Improving the transition from school to work Contents

Chapter 7: Improving and Expanding Use of Data

“If you are on the academic route in education, you have a very clear progression route of GCSE to A-Level to university, and that is very easily understandable. However, only 40 per cent of people do A-Levels. The other 60 per cent do something else, and it is harder to classify what those people do. They can be doing all sorts of things, and the coding is extremely complex because the system is complex.”448

287.Throughout our inquiry we have tried to establish who exactly is in the group of young people who do not take A-Levels, do not go to university but are not NEET. We also tried to find out how they make the transition into work. We could not.

288.Our witnesses told us that there were significant issues surrounding the data available for this particular group of young people. For instance, Professors Hodgson and Spours told us that there is not enough detailed data to identify this group.449

289.This is concerning to us because data is the foundation of any policy. Without good data, these problems will be impossible to understand and then solve and any strategy to address opportunities for this group’s social mobility will be difficult to implement and monitor.

Different demographic factors

290.Our body of evidence has alluded to the fact that different demographic groups within the population of young people have different patterns of participation in further education and also differences in future earnings.450 This is supported by data from the Association of Colleges. For instance, the report ‘College Key Facts 2014–15’ found that ethnic minority students make up 20 per cent of students in colleges, compared with 15 per cent of the general population, and 16 per cent of 16 to 18-year-olds in colleges were eligible for, and claiming, free school meals at age 15, compared with 9 per cent in maintained school and academy sixth forms.451 452

291.We asked our witnesses about this. Dr Speckesser told us:

“There is very clear evidence about certain demographic factors influencing participation as well as attainment. They are the usual suspects. Good GCSEs help you to progress; there are gender and ethnic group barriers that are obviously visible; there are local area effects; and then there is a whole area of parental background and traditions in the family. It is not only income or social status; you may also find some vocation orientation in the family’s trajectory. The truth is that the administrative data will not be extremely helpful in shedding more light on this.”453

Linked data

292.The ways in which administrative data on pupils in England is collected through the education system are complex. There is the unique pupil number; the unique learner number; the personal learner record; and the individualised learner record.

Box 16: Administrative data

Administrative data is information collected for administrative (not research) purposes. This type of data is collected by Government departments and other organisations to help in the delivery of services. The largest administrative databases in the United Kingdom come from the welfare, tax, health and education record systems. The statistics from these datasets will be used to make policy.

Source: Administrative Data Liaison Service: [accessed 22 March 2016]

293.Administrative data from the national pupil database is linked to the further education individual learner records and records gathered by the Higher Education Statistics Agency (HESA). It is not linked to HMRC earnings data.

294.Our witnesses from the Centre for Vocational Education Research told us that due to legislative changes, in the future they hoped to be able to “ … use the administrative data from the national pupil database … and to link that, in the future, to earnings.” The researchers at the centre will then be able to answer the following questions: “how do people doing vocational education now perform in the labour market; what are their chances of getting a job?”.454 Dr Sandra McNally told us: “The issue is the earnings part of the ILR [Individual Learner record]/HMRC data. The linked data set on earnings can be made available to researchers only if they are funded by BIS or DfE.”455

295.The Government explained that the legislation456 which allows the linking of the data enables: “HMRC to share tax-related information for the purpose of enabling the Secretary of State or a devolved authority, including persons providing services to the Secretary of State or devolved authority, to evaluate the effectiveness of education or training. It enables data to be shared for those persons in schools, as well as those in higher education and further education. Therefore, only researchers working on behalf of the Secretary of State can have access to this information.”457 The Government did not say why this was. Our witnesses speculated the data was deemed to be confidential. Professor McNally said that there was no good reason why data was not shared. She told us:

“I appreciate you have to protect people’s privacy and have data protection there, and you have to make sure that the institutions and people are using the data in an appropriate way, all the right security arrangements are in place and they are using it for the right purposes. However, once you have those things set up, it seems to me really important that researchers are allowed to use the data so that we can answer the questions that you are interested in quickly and well, and do cutting-edge research. We do not necessarily need to be funded explicitly by, say, a BIS grant or a DfE grant to do that work. A lot of people would willingly do that in universities. It is a question of making the data available and putting in place the proper arrangements.”458

If data is not shared for reasons of confidentiality, a comment about following due ethics procedures could ensure that other researchers would fulfil requirements for confidentiality.459

Unique pupil numbers

296.Since 1999, unique pupil numbers (UPNs) have been used to track the progress of pupils in England. A number is allocated to a pupil when they first start at a publicly funded school. The number remains with the pupil throughout their school career regardless of any change in where they go to school.

