Further Education Workforce Data for England

Further Education workforce data for England

Analysis of the 2013-2014 Staff Individualised Record (SIR) data

RPT-SIR22-130415-STCPage 1 of 7208/04/2015

Contents

Foreword

Executive Summary

1.Introduction

2.Our approach to the analysis

2.1The data

2.2Data processing and definitions

3.Profile of the English FE workforce, 2013-14

3.1Occupation types

3.2Contract types

3.3Staff turnover

3.4Gender

3.5Age

3.6Ethnicity

3.7Sexual orientation

3.8Disability

3.9Region

3.10Annual pay

4.Profile of teaching staff, 2013-14

4.1Overview of characteristics in comparison to all FE staff

4.2Overview of characteristics in comparison to the school workforce in England

4.3Subjects taught by FE teaching staff

4.3.1Subjects by college and teacher numbers

4.3.2Number of teachers per college offering each subject

4.3.3Turnover rates by subject

5.Differences between General Further Education and other FE colleges

5.1All staff

5.1.1Occupation types

5.1.2Gender

5.1.3Age

5.1.4Staff turnover

5.2Teaching staff

6Trends in the General Further Education College workforce

6.1All GFEC staff

6.1.1Occupation type

6.1.2Gender

6.1.3Age

6.1.4Ethnicity

6.1.5Staff turnover

6.1.6Pay

6.2Teaching staff

7Inferences on the total workforce population

7.1Representativeness of the SIR 22 sample

7.2Estimates of the total workforce population

8Conclusions

Annex 1: Additional tables

Annex 2: Representativeness of the SIR 22 sample

Annex 3: Further Education colleges in England

Foreword

A college’s workforce is fundamental to how learners experience the college, how the local community see the college, how employers and other stakeholders perceive the college and ultimately fundamental to the college’s culture. As Governors, we’re not in the college every day, but we still need to understand the profile and characteristics of staff working in our college, and what that might mean for the college in the present and the future.

This report shows me what the college workforce looks like across the country, and some of the trends. Charts and tables showing me the national and regional picture on staffing help me and my governor colleagues to better understand how our college compares against others. This report prompts us to consider and discuss whether our colleges have the right skills for the future; do we have the right profile of staff in the right roles to deliver our strategic ambitions? If we are downsizing or expanding, are we ensuring we are continuing to invest in the right profile of staff?

Are we creating new roles fit for the future? How is the shape of our college workforce changing to manage the challenges we are facing across the sector?

It doesn’t surprise me to see that teachers are now making up more of the workforce in colleges, as this report shows. While pay is slightly higher than last year, staff numbers in general are down. Although not much has changed since last year, there are some areas in the detail that I’m keen to compare to our college.

There are more teachers on part-time contracts, and the age of new teachers is getting older, along with the rest of the workforce. Staff aged over 60 are a growing group. This report makes me want to see what the situation is in my college and in others.

Sample sizes are down on last year, with fewer colleges making returns to the Staff Individualised Record. Smaller sample sizes make the data less reliable, and I hope we’ll see more colleges using the data and making returns next year.

The data in this report is invaluable, not just for governors and senior managers in colleges, but for government departments making decisions about how to support the maths and English workforce in future, and for membership bodies like the Association of Colleges who lobby on our behalf. I would urge every college to complete it next year, so that together we can get the best available data on the workforce across the sector.

The Education and Training Foundation is changing the way they collect workforce data over the next eighteen months, and are keen to make sure the data is as useful as possible to colleges. I want to make sure our college data is there, so I and other governors will be able to see a dashboard of trends when it comes out from the Foundation. I’m asking you to join me and make sure your college data is there too.

Carol Jones
Chair of the Corporation, Stoke on Trent College
National Leader in Governance, Education and Training Foundation and Association of Colleges

Executive Summary

Frontier Economics was commissioned by the Education and Training Foundation to carry out an analysis of information on the Further Education (FE) workforce in England from the 2013-14 Staff Individualised Record (SIR) dataset. The SIR dataset holds information on standard contracts of employment between FE colleges and their members of staff, including information on the contract and on the demographic characteristics of the employee.

This report provides a descriptive account of the staff working in English FE colleges in 2013-14, and draws out comparisons of the workforce across different types of FE college and with the results from 2012-13.[1] Comparisons across college types focus on differences between General FE Colleges (GFECs, which account for the large majority of the sector in terms of number of providers and number of students), and all other institutions.[2]

In practice, our ability to draw comparisons over time and across college types was affected by data availability. SIR data are supplied by FE colleges for each academic year on a voluntary basis, and response rates have been declining over time. In 2013-14, 84 colleges, approximately one quarter of all FE colleges in England, supplied up-to-date information representing 61,524 employment contracts. This compares with around one-third of colleges responding in 2012-13.

