Category Archives: Career Guidance

STEM and LEM – which pays the most?

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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.

Talking about Data – Careers Information, Advice and Guidance

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This is the first in a new weekly series ‘Talking about Data’. As the name implies, each week I shall be publishing data related to education and learning and talking about it. And I hope you will join in the discussions.

This weeks ‘Talking about Data’ focuses on the provision of Careers Information, Advance and Guidance in England. The data source is Wave Six of the Longitudinal Study of Young People in England. The main objectives of the study are:

  • to gather evidence about the transitions young people make from secondary and tertiary education or training to economic roles in early adulthood
  • to enhance the ability to monitor and evaluate the effects of existing policy and provide a strong information base for future policy development
  • to contextualise the implementation of new policies in terms of young people’s current lives.

E-portfolios – taking learning out of the shoebox: a reply to Donald Clark

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The ever provocative Donald Clarke has posted an interesting article – E-Portfolios – 7 reasons why I don’t want my life in a shoebox. It has sparked off a lively debate with Simon Grant wading in to defend E-Portfolios.

Clarke makes two key points in his argument. The first regards lifelong learning:

People do not see themselves as ‘learners’, let alone ‘lifelong learners’. It’s a conceit, as only educators see people as learners. Imagine asking an employer – how many learners do you have? People are individuals, fathers, mothers, employees, lawyers, bus drivers, whatever….but certainly not learners. That’s why an e-portfolio, tainted with ‘schooling’ will not catch on. By and large, most adults see school as something they leave behind and do not drag along with them into adulthood.

Of course he is right, but there are two ways to look at the idea of lifelong learning. And I do not think this new paradigm of the lifelong learner is a conceit of educators but rather is a policy directive. In a fast changing economy and a period of rapid changes in technology and working practices the drive of such policies is to say that we should all be involved in learning for all of our lifetimes to ensure we are employable and have up to date skills and knowledge etc. etc. This is part of a longer term debate over who pays for education and whose responsibility is it for maintaining our ability to find jobs. In this scenario, unemployed people only have themselves to blame for having no job. If they had maintained their skills they would now be able to find employment. It is indeed a conceit – or rather a deceit – but one which is ideological in intent. But of course educators are being coerced to make this happen.

But there is a second way to look at the idea of lifelong learning. We all learn to a greater or lesser extent every day. Not from the schooling system but through work and play, through informal learning. Of course we do not recognise that as learning and often would not identify ourselves as learners. And then the issue is how that learning can be recognised societally. Not through ‘my life in a shoebox’ but precisely my life outside the shoebox of formal certification and records of achievement.

And coming back to Donald’s shoebox – is this anything new? Prior to e-Portfolios, we all kept bundles of certificates and formal qualifications – indeed often in a shoebox. e-Portfolios have the potential to free us from such restrictions and such narrow ways of looking at learning.

But I agree with Donald when he says:

Media are linked on the web and cannot be easily stored in a single entity or within a single entity, so the boundaries of a real e-portfolio are difficult to define, and will change. An e-portfolio would have to cope with my social networks but they are proprietary. Information wants to be free fiscally and ontologically. We want to be part of all sorts of expansive and variously porous networks, not boxed in.

E-portfolio systems – as they have been conceived – have often been proprietary – despite Simon Grant’s and others’ best efforts to promote interoperability standards. Even that is not the main problem. The main issue is that our digital identity and thus the story of  our personal achievement is scattered across the web. E-portfolios have firstly tended to overly value (and prescribe) formal learning and achievement and secondly have failed to allow us to present our digital presence and life stories in any meaningful way.

Then arises the issue of whether all the effort (and money) expended on e-portfolios has been wasted. On the whole I think not. e-Portfolios is merely a term which was used to encompass the research and development of new forms of technology beyond the VLE – what we now often call Personal Learning Networks or Personal Learning Environments. Perhaps the term e-portfolio is no longer relevant. But that work maintains its coherence and validity. That we have moved on from earlier developments is unsurprising. The use of computers in business and entertainment and for all kinds of other uses is hardly a slow moving field. We cannot expect the use of technology for learning to be any different.

There is one part of Donald’s article with which I would disagree. He talks of a ‘recruitment myth’ saying:

I spent a lot of time recruiting people and what I needed wasn’t huge, overflowing e-portfolios, but succinct descriptions and proof of competences. If by e-portfolio you mean and expanded CV with links to your blog and whatever else you have online, fine. But life is too short to consider the portfolios of hundreds of applicants. Less is more.

