Archive for the ‘labour markets’ Category

Skills for Green Jobs

June 14th, 2019 by Graham Attwell


Addressing climate change and setting economies and societies more firmly onto a path towards a sustainable, low-carbon future is one of the defining challenges of our time. Such shift will entail far-reaching transformations of our economies, changing the ways we consume and produce, shifting energy sources, and leveraging new technologies.

The European Centre for Vocational Education and Training, Cedefop, has released a new report on Skills for Green Jobs. The report is based on country studies undertaken in collaboration with the International Labour Organization (ILO) in six countries (Denmark, Germany, Estonia, Spain, France and the UK) since 2010.

A key outcome, says CEDEFOP, is that countries vary in their approach to defining, classifying and collecting data on green jobs and skills. However, they have observed increased efforts are observed on data collection on developments in the ‘green economy’.

Since 2010, green employment trends have tended to parallel general economic trends. Carbon reduction targets and associated incentives and subsidies have been especially influential on green jobs and skills; other green policies, such as legislation to protect the environment, have also been important.

Although few countries have a strategy on skills for green jobs, “the updating of qualifications and VET programmes has soared, reflecting increased demand for green jobs and skills since 2010.” Updates mainly concern adding ‘green’ components to existing qualifications/programmes, since changes in skill demands are perceived more pertinent to including new green skills within existing occupations rather than the creation of new green ones.

 

More information is available in the CEDEFOP magazine promoting learning for work, Skillset and Match.

Transferable skills and the future of work

April 9th, 2019 by Graham Attwell

There continues to be a flurry of newspaper articles and studies of teh effect of automation and Artificial Intelligence on employment and jobs. There are different predictions about the scale of the change and particularly about the numbers of jobs which are at risk. One cause of the difference is disagreements about how many new jobs will be created, another is the speed of change. This may in part depend on whether employers choose to invest in new technologies: in teh UK productivity has remained persistently low, probably due to low wage rates.

What we do know is that organisations will need to cope with many of the changes associated with changes in the skill mix required of their employees  through learning through challenging work, training and continuing professional development etc. We also know that the changes mean it is difficult to imagine exactly how the labour market will look in say ten years but understanding the labour market can help people make sense of the context in which they are working or are seeking to work

At the same time we do not know the exact skill demands associated with unforeseen changes in the labour market, but we do know that new technical skills will be required, individuals and firms may need to specialise more to compete in global markets, and that demand will grow for ‘soft skills’ which are very difficult to automate, including complex social skills, cultural and contextual understanding, critical thinking, etc.

Yet this debate is not new. In the 1990s there were similar debates around teh move towards the ‘knowledge society’. At that time it was being predicted that low skilled work was set to rapidly decline, a prediction that pre-dated the rapid expansion in low skilled (or at any rate low paid) employment in the service sector. the answer at that time was seen to be promoting transversal skills and competences, variously called core skills, core competences etc. These emhpasised teh important of literacy and numeracy as well as communication skills and Information Technology. The problem was that such skills and competences were, in general abstracted from the curriculum as stand aone areas of learning, rather than being integrated within occupational learning. Of course, the other tendency n many Euroepan countries was to increase the number of young people going to university, at the expense of vocational educati0on and training.

What was needed then as now was to develop technical skills coupled with soft skills. Mastery of a technical skill is itself be a transferable skill whereby other technical skills can be developed more quickly as they are required . Developing latest industry-integrated technical skills is easiers if an underpinning technical knowledge base has been developed through more traditional educational provision. Retraining while in-work is very much easier than getting redundant people back into work.

Germany by Gerald Heidegger and Felix Rauner who looked at occupational profiles. Occupational profiles are in effect groups of competencies based on individual occupations. In Germany there are over 360 officially recognised occupations.

As long ago as 1996, Gerald Heidegger and Felix Rauner from the University of Bremen were commissioned by the Government of Rhineland Westphalia to write a Gutachten (policy advice) on the future reform and modernisation of the German Dual System for apprenticeship training.

They recommended less and broader occupational profiles and the idea of wandering occupational profiles. By this term they were looking to map the boundaries between different occupations and to recognise where competences from one occupation overlapped with that of another. Such overlaps could form the basis for boundary crossing and for moving from one occupation to another.

