

Gender balance in STEM (science, technology, engineering and maths) is a perennial topic of concern and campaigning. For our part, SchoolDash is proud to be associated with Ada Lovelace Day, the global celebration of women in STEM, which this year kicks off on 12th October, and with Maths4Girls, an initiative that introduces budding British mathematicians to role models with whom they can identify.

This post digs into some of the numbers that explain why such initiatives are necessary and the nature of the problem they're seeking to address. Specifically, we're going to look at gender differences in STEM subject choice at A-level using data from the Department for Education (DfE) that covers the cohorts in England that sat their A-levels in 2018 and 2019 (ie, before COVID-19 struck).

In summary, we find that:

• Computing shows the most skewed gender ratio, with only 3 girls for every 20 boys, but Maths and Physics show the biggest notional shortfalls, with over 20,000 girls a year 'missing' in each subject. If anything, these gender gaps widened slightly between 2018 and 2019, particularly in Maths
• Despite this, Maths remains the second most popular STEM subject among girls (after Biology), with 17% of female A-level students taking it in 2019. This compares to only 4% for Physics
• Gender disparities exist in all parts of England and at every kind of school. Indeed, they tend to be bigger at schools with low levels of disadvantage, where STEM subjects are more popular across the board but gender differences tend to be even more pronounced
• Single-sex and independent schools show somewhat less gender-stereotyped subject choice, but it's unclear how much of this is down to the schools themselves rather than simply the characteristics of their intake
• On a more positive note, we see relatively little evidence for gender-specific cohort effects in which very small numbers of girls or boys wishing to take a subject at a particular school result in none of them doing so

For more on this topic, including school-level information, see also the data and research assembled by the Advanced Mathematics Support Programme. They have a useful factsheet for teachers too.

For more on our analysis, read on...

The data presented here use two distinct and complementary ways of measuring differences between girls and boys in A-level subject choice:

• Percentage point gap: If a subject is taken by, say, 20% of boys but only 10% of girls then we can say that there is a 10 percentage point gap. One benefit of this approach is that it provides an indicator of roughly how many students we're talking about (on the basis that 1 percentage point corresponds to 1,400-1,500 girls or 1,100-1,200 boys each year).
• Gender ratio: This shows how many girls take a subject for each boy that does so. It is important to understand because sometimes small percentage-point gaps can hide very large gender disparities. For example, a subject taken by 1% of boys and 0.1% of girls would have a gap of less than one percentage point but a huge boy:girl gender ratio of 10:1.

 

Mind the gap

We will start by looking at percentage-point gender gaps. Figure 1 shows these for all six A-level STEM subjects covered by the DfE data. They come from exams sat by students in England in 2018 (blue columns) and 2019 (red).

Biology has more girls than boys, while Chemistry is almost balanced. Other STEM subjects show relative shortfalls for girls, with Maths having the biggest gap of all. Note that this is in part because overall participation rates in Maths are relatively high (roughly 17% of girls and 35% of boys in 2019). In four of the six subjects, percentage-point gender gaps increased between 2018 and 2019.

(Hover over the columns to see underlying values and cohort sizes. Click on the figure legend to hide or display years.)

Figure 2 breaks these national results down by school location and type. Looking at Maths participation by region, disparities are present everywhere, though the Midlands and the East of England have larger gaps than most. So does London, but note that overall Maths participation there is high (22% of girls and 40% of boys in 2019).

Some outcomes are a slightly counterintuitive. For example, schools with lower deprivation (as indicated by the proportion of students eligible for free school meals) have larger gender gaps. So do those with higher Ofsted ratings or greater proportions of students with English as an additional language (EAL; usually a positive indicator of educational outcomes). Once again, this is largely because they have higher overall entry rates in these subjects. As we shall see below, these don't always translate into worse gender ratios.

Single-sex schools, which are often considered to reduce gender stereotyping among teenagers, have somewhat lower disparities in Biology and Computing, but not in Maths or Physics. Note, however, that overall entry rates in Maths and Physics are higher at single-sex schools, so it is also important to look at gender ratios (see below). Much the same is true of grammar schools, which overlap considerably with single-sex schools.

(Use the menus below to explore other school categorisations and STEM subjects. Hover over the columns to see underlying values and sample sizes. Click on the figure legend to hide or display the different years.)

Figure 3 shows the same 2019 data, but by local authority. This uses a cartogram in which each area is scaled according to its pupil population, making it easier to see small, densely populated urban locations. Red areas have low levels of female participation, blue areas have high levels and maroon ones are roughly in balance. Predictably, these patterns are very different by subject: compare Biology, Chemistry, Computing, Further Maths, Maths and Physics.

Note that sometimes a large imbalance, or even gender parity, is simply a consequence of low overall entry rates. To give an extreme example of the latter, Knowsley in the North West achieved a perfect balance by reporting no girls or boys taking A-level Maths in 2019.

(Explore further using the menu below. Hover over the map to see corresponding data and cohort sizes for each region.)

 

The results shown above come from state schools (which are much easier to slice and dice by type because data about them are plentiful). But independent schools are a significant part of the mix too. As shown in Figure 4, they tend to do better at getting girls into STEM subjects, notably in Maths and Computing, where the gender gaps are considerably smaller than at state schools.

Of course, this doesn't demonstrate that independent schools themselves are causing the effect since the characteristics of their intakes are very different to state schools. Indeed, one could even argue that if girls who are attracted to STEM subjects are disproportionately likely to attend an independent school then this would tend to increase gender gaps in the state sector. The data shown here demonstrate that there is a difference between the sectors, but not, unfortunately, anything about its underlying causes.