In my experience employers are precisely wanting to move away form formal competences to learn what people can do. One Romanian CEO in an advertising company told me he would not employ anyone who did not have an active web presence. Many employers – especially in small enterprises – just Google someone to find out more about them. So yes, I do think we need an application which allows us easily to create an expanded (digital) CV with links to whatever we have online. We do not really have such an application at the moment. If this is to be called an e-portfolio or something else does not matter.

Finally I think Donald disproves his own point when he says:

I can see their use in limited domains, such as courses and apprenticeships, but not in general use, like identity cards.

It seems to me Donald’s “limited domains” are pretty broad. Of course the use of any software, educational or otherwise, is contextual. Contextual in place and time and contextual in terms of why and how we use it. And those are some of the main issues for those wishing to explore the future of e-portfolios or whatever else we call them!

Technology Enhanced Boundary Objects and Visualising Data

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I have been spending a lot of time lately on visualising data as part of our efforts for build technology Enhanced Boundary Objects (TEBOs) to support careers professional in understanding and using Labour Market Information. The work is being undertaken as part of the EU funded Mature-IP and G8WAY projects.

In a short series of posts I will be reporting on my experiences with this work. But first more about those TEBOs.

Background to TEBOs

One particularly fruitful way of thinking about skills development at work is to look at the boundaries between different communities of employees within a workplace and the artefacts (documents, graphs, computer software) that are used to communicate between communities (Kent et al., 2007). Following the analysis of Bowker & Star (1999), “boundary objects” are “objects that both inhabit several communities of practice and satisfy the informational requirements of each of them”, thus making possible productive communication and “boundary crossing” of knowledge. In an earlier project on knowledge maturing and organisational performance (including in career guidance) we developed an approach to learning based on the design of symbolic boundary objects which were intended to act as a facilitator of communication across community boundaries, between teams and specialists or experts. Effective learning could follow from engagement in authentic activities that embedded models which were made more visible and manipulable through interactive software tools. In bringing the idea of boundary objects to the present research, we realised that a sub-set of general boundary objects could be ‘TEBOs’ (technology-enhanced boundary objects), resources within an OLME which were software based.

This approach makes use of the notions of boundary object and boundary crossing. The ideas of boundary crossing and tool mediation (Tuomi-Gröhn & Engeström, 2003; Kaptelinin & Miettinen 2005) and situated learning with a close alignment to the importance of a focus upon practice (Brown et al., 1989; Hall, 1996) informed considerations of the role of technologically-enhanced boundary objects in knowledge maturing processes in different contexts. One specific concern is to make visible the epistemological role of symbolic boundary objects in situations in which people from different communities use common artefacts in communication. A fruitful approach to choosing ways to develop particular boundary objects is to focus on what Onstenk (1997) defines as core problems: the problems and dilemmas that are central to the practice of an occupation that have significance both for individual and organisational performance — in this case the problems associated with providing advice relevant for career planning. One method this development project used was therefore to engage in a dialogue with careers guidance practitioners about common scenarios involving Labour Market Information (LMI) which could inform the development of prototype technologically-enhanced boundary objects (TEBOs). The development of the TEBO is therefore informed by a consideration of the following issues:

  • Importance of developing methods and strategies for co-design with users.
  • Need for conceptual tools to help people understand the models and ideas which are part of LMI.
  • Need for a more open pedagogy (than is typical of much existing technology-enhanced learning, and existing workplace training practice).
  • A system in which boundary objects are configurable by end-users. (practitioners) and by guidance trainers to be used in multiple ways
  • Need to build an understanding of how TEBOs may be used in ways that have utility for the employing organisation (in terms of efficiency savings), are empowering for practitioners, and ultimately for clients too.

These concerns could be coupled with another set of issues concerning appropriate skill development:

  • Need for time for people to interact, reflect, use concepts etc.
  • Trying to reach a stage where practitioners have justifiable confidence in the claims they make and can exercise judgement about the value of information when faced with unfamiliar LMI.
  • Choosing between a range of possible use-contexts.
  • Deciding how to employ support from communication and discussion tools.
  • Developing and transmitting Labour Market intelligence – importance of communicating to others.
  • Preconfiguring certain ways of thinking through use of scenarios; discussions can point into and lead from scenarios.