Heidegger and Rauner’s work was grounded in an understanding of the interplay between education, work organisation and technology. They were particularly focused on the idea of work process knowledge –  applied and practice based knowledge in the workplace. This was once more predicated on an idea of competence in which the worker would make conscious choices of the best actions to undertake in any particular situation (rather than the approach to competences in the UK which assumes there is always a ‘right way’ to do something).

Per Erik Ellstroem from Sweden put forward the idea of Developmental Competence – the capacity of the individual to acquire and demonstrate the capacity to act on a task  and the wider work environment in order to adapt, act and shape (design) it.

This is based on the pedagogic idea of sense making and meaning making through exploring, questioning and transcending traditional work structures and procedures. Rauner talked about holistic work tasks, based on the idea that a worker should understand the totality of the work process they are involved in.

In this respect it is interesting to see the results of recent research by Burning Glass, a company using AI and big data techniques to analyse labour market information. They say that in examine the role of Receptionist in Burning Glass Technologies’ labor market analysis tool, Labor Insight, “we can see that receptionists have a variety of related jobs they can do based on their transferable skills. Transferable skills are types of skills that a worker can use across many jobs, allowing them to more easily transition into a new role. A receptionist has many transferable skills such as administrative support, customer service, scheduling, data entry, and more. These transferable skills will allow a receptionist to move into related jobs such as Legal Secretary, Executive Assistant, or File Clerk.

According to Labor Insight, a Receptionist can transition into a Medical Secretary role which offers a higher average salary and is projected to grow by 22.5% in the next 10 years. This also offers an opportunity for the receptionist to venture into a new industry, allowing them to explore new health care roles such as Nursing Assistant, Emergency Room Technician, or Patient Service Representative.

The transferable skills that Burning Glass talk of are very similar to Rauner and Heidegger’s wandering occuaptional profiles. Rather than. as some commentators have suggested (see for example Faisal Hoque), a return to humanities based subjects in providing abstracted knowledge as the basis for future qualifications, the need is to improve vocational education and training which allows workers to understand the potentials of integrating automation and AI in the workplace. Creativity is indeed important, but creativity was always a key aspect of many jobs: creativity is part of the work process, not an external skill.

Automation and the future of work: the Chatbot

April 8th, 2019 by Graham Attwell

According to the Office for National Statistics, around 1.5 million jobs in England are at high risk of some of their duties and tasks being automated in the future.

The ONS analysed the jobs of 20 million people in England in 2017, and has found that 7.4% are at high risk of automation.

Automation involves replacing tasks currently done by workers with technology, which could include computer programs, algorithms, or even robots.

Women, young people, and those who work part-time are most likely to work in roles that are at high risk of automation.

It is important to understand automation as it may have an impact on the labour market, economy and society and on the skills and qualifications young people will need in the future.

The ONS have developed a chatbot for people to find out more about automation. You can try it out below and you can download the data here.

Understanding Labour Market data

April 8th, 2019 by Graham Attwell

The increasing power of processors and the advent of Open Data provides us information in many areas of society including about the Labour Market. Labour Market data has many uses, including for research in understandings society, for economic and social planning and for helping young people and older people in planning and managing their occupation and career.

Yet data on its own is not enough. We have to make sense and meanings from the data and that is often not simple. Gender pay gap figures released by the UK Office of National Statistics last week reveal widespread inequality across British businesses as every industry continues to pay men more on average than women. This video Guardian journalist Leah Green looks at the figures and busts some of the common myths surrounding the gender pay gap.

Where do graduates come from and where do they go?

February 21st, 2019 by Graham Attwell

I’ve written too many times about the problems in sense making from data – particularly where the labour market and education are involved. This presentation from the UK Centre for Cities makes an admiral attempt to use the data to tell a story about where students are coming from to study at Glasgow’s Universities and where they go afterwards.

It has its drawbacks – mainly due to the lack of data. For instance most of the slides fail to show movements in and out of the UK. Also, I would have loved to have more detailed data about what jobs students go into after university, but this data just is not available from UCAS at a more disaggregated level. And I am not very sure about the click bait title: “the Great British Brain Drain.” If there is a brain drain, nothing in the analysis points to one.

It is interesting to see that manufacturing still accounts for 44% of new graduate employment is Glasgow, despite manufacturing only constituting 30% of total employment in the city. This is much more that the 19& of new graduate working in the much heralded knowledge intensive business services sector.

One of their conclusions is very important: its not just about the student experience or the quality of nightlife in a city but more importantly “Ultimately it’s the jobs available to graduates which determine if they stay. By offering more, and better, opportunities the city will attract more graduates, both those who have studied in the city and those moving in for the first time from elsewhere.”

