Category Archives: Mature

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.

After the event – what are the lessons from organising the Bremen Mobile Learning Conference?

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Just a few quick comments about the Mobile Learning Conference Bremen, which took place last week. By all accounts it was a big success – at least if the feedback from participants is to be believed. And I enjoyed it greatly.We had about one hundred delegates – from 19 different countries according to Judith Seipold. What were the lessons for the future?

1. The conference theme – ‘Mobile Learning: Crossing boundaries in convergent environments; allowed us to look at learning from a  number of different perspectives including from pedagogy, the arts and entertainment as well as from technology. As learning is embedded in ever wider contexts these perspectives can provide us with a richer and wider perspective on our work.

2. The venue is important. Although it raised some eyebrows when we said we were holding the conference in a youth hostel – the deign and location of the building – allowing different interlinked spaces with lots of light and right by the river (with a sun terrace) – facilitated informal discussions and learning linking the formal presentations and workshops with that valued ‘out of conference’ time.

3. Conferences do not need to be so expensive. We only charged 50 Euro per delegate and provided free access to students. How did we do it? Firstly the youth hostel gave us an excellent deal – considerably cheaper, I suspect, than we would have been charged by purpose built conference venues or by universities. And it was a no frills conference – no gala dinner and no free iPads. We managed all the administration ourselves using free or open source software – EasyChair, Twitter, Google forms etc. (The most tricky bit was negotiating with PayPal which took for ever).We begged and borrowed equipment.

Ok it was a bit touch and go – we haven’t paid everything yet but my guess is we will make a profit of about 45 Euro. But if we can do it so can others – the cost of conferences at the moment excludes many people resulting in a poorer discussion.

3. We encouraged multiple formats including workshops and demonstrations. the poster sessions was particularly good. And although the multiple strands meant some of the sessions were quite small it was those sessions which in my experience were the most interesting.

I think we still have some way to go in integrating unconferencing sessions properly in the agenda. Unconferencing takes a lot of organization and facilitation. But perhaps we should stop thinking about a dichotomy between conferencing and unconferencing and look at how we can encourage the maximum involvement and participation in all of our work.

4. We have got some sort of record of our conference on Cloudworks. But that took a lot of work and we need to look again at how we can pull together diverse information sources from the different places – slideshare, twitter, blogs etc which people use to show their work and ideas. This links back to the idea of how we amplify conferences and events.

5. We had a relatively small local organising committee. This has pros and cons. On the good side this allowed us to work together informally and intensely. On the down side it resulted in a few individuals ending up with a lot of work. We also had recruited a lot of reviewers prior to the conference which spread out the time consuming work of reviewing proposals. And we were extremely lucky to be able to draw on support from students from the local university who did this work for free as part of their studies.

And people are already asking about next years conference. I think we should do it again. But one suggestion is we might stick with the Crossing Boundaries theme but move on with the technology. After all mobiles are not alone in crossing those boundaries!

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.

Barriers to elearning in Small and Medium Enterprises

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I have been doing some thinking recently on the use of technology for learning in Small and Medium Enterprises (SMEs). Or rather the lack of it. Some six or seven years ago we did a project on this finding that although there was much use of technology for informal learning, there was very little awareness, take up or implementation of elearning systems in SMEs (the book of the project is available on our publications page).
Since then there has been considerable public expenditure in Europe encouraging the enhanced use of technology for learning. Small and Medium Enterprises are seen as a key sector for creating employment and for innovation. Training and Continuing Professional Development are critical to innovation and the growth of SMEs. SMEs do not provide sufficient training because they cannot spare the time for staff to attend external training programmes and because internal training is too expensive. Therefore use elearning – so goes the logic. But the logic is clearly flawed. SMEs have not rushed to embrace the possibilities of elearning, despite pubic subventions. So what are the barriers and constraints. The following list is based on a series of meetings and consultation albeit in the somewhat specialist field of careers guidance, which, in England, is organised through private careers companies under contracts with local and national government. Indeed, one of the problems, I think, is that we have tended to treat SMEs as a homogeneous entity, whilst, in reality, the possibilities and approach in different sectors varies greatly and there is also big differences between an SME of 250 workers (the EU says an SME is any organisation employing less than 300 staff) and small enterprises with say 8 or ten staff.

  1. Lack of resources. Lack of formal based learning courses or resources. Most training programmes and Continuing Professional Development opportunities are face to face. This may reflect culture, lack of awareness of potential of e-learning and lack of technically proficient specialists to develop e-learning resources, plus of course the cost of producing high quality learning materials.
  2. Poor infrastructure. Many careers companies have a poor network infrastructure and are using out of date computers with even more out of date web browsers etc. Furthermore many of companies have set up heavy firewalls preventing access to social networking sites.
  3. Lack of competence or confidence in use of computers by some careers advisers. May be some reluctance by staff to become involved in elearning.
  4. Lack of awareness by senior managers and staff development officers of potential of elearning. Lack of local champions for change
  5. Despite all these problems and barriers, most careers advisers use computers as part of their everyday job. There are requirements to use networked systems for record keeping. In addition many use the computers for informal learning and especially for browsing for resources, also using the computer in direct work with clients. However such activity is not viewed by managers as ‘learning’ neither is it accredited.
  6. Lack of time. It is difficult to persuade managers to provide time for informal (or formal) online learning, especially given present financial climate. Many do appear to use computer for work purposes at home and in their own time.
  7. Cost. Many online resources are expensive and at present careers services are under heavy financial pressure. Is also worth noting that practices of companies in paying for online access by say mobile phone varies greatly. Staff may be unwilling to use mobile devices if are expected to pay themselves.
  8. Confidentiality. Much of the work is confidential. This may mitigate against the use of open social software networks.
  9. Organisational structures. Careers companies have to bid for contracts and may be unwilling to share learning opportunities or resources with other companies who may be perceived as competitors.
  10. Lack of functionality to share informal learning. Are only limited networks and community applications for sharing learning. there are some signs this may be changing but most learning is hared and disseminated face to face or by email.
  11. Much of the work of careers advisers take place outside the office. Access to resources including internet may be limited.

These barriers could be categorised as social, pedagogical, organsiational and technological. In reality the different categories probably reinforce each other and overlap. But each area needs to be addressed if progress is to be made.

I would be interested in other opinions as to barriers in developing elearning in SMEs – in this or other sectors

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?