The decline in the response rate compared to 2012-13 was particularly marked for Sixth Form colleges (SFCs): less than 15% of all SFCs in England returned information as part of the 2013-14 SIR collection. This low response rate limited the scope to use SIR data to describe the characteristics of SFCs in isolation, and also meant we were most confident only to draw comparisons between 2012-13 and 2013-14 for the GFECs rather than across the whole FE sector.

Despite the limitations of the data our results provide an accurate picture of the characteristics of the FE workforce. A statistical analysis suggests that colleges in SIR are reasonably representative of the characteristics of the wider population of FE colleges in England.

The key findings from our analysis of 2013-14 SIR data provided by all college types are the following:

• Teachers represent nearly half of the FE workforce, making up the largest occupational group in FE. After teaching staff, the next largest occupational groups are service staff; word processing, clerical, and secretarial staff; administrative and professional staff; technical staff; managers; and assessors and verifiers.
• Over half (58%) of contracts in FE are part-time. Part-time contracts are considerably more frequent than in the general UK workforce where only one in four people works part-time.
• 63% of FE staff are women, a larger proportion than the general UK workforce, but a smaller proportion than the school workforce.
• The median pay band for full-time staff across all occupational categories is £25,000 to £25,999.
• Our analysis of contracts starting and ending in 2013-14 suggests that the size of the FE workforce is declining, with a net employment change[3] of -1.7%. This change is less marked for teachers (-0.7%) and more marked for other (non-senior) managers (-5.5%).
• The availability of information on the ethnicity of FE staff has increased compared to 2012-13. Ethnicity was reported for 86% of contracts in 2013-14, a sizeable increase compared to 76% in 2012-13.
• The most common subject areas, taught in at least 90% of FE colleges in our sample, are: Business Administration, Management, and Professional; Health, Social Care and Public Services; Hospitality, Sports, Leisure and Travel; English, Languages and Communication; Science and Mathematics; and Visual and Performing Arts and Media.

Our comparative analysis of GFECs and other FE colleges shows that:

• A “typical” GFEC holds 650 contracts with members of staff (402 in FTE terms), of which 315 are teachers.
• It provides courses in 13 distinct subject areas, and employs 41 English, Languages and Communication and 24 Science and Mathematics teachers.
• GFECs tend to be larger than other colleges: they offer more subjects and employ more teachers per subject offered.
• Staff employed in GFECs tend to be older, with a median age of 50 compared to 48 in other colleges.
• There is little difference between GFECs and other colleges in terms of other employee characteristics.

Comparing information returned by GFECs in 2012-13 and 2013-14, we found that:

• As a proportion of FTE staff, teachers have increased from 43.5% to 44.1%, while the proportion of technical staff and of other managers has decreased (from 6.9% to 6.2% and from 8.9% to 7.6%, respectively).
• The mean age of GFEC staff increased from 44 years in 2012-13 to 45 year in 2013-14. The median age for contracts starting in 2013-14 is 42, considerably higher than the median age for teaching contracts with earlier start dates, 39.
• The share of women in FTE staff has increased slightly, from 61.8% to 62.1%. The increase is larger for teachers, where the share of female staff has gone up from 54.6% to 55.9%.
• The median annual pay for full-time teaching staff has gone up by one pay band: from £30,000 - £30,999 in 2012-13 to £31,000 - £31,999 in 2013-14.

As in the 2012-13 report we also provide indicative estimates of the total size of the FE workforce. This estimation remains a challenging task, particularly given the decline in the response rate. However, statistical comparison of the sample of colleges in SIR against the overall population of FE colleges suggests that scaling up the SIR data to match the number of colleges overall gives a reasonable way to estimate the size of the overall workforce in England.

Based on this approach, we estimate the FE workforce to consist of approximately 250,000 contracts (155,000 FTEs), of which approximately 123,000 (71,000 FTE) are teachers.[4]

1. Introduction

This report presents the findings from an analysis of workforce data from the Staff Individualised Record (SIR) dataset for Further Education (FE) colleges in England for 2013-2014.

This is the eleventh publication in the series of annual SIR reports on the English FE workforce, and the second to be produced by the Education and Training Foundation.

There are four types of colleges included in our analysis: general FE (including tertiary education) colleges (GFECs), sixth form colleges (SFCs), special colleges (Agriculture and Horticulture Colleges; Performing Arts Colleges) and specialist designated colleges (SDCs).[5] We do not include national specialist colleges (NSCs), which focus specifically on providing young people with learning difficulties or disabilities with valuable skills for living independently. NSCs tend to be much smaller than other colleges in the sector, and none made returns to the SIR. Throughout the report, we have used information from the Association of Colleges (AoC), whose members are GFECs, SFCs, special colleges and SDCs, to help validate our data.

The data contain information on all staff – teaching and not teaching – covering staff demographics (such as age, gender, ethnicity, disability and sexual orientation), staff occupation and pay, subjects taught and geographical location.