Developing a skills taxonomy

February 6th, 2019 by Graham Attwell

This morning’s mailing from the Marchmont Employment and Skills Observatory reports that NESTA have launched an interesting new Tool – a UK skills taxonomy:

“Skill shortages are costly and can hamper growth, but we don’t currently measure these shortages in a detailed or timely way. To address this challenge, we have developed the first data-driven skills taxonomy for the UK that is publicly available. A skills taxonomy provides a consistent way of measuring the demand and supply of skills. It can also help workers and students learn more about the skills that they need, and the value of those skills.” NESTA

It should help with careers guidance and is ideal for people looking at the return to differing career choices and how you get there. NESTA began with a list of just over 10,500 unique skills that had been mentioned within the descriptions of 41 million UK job adverts, collected between 2012 and 2017 and provided by Burning Glass Technologies. Machine learning was used to hierarchically cluster the skills. The more frequently two skills appeared in the same advert, the more likely it is that they ended up in the same branch of the taxonomy. The taxonomy therefore captures ‘the clusters of skills that we need for our jobs’.

The final taxonomy can be seen here and has a tree-like structure with three layers. The first layer contains 6 broad clusters of skills; these split into 35 groups, and then split once more to give 143 clusters of specific skills. Each of the approximately 10,500 skills lives within one of these 143 skill groups.

The skills taxonomy provide a rich set of data although requiring some work in interpretation. The six broad clusters of skills are:

The ten clusters (at the third layer) containing the most demanded skills are:

  1. Social work and caregiving
  2. General sales
  3. Software development
  4. Office administration
  5. Driving and automotive maintenance
  6. Business management
  7. Accounting and financial management
  8. Business analysis and IT projects
  9. Accounting administration
  10. Retail

The five skill clusters at the third layer with the highest annual median salaries are:

  1. Data engineering
  2. Securities trading
  3. IT security operations
  4. IT security standards
  5. Mainframe programming

The five clusters with the lowest salaries are:

  1. Premises security
  2. Medical administration
  3. Dental assistance
  4. Office administration
  5. Logistics administration

While the taxonomy is based on web data collected between 2012 and 2017, the approach has teh potential to be developed on the basis of real time data. And it is likely to be only one of a number of tools produced in the next two years using machine learning to analyse large data sets. The use of real-time data from web vacancies is receiving a lot of attention right now.

There is also interest in the idea of skills clusters in the ongoing debate over the impact of Artificial Intelligence on jobs and employment. Rather than whole occupations disappearing (and others surviving) it is more likely that the different skills required within occupations may change

The development of Labour Market Information systems

August 29th, 2018 by Graham Attwell

Over the past few years, part of my work has been involved in the design and development of Labour Market Information Systems. But just as with any facet of using new technologies, there is a socio-technical background to the emergence and use of new systems.

Most countries today have a more or less elaborated Labour Market Information system. In general, we can trace three phases in the development of these systems (Markowitch, 2017). Until the 1990s, Labour Market Information systems, and their attendant classification systems, mainly provided statistics for macroeconomic analysis, policy and planning. Between the 1990s and 2005 they were extended to provide data around the structuring and functioning of the Labour markets.

Mangozho (2003) attributes the change as a move from an industrial society to a post-industrial society (and the move to transition economies in Eastern Europe). Such a definition may be contentious, but he usefully charts changes in Labor market structures which give rise to different information needs. “While previously, the economic situation (especially the job structure) was relatively stable, in the latter phase the need for LMI increases because the demand for skills and qualifications changes fundamentally; the demand for skills / qualifications changes constantly, and because of these changes, Vocational Education and Training (VET) system has to be managed more flexibly (ETF, 1998)’.

He says: “In the industrial/pre-transition periods:

  • The relationship between the education and training system and the Labor market was more direct.
  • Occupational structures changed very slowly and as such, the professional knowledge and skills could easily be transferred.
  • Planning, even for short-term courses, could be done well in advance, and there was no need to make any projections about the future demands of occupations
  • The types of subjects and the vocational content required for specific jobs were easily identifiable.
  • There was little need for flexibility or to design tailor-made courses.
  • The education system concentrated on abstract and theoretical knowledge as opposed to practical knowledge.
  • Steady economic growth made it possible for enterprises to invest in on the job training.
  • There was less necessity to assess the relevance and adequacy of the VET system because it was deemed as adequate.
  • A shortage of skills could easily be translated into an increase of the number of related training institutions or student enrolments without necessarily considering the cost effectiveness of such measures. (Sparreboom, T, 1999).
  • Immediate employment was generally available for those who graduated from the education and training systems.”

