I am intrigued by this presentation. Whilst I appreciate what Chris Taggart, who has been invo0lved in the development of the opencorporates and openlylocal data sites (and who undoubtedly has more experience and knowledge than me of the use of Open and Linked Data) I would be less pessimistic. I see the use of open and linked data as in very early days.

Firstly, although I appreciate that politicians and bureaucrats do not always want to release data – I think there is still a groundswell in favour of making data available – at least in Europe. Witness yesterdays unveiling of the Italian Open data store (sorry, I can’t find the url at the moment). And although Google search results do not help promote open data sites (and I am not a great fan of Google at the moment after they wiped out my account ten days again), they have contributed very useful tools such as Refine, Fusion Tables and Public Data Explorer.

I still think that as Chris Taggart says in one of his first slides the biggest challenge is relevance. And here I wonder if one of the problems is that Open and Linked Data specialists are just that – specialist developers in their own field. Many of the applications released so far on the UK Data store, whilst admiral examples of the art of development – would seem to have little practical use.

Maybe it is only when the tools and knowledge of how to work with Open and Linked data are adopted by developers and others in wonder social and subject areas that the true benefits will begin to show. Open data applications may work best, not through dedicated apps or sites, but when incorporated in other web sites which provide them with context and relevance. Thus we have been working with the use of open and linked data for careers guidance (see our new web site, www.careerstalk.org which includes working demonstrations).

Bu even more important may be finding ways of combining Open and Linked data with other forms of (human) knowledge and intelligence. It is just this form of knowledge – for instance the experiences and informal knowledge of careers guidance professionals, which brings relevance and context to the data from official data sets. And that provides a new design challenge.

The debate over the future of Higher Education is continuing. There were two interesting newspaper articles in the past days in the Guardian and the New York Times.

The Guardian reports that the first set of statistics on applications to university next year, published by the Universities and Colleges and Admissions Service (Ucas), reveal that 52,321 applicants have applied from within the UK, compared with 59,413 this time last year. This is a fall of some 12 per cent, perhaps unsurprising given the steep rise in university tuition fees.

But the main interest is in the detail. The fall in applications is by no means even across universities and subjects, or by geographical region or age of applicant. The Guardian reports: “The figures suggest more women than men have been put off from applying to university. Some 10.5% fewer women have applied this year, and 7% fewer men.

Mature students appear to have been particularly deterred by the higher fees, the figures show. The number of applicants aged 40 or older has fallen by 27.8%, and among those aged between 30 and 39 the number has dropped by 22.7%.”

In terms of regions  the “numbers of applicants from the east Midlands (down 20%), Yorkshire (17.3%) and the north-east (14.7%) have fallen furthest, the figures show. London (down 9.1%) and the south-east (8.1%) have been less affected.”

And in terms of subjects “applications to education degrees have fallen by 30%, and those to business studies by 26.1%, the figures show.”

There are some pretty clear patterns here. Although there is no data on socio econo0mic backgrounds of applicants the fall in applicants is greatest from working class areas. And in  deterring mature students from applying, this will have a disproportionate effect on education which has in the past been an attractive second career.  The reduction in applications for business studies is more puzzling. Once more this may be an effect of less applications from mature students. Or it could be a general disillusionment with business as a whole. Or it may be that students are turning towards more vocational degrees and fear business studies offers little chance of post university employment.

It is also interesting to note that the fall in applications is uneven across institutions. The elite universities – like Oxford and Cambridge –  are little affected with the biggest reductions seemingly hitting the old Polytechnics.

Once more this can be seen as a class factor, with elite universities always having had a disproportionate number of applications from higher income social groups.

All in all, the figures appear to co0nfirm those critics who pointed to the UK university system becoming more elitist, with working class students afraid of the high debt levels the new fees structure will result in.

The New York Times published an “Opinion” article by Michael Ellsberg entitled “Will dropouts Save America”?

Although somewhat whimsical, Ellsberg points out most job creation comes from business start ups. he goes on to say: “Start-ups are a creative endeavor by definition. Yet our current classrooms, geared toward tests on narrowly defined academic subjects, stifle creativity. If a young person happens to retain enough creative spirit to start a business upon graduation, she does so in spite of her schooling, not because of it.”