The above sets of issues provided a clear steer to the type of investigations that would be needed to investigate how TEBOs might be used to support the learning and development of careers guidance practitioners. There are also broader questions about the overall design of the learning system and how users might interact with the system in practice.

Communities of Practice

The importance of Labour Market Information (LMI) in Careers Advice, Information and Guidance has been recognized by the EU in its New Skills, New Jobs strategy. LMI is crucial for effective career decision-making because it can help young people in planning future careers or those planning a change in career in selecting training new careers pathways. LMI is also critical for professionals in supporting other stakeholders in education (like careers coordinators in schools) and training planners and providers in determining future skills training provision. LMI is collected by a variety of different organizations and agencies in Europe including government and regional statistical agencies, industry sector bodies and private organisations. Each collects data for different purposes. Some of these data are made available in a standardized form through Eurostat. However access is uneven. Furthermore the format of the data is seldom usable for careers guidance, and there are few tools to enable its use by advisors or job seekers. This is especially an issue at a time of financial pressures on training courses when potential participants will wish to know of the potential benefits of investing in training. It is also often difficult to access potential training opportunities with the lack of data linking potential careers to training places.

The use of LMI, therefore, lays at the boundaries between a number of communities (and emerging communities of practice).

The practice of careers professionals is related to the provision of careers guidance to clients, such as young people, those returning to the labour market, unemployed people and those seeking a change in careers, amongst others.

LMI is predominantly collected by statisticians working for governmental or non-governmental organisations and agencies. Their practice relates to the collection, compiling, curating and interpretation of data. Data are not collected primarily for providing careers guidance, but for economic and social forecasting and policy advice.

The forms of artefacts used in these different practices vary considerably, with data being released in data tables, which make little sense without (re)interpretation and visualisation. Visualisation is an emergent specialist practice itself requiring cross disciplinary knowledge and a new skills base. Furthermore the use of data in careers practice may require the use of statistical and visualisation tools, however basic, which are generally outside the skills and practice of careers professionals.

In the next post in this series I will look at the identification of the core problems as the basis for the pilot TEBO.

References

Ainsworth, S. & Th Loizou, A. (2003) The Effects of Self-explaining When Learning with Text or Diagrams, Cognitive Science, 27 (4), pp. 669-681.

Bowker, G. C., & Star, S. L. (1999). Sorting things out. Classification and its consequences. Cambridge, MA: MIT Press.

Brown, J. S., Collins, A., & Duguid, P. (1989) Situated cognition and the culture of learning, Educational Researcher, 18 (1), pp. 32-41.

Chandler P. (2004) The crucial role of cognitive processes in the design of dynamic visualizations, Learning and Instruction 14 (3), pp. 353-357.

Hall, R. (1996) Representation as shared activity: Situated cognition and Dewey’s cartography of experience, Journal of the Learning Sciences, 5 (3), 209-238.

Hegarty, M. (2004) Dynamic visualizations and learning: getting to the difficult questions, Learning and Instruction 14 (3), pp 343-351.

Kaptelinin, V., & Miettinen, R. (Eds.) (2005). Perspectives on the object of activity. [Special issue]. Mind, Culture, and Activity, 12 (1).

Kent, P., Noss, R., Guile, D., Hoyles, C., & Bakker, A (2007). “Characterising the use of mathematical knowledge in boundary crossing situations at work”. Mind, Culture, and Activity 14, 1-2, 64-82.

Lowe, R.K. (2003) Animation and Learning: selective processing of information in dynamic graphics, Learning and Instruction, 13 (2), pp. 157-176.

Lowe, R. (2004) Changing status: Re-conceptualising text as an aid to graphic comprehension. Paper presented at the European Association for Research on Learning and Instruction (EARLI) SIG2 meeting, ‘Comprehension of Text and Graphics: basic and applied issues’, Valencia, September 9-11.

Narayanan, N. H. & Hegarty, M. (2002) Multimedia design for communication of dynamic information. International Journal of Human-Computer Studies, 57 (4), pp. 279-315.

Onstenk, J. (1997) Core problems, information and communication technologies and innovation in vocational education and training. Amsterdam: SCO Kohnstamn Institut.

Ploetzner R. and Lowe R. (2004) Dynamic Visualisations and Learning, Learning and Instruction 14 (3), pp. 235-240.