297.The Government told us that UPNs were “introduced to enable accurate and timely data sharing between schools/academies, local authorities and central Government.”460 It also told us that when UPNs were introduced the Department for Education agreed measures with the Information Commissioner to minimise the risk to the personal privacy of students. These measures were:

Unique learner numbers

298.All students aged 14 and over in publicly funded education and training are given a unique learner number (ULN). The ULN is different to the UPN as it stays with a learner for their lifetime. It is a public identifier (and so appears on exam certificates and qualifications). It helps inform the personal learning record.

299.The Government told us that “the ULN is intended to help learners throughout their lifelong learning, particularly when accessing careers advice and benefits both learners and learning providers by allowing higher education applications and course registrations to be processed without applicants having to provide paper qualification certificates.”461

Personalised learning records

300.The personal learning record (PLR) is an official online record of a pupil in England’s qualifications and achievements since the age of 14. The qualifications and certified learning which have been done and recorded on the PLR can be from schools, colleges or the workplace.

Individualised learner records

301.The Individualised Learner Record (ILR) is the main way in which data is collected on participation in further education and work-based learning in England. It is requested from further education providers. It is the only way in which data on participation in further education is collected. Colleges, training organisations, local authorities and employers who receive funding from the Skills Funding Agency to deliver education and training are required to submit learner data via an ILR to the Agency at regular points in the year.

A complete picture?

302.It is clear that there are a lot of ways in which data can be collected and is collected on a young person’s education in England. There are however a number of issues with the datasets produced. The most fundamental is that they do not provide a picture for everyone learning in the education system post-14. This is because the requirements for data collection are only on schools and colleges which are publicly funded. This excludes anyone in private education, for example.

303.Another issue is that the information on what people are doing after the age of 16 is even more incomplete. Professor Orr said: “we do not have enough data within this area. We do have for higher education, but we do not for vocational and further education.”462 Further to this, Sir Michael Wilshaw told us that the data “is not particularly good on youngsters who fall out of the system at 16 and beyond.”463 He said that this is because “it becomes the responsibility of the local authority to gather that data when they leave school and go into FE. Some of them do not do it well.”464 New Economy told us that “local authority data requirements do not currently provide the necessary long term tracking data to come to a conclusion about the wider cohort [of young people compared to those doing apprenticeships]”.465 It is easy to see why datasets are unreliable and incomplete.

304.Dr Stefan Speckesser explained that the problem with the data is that “the missing bit is the non-education participation.”466 He told us that local authorities do not always follow up on the destinations of people after the age of 19. Young people are often in low paid work, and do not appear on HMRC datasets when they are in employment. This is because there is a minimum amount of money that has to be earned before tax is paid. People are only on HMRC datasets when they pay tax. Professor Anne Green told us that “There is also an issue that at local level … there is dependence on the skill sets and experience of the people at local level” and how they collect, collate and use the data.”467 Given that a lot of the data is collected by local authorities, this could be a significant problem.

305.These are all issues concerning the problems in how the data is collected. There is still, however, a vast amount of data collected by local authorities, the Skills Funding Agencies, the Department for Education and the Department for Business, Innovation and Skills.

Making destinations data available

306.The Government publishes data showing the destinations of young people after Key Stages 4 and 5, for those who studied a Level 3 qualification. There are a number of problems with this.

307.The first problem is that the data is not robust. The Government told us that “the destinations of 17 per cent of the group were unknown.”468 It is, however, working on improving this.469 One of the reasons for this is that young people change jobs frequently within the first couple of years.

308.The second problem is more fundamental. The Government only publishes data on those who complete a Level 3 qualification. We know that having this qualification is important (see paragraphs 206–265). Those who have one have a greater chance of social mobility than those who do not. This data is used to work out what the economic returns are on having completed a Level 3 qualification. What is not published are the destinations of those who have completed a Level 1 or 2 qualification. This makes it harder to assess what the value of a Level 1 or 2 qualification is. The picture is therefore not complete. Even though a Level 3 qualification may have much greater value than a Level 1 or 2 qualification, it may still be better to achieve a Level 1 or 2 qualification than no qualification at all.