But Ellsburg’s solution is hardly progressive. He thinks schools and universities should teach people how to buy and sell things as the bedrock of business start up. And in general he thinks young people are better off not going to university. Ellsburg ignores the importance of access to capital for those seeking to set up new businesses. But I would agree with several things he says. he points out that there is a dual job market in the USA – and I would contend in the UK as well. he points to an informal job market with employment being based on netwo0rking and contacts. “In this informal job market, the academic requirements listed in job ads tend to be highly negotiable, and far less important than real-world results and the enthusiasm of the personal referral.”

And he says “Employers could alter this landscape if they explicitly offered routes to employment for those who didn’t get a degree because they were out building businesses.”

Such employment routes used to be called apprenticeships. A revival of apprenticeship training could offer a high skills alternative to university education and provide the job adaptability skills need for succeeding in the highly unstable employment market today. But such apprenticeships cannot be left to employers alone. In the UK the government has taken to calling almost any course an apprenticeship, regardless of skills levels or length. Apprenticeship requires development and regulations to ensure the quality of the learning experience. Bit apprenticeship can offer an alternati9ve route of education to the failed model of mass university education.

We are happy to announce the launch of a new webs site, CareersTalk. The site, developed jointly between Pontydysgu and the Institute for Employment Research, Warwick University, provides access to the ongoing research and development we are undertaking into careers guidance and in particular, the use of new technology to support careers guidance. Much of this work has been undertaken with support from the EU Mature-IP and G8WAY projects.

The introduction says: “The web site is designed to provide leading-edge ideas for careers work – including information-advice-and-guidance, careers education, career counselling, mentoring, coaching, personal-and-social development, learning for well-being, for a changing world, portfolio development and individual action-planning. In particular it focuses on the use of technology for careers information, advice and guidance. Technology has already influenced, and will continue to influence, not only the ways in which guidance services are accessed by clients, but how they are used by them.”

The web site also provides links to working versions of our data visualisation tools.

Over the last two years there has been much excitement about the idea of Open and Linked Data. This is especially so in countries like the UK where there has been a pronounced policy commitment to opening the use of public data for commercial and non commercial use. The UK government open data store boasts links to over 5400 sets of data saying “This can then be used by people to build useful applications that help society, or investigate how effective policy changes have been over time.”

There is no doubt that this data is of immense value to researchers. But despite various hack days, the number of genuinely useful applications seem limited.

We have been working with the data for the last nine months attempting to use labour market data to assist careers professionals and young people in choosing careers pathways. As Leia says in a comment on a recent post on this site “so many of our learners arrive with a complete incorrect (or no) idea about what skills are in demand and what’s realistic to expect in terms of looking for work and training.” We are not saying that labour market data and skills demand alone should guide young peoples’ choices. But it is certainly an important factor especially with university education becoming so expensive.

Why are we finding it hard to do? Firstly as the similar Salami project run by the University of Nottingham noted in a recent report much of the official data is collected for economic purposes, not for social use. For instance, much of the labour market information is collected through the Standard Industrial Classification (SIC) which although useful for analysing economic trends, is of limited use for occupational guidance. Instead, we really need Standard Occupational Classification (SOC) data. It doesn’t help that despite the data store which provides links to different data sets, the raw and interpreted data is scattered across a number of different web sites. Most of them are in the course of updating their sites, probably in order to make the data more accessible. But at the same time his is breaking links. And although there are a growing number of on-line tools, these all have their own idiosyncratic interfaces and processes (and often seem just not to work).

I was never very interested in statistics until I got involved in this project. And now I am desperately trying to teach myself SPSS but it is not easy and once more is time consuming.

Even when we have obtained the data it has to be cleaned. much of the data also requires manipulation if it is to be visualised. Visualisation tools are becoming more powerful, but still are not always simple to handle.

Using Open and Linked Data is a design process. And some of the most important people who have to be involved in any design process are the end users. Once more this is time consuming. And of course it is necessary to show them what the possibilities are. each different group of users will have different needs. We have spent a long time thinking about what data we should show to young people and what might be relevant for careers advisers.