Changes in the structure and functioning of Labour markets and the VET systems led to a greater need for comprehensive LMI to aid in the process of interpreting these structural shifts and designing effective HRD policies and programs, which provide for more linkages between the education and training systems and the Labor market.

At the same time, the reduction in the role of the state as a major employment provider and the development of market economies gave impetus to the need for a different approach to manpower planning, where the results of Labor market analysis as well as market based signals of supply and demand for skills are made available to the various economic agents responsible for the formulation and implementation of manpower and employment policies and programmes.

This led to the establishment of formal institutions to co-ordinate the generation of LMI, for instance internet based Labour Market Information Systems and the setting up of Labour Market Observatories and the development of more tangible LMI products, which provide a broad up, dated knowledge of the developments on the Labour market for different users.

Since 2005, Labour Market Information systems have been once more extended to incorporate both matching of jobs to job seekers and matching of supply and demand within Labour markets, particularly related to skills.

Data and the future of universities

August 2nd, 2018 by Graham Attwell

I’ve been doing quite a lot of thinking about how we use data in education. In the last few years two things have combined – the computing ability to collect and analyse large datasets, allied to the movement by many governments and administrative bodies towards open data.

Yet despite all the excitement and hype about the potential of using such data in education, it isn’t as easy as it sounds. I have written before about issues with Learning Analytics – in particular that is tends to be used for student management rather than for improving learning.

With others I have been working on how to use data in careers advice, guidance and counselling. I don’t envy young people today in trying to choose and  university or college course and career. Things got pretty tricky with the great recession of 2009. I think just before the banks collapsed we had been putting out data showing how banking was one of the fastest growing jobs in the UK. Add to the unstable economies and labour markets, the increasing impact of new technologies such as AI and robotics on future employment and it is very difficult for anyone to predict the jobs of the future. And the main impact may well be nots o much in new emerging occupations,or occupations disappearing but in the changing skills and knowledge required n different jobs.

One reaction to this from many governments including the UK has been to push the idea of employability. To make their point, they have tried to measure the outcomes of university education. But once more, just as student attainment is used as a proxy for learning in many learning analytics applications, pay is being used as a proxy for employability. Thus the Longitudinal Education Outcomes (LEO) survey, an experimental survey in the UK, users administrative data to measure the pay of graduates after 3, 5 and 0 years, per broad subject grouping per university. The trouble is that the survey does not record the places where graduates are working. And once thing we know for a certainty is that pay in most occupations in the UK is very different in different regions. The LEO survey present a wealth of data. But it is pretty hard to make any sense of it. A few things stand out. First is that UK labour markets look pretty chaotic. Secondly there are consistent gender disparities for graduates of the same subject group form individual universities. The third point is that prior attainment before entering university seems a pretty good predictor of future pay, post graduation. And we already know that prior attainment is closely related to social class.

A lot of this data is excellent for research purposes and it is great that it is being made available. But the collection and release of different data sets may also be ideologically determined in what we want potential students to be able to find out. In the same way by collecting particular data, this is designed to give a strong steer to the directions universities take in planning for the future. It may well be that a broader curriculum and more emphasis on process and learning would most benefits students. Yet the steer towards employability could be seen to encourage a narrower focus on the particular skills and knowledge employers say they want in the short term and inhibit the wider debates we should be having around learning and social inclusion.

 

Learning about Careers: Open data and Labour Market Intelligence

August 1st, 2018 by Graham Attwell

I’ve spent a lot of the last two months writing papers. I am not really sure why – other than people keep asking me to and I really do have a built up load of things which I haven’t written about. But one bad consequence of all this is I seem to have abandoned this blog. So,  time to start catching up here.

This paper – Learning about Careers: Open data and Labour Market Intelligence – is co-written with Deirdre Hughes. It is a preprint and wil be published in RIED – Revista Iboeroamericana de Educación a Distancia (The Iberoamerican Review of Digital Education) some time soon.