Tuomi-Gröhn, T., & Engeström, Y. (2003) Conceptualizing transfer: From standard notions to developmental perspectives. In T. Tuomi-Gröhn & Y. Engeström (Eds.), Between school and work: New perspectives on transfer and boundary-crossing. Amsterdam: Pergamon, pp. 19-38.

van Someren, M., Reimann, P., Boshuizen, H.P.A., & de Jong, T. (1998) Introduction, in M. van Someren, H.P.A. Boshuizen, T. de Jong & P. Reimann (Eds) Learning with Multiple Representations, Kidlington: Pergamon, pp. 1-5.

Story telling with Data

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Today Google Labs released their new data visualisation store. Very impressive it is too, although it is not a straightforward task to register on the site, upload uses an XML format and you cannot download data. But the visualisation is pretty good and Google themselves have linked to a number of large Eurostat data sets.

I have been working on data for the last couple of weeks. I am trying to build a TEBO – a Technology Enhanced Boundary Object (or objects) for explaining Labour Market data to Careers Advice, Information and Guidance (CAIG). Together with my colleagues from the Institute for Employment Research at Warwick University, I have been looking at TEBOs for some time.

Alan Brown explains the conceptual idea behind TEBOs:

The ideas of boundary crossing and tool mediation (Tuomi-Gröhn & Engeström, 2003; Kaptelinin & Miettinen 2005) and situated learning with a close alignment to the importance of a focus upon practice (Brown et al., 1989; Hall, 1996) informed considerations of the role of technologically-enhanced boundary objects in knowledge maturing processes in different contexts. One specific concern is to make visible the epistemological role of symbolic boundary objects in situations in which people from different communities use common artefacts in communication. A fruitful approach to choosing ways to develop particular boundary objects is to focus on what Onstenk (1997) defines as core problems: the problems and dilemmas that are central to the practice of an occupation that have significance both for individual and organisational performance — in this case the problems associated with providing advice relevant for career planning. One method this development project used was therefore to engage in a dialogue with guidance practitioners about common scenarios involving Labour Market Information (LMI) which could inform the development of prototype technologically-enhanced boundary objects (TEBOs). The development … was therefore informed by a consideration of the following issues:

  • Importance of developing methods and strategies for co-design with users
  • Need for conceptual tools to help people understand the models and ideas which are part of LMI
  • Need for a more open pedagogy (than is typical of much existing technology-enhanced learning, and existing workplace training practice)
  • A system in which boundary objects are configurable by end-users (practitioners) and by guidance trainers to be used in multiple ways
  • Need to build an understanding of how TEBOs may be used in ways that are empowering for practitioners, and ultimately for clients too.

These concerns could be coupled with another set of issues concerning appropriate skill development:

  • Need for time for people to interact, reflect, use concepts etc.
  • Trying to reach a stage where practitioners have justifiable confidence in the claims they make and can exercise judgement about the value of information when faced with unfamiliar LMI
  • Choosing between a range of possible use-contexts
  • Decide how to employ support from communication and discussion tools
  • Developing and transmitting Labour Market intelligence – importance of communicating to others
  • Preconfigure certain ways of thinking through use of scenarios; discussions can point into and lead from scenarios.

In practice it is not so easy to develop such TEBOs. Identifying key problmes is probably the most useful approach. But then there is an issue in accessing different data to visualise as part of the process. A great deal of data is now publicly available. But I am no data specialist and have faced a steep learning curve in understanding and interpreting the data myself. then there is the issue of visualisation – I am mainly using Google Gadgets, although we are also working with Tableau (a powerful tool, but unfortunately only available for Windows) and IBM;s Many Eyes. All these tools are good, but are all extremely finicky about how the data is formatted. We are working with data in xls and Apple’s Numbers but I suspect longer term it would be better to use the Open Source R programming environment.

And the hardest task of all is the storyboarding. At the end of the day we are trying to tell stories with data: TEBOs are a storytelling and exploration approach to learning. So for each TEBO I intend to make a short video explaining the key concepts and showing the various visualizations. We will also provide access to the raw data and to static versions of the graphing, along with explanatory notes. And for each TEBO we will try to construct an interactive visualisation tool, allowing learners to play with the data and displays. I also want to try to build some sort of simulations using the Forio tool. No doubt there is better software (and if anyone has any ideas I would be very grateful). But I sort of feel that the more social software, open source or free tools we can use the better. We want to encourage people to do it for themselves. And they have no money to spend on fancy software tools.We cannot possibly provide access to visualisations of all the data available. But if we cane explain what is possible, hopefully interested CAIG professionals will start there own work. And then who knows – a Careers Guidance data store?