Finally we have to remember that data is just data – however well visualised. The use of data has to involve meaning making. meaning making is not a precise science. Different people will make different meanings from the same data. The real added value comes when we allow them to participate in collective sense making through sharing and negotiating meanings.

We have developed the idea of a Technology Enhanced Boundary Object which is able to bring together data and data vidsualisations with a  social software layer to explore meanings. We hope to pilot this in the autumn. And we will provide access to a working version of some of our tools in the next week.

So in conclusion – I remain very excited about the potential of Open and Linked Data. But to design apps which are useful takes a lot of work.

Here is a quick update on some current work at Pontydysgu. With funding from the European Lifelong Learning Programme G8WAY project and the European Research Framework Mature-IP project, and working with a growing community of partners, we have been developing a series of Web 2.0 tools to support careers guidance. At the moment we are developing a  new web site which will give full access to these tools and applications, as well as to research about the use of Web 2.0 and social software for careers information, advice and guidance. Below is a summary of these tools. If you are interested in finding out more about any of these tools or about our approach to using technology to support careers guidance please get in touch.

Labour Market Visualisation Tools

We are developing tools and applications for visualising Labour Market Information in order to provide young people with an informed basis for decision making around career directions and to support the careers guidance professionals who advise young people. This work has been undertaken in conjunction with the Institute for Employment Research, University of Warwick and Careers Wales.

RadioActive

RadioActive is a project using internet radio to assist young people, particularly those from a NEETS (Not in Employment, Education, or Training) background in developing decision making and communication skills. This approach focuses on informal learning and the development of communities of practice through the use of new technologies. The approach is being piloted in conjunction with the University of East London, Yoh, a Hackney based youth agency, and Inspire!, the Education Business Partnership for the London Borough of Hackney.

Storiboard

Storiboard is a Web 2.0 tool for storytelling. In the first year of the G8WAY project we found that storytelling is a powerful tool for developing and reflection on careers biographies. Storiboard allows young people to use multimedia including video, audio and graphics to tell their careers stories and aspirations. It is initially being tested  through using the original stories collected in year one of the project and will then be piloted with UK based careers services.

Webquests

We are developing a series of Web 2.0 webquests designed to support professional development for Careers Guidance professionals. The first two are on the use of the internet for Careers Guidance and on careers in Science, Technology, Engineering and Maths (STEM). Along with our technical partners, Raycom, we are developing a lightweight repository which combined with the Storiboard interface, will provide for easy editing and development of Webquests.

A quick update. I have been slow posting lately due to travelling around and a series of project meetings.

We are moving forward on a series of ideas and developments.

Firstly we are working with The Univeristy of East London, the Hackeny Education – Business Partnership and a Yoiuth Organisation called Go! to launch Radiocative, an internet radion station run by young people for young people.

Secondly we are developing a new application for online story telling.

Thirdly I have been doing demos of our new open and linked data application for supporting young people in planning careers and providing information for careers advisors. Early feedback has been very positive and I am hopeful we will be able to roll this out for an extended trial after the summer. Before that though, I want to develop a social layer, allowing data outputs to be discussed  and incorporated in wider social discourses.

I am ever more interested in how we can use technology for supporting young people (and not just young people) in making future careers choices. Talking to a focus group of young people last year, they  make use of the internet, particuarly using Google to search for details about possible future education choices, jobs and careers. I also asked them how far they explored the results of a Google search and not surpisingly they told me that they usually looked at the first three or four results. Try doing this yourself – type in your job of choice and see what comes up. All too often the results can be highly misleading.

Anyway we are working on new tools to asisst young people in choosing their future careers (more details to follow quite soon, I hope). And here is a conference paper, prepared by my colleague Sally Anne Barnes from the University of Warwick and describing the emprirical research we undertook on the use of technology in careers education in the UK (requires html5 compliant browser to view). Comments welcome – I would especially like to know what is happening in other countries than the UK.