(Hover over the columns to see underlying values and cohort sizes. Click on the figure legend to hide or display individual sectors.)

 

Rational numbers

This section provides roughly the same analysis as above, but using gender ratios. These are presented as girl:boy, so 0.5 means half as many girls as boys, while 2.0 means twice as many girls.

Figure 5 shows a summary by subject. In this case, Computing shows the greatest imbalance with a national ratio of 0.15 in 2019 (ie, 3 girls for every 20 boys). Maths has a ratio of about 0.6 (3 girls for every 5 boys), while Biology shows the inverse, with a ratio of 1.7 (roughly 5 girls for every 3 boys).

Here, too, disparities in Maths were evident in every region, as shown in Figure 6. Once again, the Midlands and the East of England showed the largest disparities. On this measure, London does relatively well.

Consistent with the analysis of percentage-point gaps described above, schools with lower deprivation tend to have worse gender ratios for Maths. But the same is not true of schools with higher Ofsted ratings or greater proportions of EAL students, which have more balanced gender ratios despite having large percentage-point gaps. The same is true of single-sex schools and grammar schools, which have more balanced gender ratios in Maths and the other STEM subjects covered here.

It is interesting to observe that single-sex schools also have different proportions of female and male teachers. As a whole, 64% of teachers in single-sex schools are female, which is very close to the proportion for mixed-sex schools (62%). But at girls' schools fully 75% of teachers are female while at boys' schools only 47% are. How these proportions vary by subject, and whether or not they have any direct effect on A-level subject choice, is unfortunately not possible to determine using the public data currently available.

(Use the menus below to explore other school categorisations and STEM subjects.)

Figure 7 shows gender ratio data by local authority area. The picture once again varies by subject: compare Biology, Chemistry, Computing, Further Maths, Maths and Physics. Here too, look out for extreme effects caused by small numbers of students. For example, the very girl-heavy ratio achieved for Maths by Hartlepool in the North East is based on just 28 students (19 girls and 9 boys).

(Use the menu below to explore other subjects; hover over each local authority area to see corresponding data values and cohort sizes.)

 

Figure 8 compares the gender ratios at state schools that we have analysed above with those at independent schools. For every subject shown, gender ratios are more balanced (ie, closer to a value of 1) among independent schools. As already pointed out, we can't tell from these data alone how much of this is due to something the schools themselves are doing and how much is simply a consequence of their distinctive intake.

(Hover over the columns to see underlying values and cohort sizes. Click on the figure legend to hide or display individual sectors.)

 

All together now

Figure 9 summarises the relationship between the gender gaps (vertical axis) and gender ratios (horizontal axis) across all six subjects. The size of each dot represents the total numbers of students taking the subject (hover over them to see corresponding data values).

Computing shows the greatest skew towards boys, but is still a niche A-level subject, so the absolute number of 'missing' girls is relatively modest (about 9,000). Maths and Physics show somewhat less extreme gender ratios, but overall entry rates are higher, so the notional shortfalls in numbers of girls are larger (around 20,000-25,000 apiece). Conversely, Biology is short of boys to the tune of about 7,000. Chemistry – sometimes thought of as a Cinderella science caught between the profundity of Physics and the self-knowledge of Biology – is admirably well balanced on both measures. (In fact, Chemistry has a slightly higher participation rate among boys, but a gender ratio in favour of girls; this is because the whole A-level cohort contains more girls than boys.)

 

Birds of a feather?

Finally, we will look for signs of cohort-size effects. These can occur when very small numbers of students are interested in taking a subject, sometimes resulting in none of them doing so. For example, if only one or two girls at a particular school want to take Physics A-level then they may be dissuaded from doing so in order not to feel unusual or isolated. Overall, we don't see particularly strong evidence for this in the data analysed here, though that is far from the same as demonstrating that it doesn't happen.

For example, in Physics, the numbers of girls choosing the subject (red columns) are generally low (ie, shifted towards the left of the figure), but there are no obvious shortfalls in the numbers of schools reporting just one or two girls – the curve rises smoothly as it approaches the vertical axis. There is such a shortfall for boys (blue columns) – the curve dips near the axis – but since they represent the majority of students, this is presumably due to the fact that schools with very few boys taking A-level Physics will often not be in a position to offer it at all.

Maths arguably shows a hint of a shortfall among schools with low numbers of girls, though this may also be due to low total numbers of students. Further Maths and Computing do not show obvious shortfalls, but the numbers of girls here are so small that one might argue these subjects as a whole are suffering from cohort-size effects. Chemistry shows shortfalls for both sexes – which is understandable given the roughly even gender balance in that subject. Biology shows more or less the reverse behaviour to Maths, which makes sense given that it has the inverse gender ratio.

 

All askew

There is no reason to believe that all A-level subjects should attract equal proportions of boys and girls – and they don't (see this recent analysis by FFT Education Datalab for the broader picture). But the gender balance in many STEM subjects is so far out of kilter that at the very least it deserves serious attention. The potential risk is not only that girls (or boys) with genuine interest and aptitude are put off from subjects in which they could excel, serious though that may be. It is also that the analysts, engineers and technologists who shape our collective future will not be representative of the society they serve. While not the only kind of bias that ought to concern us, gender is surely one aspect in which we can still strike a much better balance.