Archive for the ‘LMI’ Category

Visualising jobs

April 26th, 2017 by Graham Attwell

bidigestersAs ever I am doing lots of work on labour market data and education and training. While we know pretty well how to take great slabs of data and turn it into various different charts – some more imaginative than others – this still leaves problems in how to illustrate ideas. data charts can be pretty dull – more than that they rely on the ability of the user to interpret that data – what we call the move from labour market information to labour market intelligence.

biodigester2

I have long been interested in the potential of info graphics in helping develop such intelligence but had yet to see any meaningful examples. Thus, I was very impressed with this graphic about the training and skills needs in the anaerobic digestion industry in the monthly newsletter from Cereq – the French Centre for Research Education, Training and Employment.

The only real problem is that the infographic – like many others is much too long for a small laptop screen (this I have only been able to capture parts of it). But it would be great as a poster.

Interpreting and presenting data

March 1st, 2017 by Graham Attwell

I have been working on the contents for week 4 of the free #EmployID MOOC on The Changing World of Work, taking place on the European EMMA platform and starting in late March. Week 4 is all about Labour Market Information – or as I prefer to call it, Labour Market Intelligence – and how we can use labour market data both for job seekers and young people choosing careers and by advisers and other professionals working in the careers and labour market domain.

One of the major challenges is how to represent data. This presentation, Data is beautiful: Techniques, tools and apps for sharing your results by Laura Ennis, provides some good practical advice on how to present data. It come from a talk she did at Leap Into Research 2017.

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    Online Educa Berlin

    OEB Global (formerly Online Educa Berlin) has announced its Call for Proposals and the overall theme for 2018: Learning to Love Learning. The event will incorporate Learning Technologies Germany – a leading European exhibition on learning technologies in the workplace – for the first time this year. More details here.


    Barcelona to go Open Source

    The Spanish newspaper, El País, has reported that the City of Barcelona is in the process of migrating its computer system to Open Source technologies.

    According to the news report, the city plans to first replace all its user applications with alternative open source applications. This will go on until the only remaining proprietary software will be Windows where it will finally be replaced with a Linux distribution.

    To support the move, the city will employ 65 new developers to build software programs for their specific needs. they also plan the development of a digital market – an online platform – whereby small businesses will use to take part in public tenders.


    OER18: Open to All,

    The OER18 Conference takes place in Bristol, UK on 18 – 19 April 2018. OER18 is the 9th annual conference for Open Education research, practice and policy. The final keynote has now been announced: Dr Momodou Sallah is Reader in Globalisation and Global Youth Work at the Social Work, Youth and Community Division, De Montfort University.  More about the conference: http://go.alt.ac.uk/2DmsPPu


    Learning about technology

    According to the University Technical Colleges web site, new research released of 11 to 17-year-olds, commissioned by the Baker Dearing Educational Trust, the charity which promotes and supports University Technical Colleges (UTCs), reveals that over a third (36%) have no opportunity to learn about the latest technology in the classroom and over two thirds (67%) admit that they have not had the opportunity even to discuss a new tech or app idea with a teacher.

    When asked about the tech skills they would like to learn the top five were:

    Building apps (45%)
    Creating Games (43%)
    Virtual reality (38%)
    Coding computer languages (34%)
    Artificial intelligence (28%)


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