The Potential Role of Technology in Careers Education in the UK

The second verse of the great Pete Seeger song ‘Little Boxes‘, written by Malvina Reynolds goes:

And the people in the houses
All went to the university,
Where they were put in boxes
And they came out all the same,
And there’s doctors and lawyers,
And business executives,
And they’re all made out of ticky tacky
And they all look just the same.

And of course it is true. More than that, it is the policy on which most of our careers guidance practice is based. Find what skills industry and commerce needs, goes the policy, set up training places to meet those needs, put people into those boxes and we will turn out a neat match between skills and the needs of the economy.The strategy is called ‘skills matching’ and forms the basis for the European New Skills, New Jobs policy as well as that of many national governments.

Universities traditionally stood aloof from such a policy which they saw only as applicable to those in vocational education and training. Univeristy was about the development fo minds and about research.

But with the increasing commodification of universities, they too are embracing such a strategy, in the name of value for money and employability. Students are reluctant to part with large sums of money unless they can see a job progression route for their expenditure on a degree course; governments regard vocational relevance as the key criteria in providing fiances for higher education.

The only problem is that the ‘Little Boxes’ approach doesn’t work. Firstly employers often don’t know what skills they want. take the fiasco at the end of the last century when the European Industry Group for Information and Communication Technologies was predicting huge skills gaps in computing and computer programming. These gaps never materialized despite little growth in the supply to computer programmers. Secondly we simply do not have sufficiently well developed central planning infrastructures to plan for skills and employment in such a way.

This is not to deny the needs for close community links between employers and education providers, at least on a local level. However this should not be to the detriment of other community interests in education and community well being. And rather than focus on skills matching, it would be far better to focus attention on creativity and innovation. If we look at regional innovation centres in Europe such as the manufacturing clusters in Emilia Romana or the media cluster in Cardiff it could be argued that such growth happened due to innovation around the skills and creativity of the workforce, rather than because of matching of skills to existing industry (indeed in Cardiff’s case the economy was traditionally based on heavy industry and manufacturing).

In any case is it possible to ‘predict’ the skills needed int he economy in a period of fast technological change? The Institut Technik und Bildung at Bremen University, with whom I have worked for many years used to talk of the ‘shaping’ principle. They saw education as playing a key role in shaping work organisation and skills development as enabling social innovation in production and economic development. The word ‘shaping’ is a translation of the German ‘Gestaltung’, also commonly translated as ‘design’. And once more this would suggest we can design our futures, that technology and production are not mechanistically determined but rather can be shaped or changed.

But for such an approach we need people who can think out of the box, who can consider the social implications of technology development. And that will not happen through a skills matching policy!

The de facto end of free education in the UK, and in particuar the imposition of coniderable fees for univeristy courses, which is likely to be extended to vocational programmes, is going to have widespread implications for peoples’ choices of careers.

Inthe next few weeks we will be exploring some of those implications on this blog.

One issue is that people are beginning to exmaine the ‘value’ of a degree in terms fo enhnaced lifetime earnings. And the rseulkts may not be as people have assumed. Governements and goevrnmental bodies have long espoused the importance of the so called STEM subjects – Science, Technology, Engineering and Maths – but figures suggest it may not be these subjects which enjoy the best pay premium.

According to the Guardian:

Male graduates in law, economics and management (LEM), for example, enjoyed faster growth in wages early in their career lifecycle compared to other majors, including Stem (science, technology, engineering and maths). Stem graduates, or those with combined degrees, eventually catch up with those who did LEM but not till much later in the lifecycle. For those opting for arts and other social science degrees, the lifetime returns are markedly lower – especially for men. The subject you study, then, makes a big difference to the investment returns, although, so far, only one institution has suggested subject specific pricing, so the costs are broadly the same across subjects. (Note that our research shows that early-career wage levels are not a good predictor of lifetime earnings – but, be warned, the government’s guidance for students on which subjects and institutions to choose will present data on early earnings.)

Among women, the picture is different. LEM graduates saw the highest and fastest rate of return. But women who did a degree – irrespective of which subject – enjoyed substantially higher lifetime earnings than those who didn’t. This can be read as an indication of the kind of discrimination that female non-graduates still face in the labour market. Moreover, the returns were broadly similar across subjects.