The full paper can be found on Research Gate or alternatively you can download it here. The abstract is as follows:

“Decisions about learning and work have to be placed in a particular spatial, labour market and socio-cultural context – individuals are taking decisions within particular ‘opportunity structures’ and their decisions and aspirations are further framed by their understanding of such structures. This article examines ways in which learning about careers using open data and labour market intelligence can be applied. An illustrative case study of the LMI for All project in the UK shows the technical feasibility of designing and developing such systems and a model for dissemination and impact. The movement towards Open Data and increasingly powerful applications for processing and querying data has gathered momentum. This combined with the need for labour market information for decision making in increasingly unstable labour markets have led to the development and piloting of new LMI systems, involving multiple user groups. Universal challenges exist given the increasing use of LMI, especially in job matching and the rapidly expanding use of open source data in differing education and employment settings. We highlight at least six emergent issues that have to be addressed so that open data and labour market intelligence can be applied effectively in differing contexts and settings. We conclude by reflecting on the urgent need to extend the body of research and to develop new methods of co-constructing in innovative collaborative partnerships.”

 

The slow cancellation of the future

March 12th, 2018 by Graham Attwell

leeds-ucu-strike-christianhogsbjergWriting in the Guardian, Becky Gardiner, a senior lecturer at Goldsmiths University in London, explains why she is on strike. Although the strike in the UK universities is now into its fourth week and is ostensibly abut cuts to pensions it raises wider issues’

‭Becky says:

My favourite banner on the picket line reads “Against the slow cancellation of the future”, a phrase popularised by the late cultural theorist, Mark Fisher. In the grip of neoliberalism, we begin to believe that there is no alternative, Fisher told us.

In universities, this slow draining of hope began with the introduction of tuition fees in 1998, and gathered pace when they were tripled in 2010. Successive governments, enthusiastically aided by overpaid senior management drawn from outside the university sector, have turned higher education into a utilitarian and consumer-driven activity that students buy in exchange for skills for the job market.

The latest idea coming from the UK Department for Education (DfE) is to introduce a ratings system would which would allow students to make “consumer-style comparisons of degree courses.” Subjects will be given a gold, silver or bronze award, and details will be made available about post-degree employment prospects, potential earnings and dropout rates, according to the DfE.

The problem for DfE is that for all their efforts educations is not a consumer good. And statistics suggest that the best indicator of potential earnings comes not from which university or indeed which subject is studies but is dependent on the social class that the student comes from. So those courses with more upper class students will have the best post employment prospects, presumably attracting more upper class students and reinforcing their positioning in the consumer style ratings. The slow cancellation of the future seems to be speeding up.

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    Digital Literacy

    A National Survey fin Wales in 2017-18 showed that 15% of adults (aged 16 and over) in Wales do not regularly use the internet. However, this figure is much higher (26%) amongst people with a limiting long-standing illness, disability or infirmity.

    A new Welsh Government programme has been launched which will work with organisations across Wales, in order to help people increase their confidence using digital technology, with the aim of helping them improve and manage their health and well-being.

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    Zero Hours Contracts

    Figures from the UK Higher Education Statistics Agency show that in total almost 11,500 people – both academics and support staff – working in universities on a standard basis were on a zero-hours contract in 2017-18, out of a total staff head count of about 430,000, reports the Times Higher Education.  Zero-hours contract means the employer is not obliged to provide any minimum working hours

    Separate figures that only look at the number of people who are employed on “atypical” academic contracts (such as people working on projects) show that 23 per cent of them, or just over 16,000, had a zero-hours contract.


    Resistance decreases over time

    Interesting research on student centered learning and student buy in, as picked up by an article in Inside Higher Ed. A new study published in PLOS ONE, called “Knowing Is Half the Battle: Assessments of Both Student Perception and Performance Are Necessary to Successfully Evaluate Curricular Transformation finds that student resistance to curriculum innovation decreases over time as it becomes the institutional norm, and that students increasingly link active learning to their learning gains over time


    Postgrad pressure

    Research published this year by Vitae and the Institute for Employment Studies (IES) and reported by the Guardian highlights the pressure on post graduate students.

    “They might suffer anxiety about whether they deserve their place at university,” says Sally Wilson, who led IES’s contribution to the research. “Postgraduates can feel as though they are in a vacuum. They don’t know how to structure their time. Many felt they didn’t get support from their supervisor.”

    Taught students tend to fare better than researchers – they enjoy more structure and contact, says Sian Duffin, student support manager at Arden University. But she believes anxiety is on the rise. “The pressure to gain distinction grades is immense,” she says. “Fear of failure can lead to perfectionism, anxiety and depression.”


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