309.The publication of details of the destinations of learners was proposed by a number of our witnesses. 470 Ralph Scott told us that holding schools and colleges to account on their destinations data would “improve the incentives for schools to really provide goodquality careers advice.”471 Professor Hodgson said destinations data “is very useful at the local level to demonstrate to young people the kinds of pathways that they might take, based on evidence that has been collected locally.”472

310.Professor Hodgson cautioned that “schools can do so much”. The main body of our evidence highlighted the strength of background on attainment. Professor Orr noted his scepticism about “… about schools being judged on things they have no control over.”473 The International Centre for Guidance Studies agreed.474

311.It would be possible to look at the approach used for gathering higher education destinations data as a model for school and college leaver data at ages 18 and 19. Destination data is gathered for all students who complete higher education courses in the UK, through the Destinations of Leavers from Higher Education (DLHE) survey. This is carried out by the Higher Education Statistics Agency (HESA). There are two surveys:

(a)an Early Survey which asks all leavers from higher education what they are doing six months after graduation; and

(b)a Longitudinal Survey, which is conducted 3 years later (3 years and 6 months after graduation), and is based on a sample of those who responded to the Early Survey.475

312.Future First is a membership body which provides a database platform for schools and colleges to record the destinations of their former students via an online form and annual survey. 476

313.In principle publishing destinations data over a period of several years is a good idea. Publishing small amounts of data is no good. More needs to be done to ensure the accurate collection and recording of data. While care would have to be taken in designing these figures, an example of a relevant figure could be the percent of free school meals (FSM) students who go onto find employment within six months. We recognise, however, that there are factors affecting young people over which schools and colleges have little or no control. Such factors include a range of influences associated with their family circumstances and background.

Using the data available

314.The variety of databases available suggest that for a complete picture of the transitions and destinations of these young people to be produced, they need to be shared and linked together. The Government told us that it is looking “to reduce the number of unknown destinations and improve the robustness of the measures in the future by matching HMRC and DWP data to our data.”477 The ability to share data under the provisions of sections 78-80 of the Small Business, Enterprise and Employment Act 2015 should enable Government to access information for every learner about post-training destinations; earnings; and whether the learner was previously on benefits.

315.Dr Speckesser recognised that data collection on people who are in education is getting better:

“The data situation has improved very dramatically in that many administrative data sets in the Department for Business, Innovation and Skills were merged so that we can see who is participating in post-16 education and we can track their later employment and earnings trajectories in HMRC administrative data.”478

316.Professor McNally called for administrative data to be linked “as efficiently … across departments as possible to make it available to researchers who have the right institutional requirements and have gone through the security checks.”479

317.We were also told that the range of data and how it is collated and collected make it difficult to use. In particular, our witnesses highlighted the difference between the data collected by schools and other data. Professor McNally told us that “the ILR data set is extremely complex to use, much more complex than the schools-level data.”480 We asked Professor Baroness Wolf if there was an ideal model of dataset for research purposes. She said: “Truthfully, if you started with school data as a model, you would not go far wrong.”481

Social Mobility and Child Poverty Commission report - March 2015

318.In March 2015, the Social Mobility and Child Poverty Commission published a report which considered the use of data to inform policy making on social issues.482 The Commission proposed three principles that should guide the Government’s sharing of data:483

(1)where there is a clear public benefit, and where there is a system in which data can be shared safely, data should be shared.

(2)where legislative changes are required to realise principle one, they should be made.

(3)given bodies that control important administrative data should share their data. These bodies should expect to justify and be held accountable for any refusals to share data.

319.It is clear to us that there are significant issues with the data used to inform policies and to understand their impact on this complex group of young people. We recognise the importance the Government puts on having robust data to inform its policies. We also welcome the proactive steps the Government has taken, and is planning to take, in addressing the issues raised by the current data.

320.Existing data is unreliable and inconsistent. Too little is known about the group of young people who do not pursue higher education, what they study, and where they are employed. In particular, the publicly available data does not allow for the analysis of learners by different demographics such as family background, ethnicity, social class, region, gender, caring status and so on.

321.We agree with, and support, the Social Mobility and Child Poverty Commission’s principles on administrative data sharing. More information is required on young people’s further education and vocational qualifications and routes, and their destinations in the labour market.

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