This report provides a descriptive account of the staff working in colleges in 2013-2014 covering all aspects of the data (demographics, pay, subjects taught, etc.).

The vast majority of FE providers in England (and of the SIR sample) are GFECs. However, it is important to recognise that other types of FE institutions may have different characteristics. The report therefore also makes explicit comparisons (as far as possible) between the characteristics of staff in GFECs and other types of college to understand better any differences between them.

The report also comments on trends over time, by comparing the findings from the 2013-14 data with those in the 2012-13 report. Since this report follows the same analytical methodology used in the previous report,[6] we are able to make more direct comparisons of changes over time than has been possible previously. To make as like-for-like a comparison as possible, we focus on comparisons within GFECs, which make up the vast majority of responses in both years.

The rest of the report is organised as follows:

• Section 2 discusses our overall approach to the work including methodology and a detailed description of the data processing we have carried out.
• Section 3 contains the main description of the FE workforce in England in 2013-14.
• Section 4 describes the characteristics of the teaching workforce in English FE in 2013-14.
• Section 5 contains our analysis comparing GFECs to other types of FE institutions.
• Section 6 investigates trends in the characteristics of the FE workforce (within GFECs) over time, based on comparing 2013-14 results with those from 2012-13.
• Section 7 contains our estimates of the total workforce numbers (derived by scaling up the up the SIR 22 data).
• Section 8 contains our conclusions.

1. Our approach to the analysis
2. The data

The SIR data for 2013-14 are based on responses from 84 FE colleges in England, which equates to approximately one-quarter of colleges. As shown in Table 1, on aggregate the colleges supplying 2013-14 data make up around a quarter of one measure of the college population in terms of number of colleges, total expenditure, full-time staff and number of students. This is reassuring – if the sample of colleges were very unrepresentative of the overall college population, we might expect to see these proportions vary across different measures. We provide more comparisons of our sample to wider population measures of English FE colleges in Section 7 and Annex 3.

One way in which we know our sample of colleges is somewhat different from the wider population is college type (see Table 2). In particular, our sample contains far fewer SFCs relative to wider college population measures, reflecting a lower tendency for SFCs to complete the SIR return. We return to this in more detail in Section 7 in terms of our ability to make inference about the total FE workforce from the SIR sample. This relatively poor response rate from SFCs also informs our decision to focus our comparative analysis between SIR 22 and SIR 21 data (see Section 6) on GFECs only.

The 2013-2014 SIR dataset contains 61,524 records, each relating to a standard contract of employment between a college and an individual. In some cases, two or more distinct contracts may in fact relate to the same individual. However, it is not possible to identify where this is the case within SIR. For ease of presentation, throughout the report we may refer to ‘members of staff’ or ‘teachers’. However, technically speaking, the underlying data are always at the level of ‘contracts’ or ‘teaching contracts’.

2.2 Data processing and definitions

The original dataset we received from Texuna Technologies Ltd. included data from 138 colleges, for a total of 65,534 records.

In contrast to previous years’ data, the dataset did not include any ‘backfilled’ records (observations from earlier years). This was to allow a more straightforward comparison with the approach taken in last year’s report which relied only on those colleges providing current year data for analysis.

For consistency with the approach taken last year, we also wanted to include in our analysis only colleges providing a complete record of contracts for 2013-14. This required additional cleaning.

In particular, records in the original dataset come from two sources. The large majority of records (57,266 or 87%) have been submitted by colleges. The remaining 8,268 records (13%) were provided by a staffing agency, Protocol. For 54 of the 138 colleges initially included (“Protocol colleges”), none of the records had been submitted by the college itself.

Although records submitted by Protocol are up to date, it was not clear whether we could consider the records in the data for these 54 colleges to be comprehensive of all the contracts held by those institutions with members of staff. We then performed a number of checks to verify whether the information on any of these 54 could be considered complete:

• We first checked whether the total number of records we had for each of these 54 institutions was comparable to the number of records submitted directly by colleges. Among Protocol colleges, the number of contracts in the dataset was often very low (in 15 cases, three or fewer records). All Protocol colleges had a low number of records (in the bottom 5% colleges by total records received).
• It may be that Protocol colleges happened to be small, which could account for this finding. We used information from the Association of Colleges (AoC) on the total number of students in 338 AoC member institutions to compute the number of records per student for the institutions in our initial dataset. The number of records per student in Protocol colleges was again low compared to all other institutions in our initial dataset. This suggested that Protocol colleges also submitted fewer records than would be expected given the number of students they have.
• Finally, we checked whether we had information on Protocol colleges on at least one teacher, one manager, and one administrative member of staff. This was not the case for any of the 54 colleges.

The results of these checks suggested that the information included in our sample for the 54 Protocol colleges does not provide a complete picture of the colleges’ staff. The 54 colleges were therefore not included in our analysis.

The final dataset used for our analysis includes 84 colleges and 61,524 records.[7]

SIR 22 data includes information on: