Archive for the ‘Data’ Category

Living in an Algorithmic World

May 4th, 2018 by Graham Attwell

This video is from Danah Boyd’s opening keynote for the re:publica 18 conference. Although it is an hour long it is well worth watching. Danah says “Algorithmic technologies that rely on data don’t necessarily support a social world that many of us want to live in. We must grapple with the biases embedded in and manipulation of these systems, particularly when so many parts of society are dependent on sociotechnical systems.” That goes for education just as much as any other part of the social world.

Designing Learner Dashboards

May 2nd, 2018 by Graham Attwell


The UK Jisc are really good at producing on line reports of workshops and meetings (something which I am not!). This is one of the presentations from the Student Experience Experts Group meeting, two of which  events held every year to share the work of the student experience team at Jisc and to offer opportunities for feedback and consultation on current activities. The Jisc web page provides a brief summary of the meeting and all of the presentations. I picked this one by Liz Bennett from the University of Huddersfield because the issue of how to design dashboards is one which perplexes me at the moment.

Student satisfaction unrelated to learning behaviour and academic performance

March 13th, 2018 by Graham Attwell

I seem to spend a lot of time lately moaning about bad data practices. About approaches to learning analytics which appear to be based on looking at what data is available and the trying to think out what the question is. And particularly over the different proxies we use for learning.

So, I particularly liked the report in THE of the inaugural lecture by Professor Rienties at the UK Open Universitity’s Institute of Educational Technology. Professor Rienties outlined the results of a study that examined data on 111,256 students on 151 different modules at his institution. He found that student satisfaction, one of the most common used proxies for learning and achievement, is “unrelated” to learning behaviour and academic performance. According to THE:

Significantly higher student satisfaction was found in modules in which students received large amounts of learning materials and worked through them individually, than in courses where students had to collaborate and work together.

However, the best predictor for whether students actually passed the module was whether there were collaborative learning activities, such as discussion forums and online tuition sessions.

Students who were “spoon-fed” learning materials also spent less time in the virtual learning environment, were less engaged, and were less likely to remain active over time than their peers engaged in more collaborative activities.

Happy birthday, Graham Attwell!

February 16th, 2018 by Pekka Kamarainen

Today the fellow-bloggers on Pontydysgu site can congratulate Graham Attwell on his birthday. I hope there is no home-made rule that would prevent us from celebrating this day via his own website.  Cheers, Graham!

Years and more …

Why is there such a big gender difference in graduate employment

June 16th, 2017 by Graham Attwell

salaries grad

In our work on Labour Market Information Systems, we frequently talk about the differences between labour market information and labour market intelligence in terms of making sense and meanings from statistical data. The graph above is a case in point. It is one of the outcomes of a survey on Graduate Employment, undertaken by the UK Higher Education Statistics Agency (HESA).

Like many such studies, the data is not complete. Yet, looking at the pay by gender reveals what WONKHE call “a shocking picture of the extent of the pay gap even straight out of university, and how different subject areas result in a diverse range of pay differences.”

Understanding why there is such a gap is harder. One reason could be that even with equal pay legislation, employers simply prefer to employ male staff for higher paid and more senior jobs. Also, the graph shows the subject in which the students graduated, not the occupational area in which they are employed. Thus the strikingly higher pay for mean who undertook nursing degrees may be due to them gaining highly paid jobs outside nursing. Another probable factor in explaining some of the pay gap is that the figures include both full and part time workers. Nationally far more women are employed part time, than men. However, that explanation itself raises new questions.

The data from HESA shows the value of data and at the same time the limitations of just statistical information. The job now is to find out why there is such a stark gender pay gap and what can be done about it. Such ‘intelligence’ will require qualitative research to go beyond the bald figures.

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.

New Insights into UK society today from longitudinal research

December 8th, 2016 by Graham Attwell

Understanding Society has published its fifth annual report highlighting some of theinsights new topical policy-relevant research conducted recently using data from the annual survey which began in 2009 with around 100,000 individuals from 40,000 households.

To support the Insights 2016 launch, the team also published a topic guide on education. This guide explores the content available to analyse in Understanding Society, highlights the types of research questions which could be explored and what research has already been carried out.

Making sense of data about education and jobs

June 6th, 2016 by Graham Attwell

restorer
High or low skills? Graduate job or not?

For a number years now I have been working on projects developing the use of open data for careers counselling, advice and guidance. This work has been driven both by the increasing access to open data but also by the realisation of the importance of Labour Market Information (LMI) for those thinking about future education and / or jobs. And of course with high levels of job insecurity, such thinking becomes more urgent and in an unstable economy and labuor market, more tricky.

Yet even if we clean the data, add it to a database, provide and open API for access and develop tools for data visualisation, interpretation is still not easy. Here is one case, taken from this mornings Guardian newspaper.

employment graph

 

Although the article is using the chart to show the rapid growth in knowledge intense occupations, I am not sure it does. Assuming that these are percentage change based on the original job totals, it probably show growth in low skilled jobs is far outstripping high skilled work, especially in the last 12 months. And that is taking into account that (once again probably) most job loss due to technology is focused din low skilled areas – e.g the quoted 70,00 jobs lost in supermarket check outs due to automation.

I am also interested to see from wonkhe that “The Higher Education Statistics Agency (HESA) who have been running the Destination of Leavers Survey (DLHE) and its predecessors for 21 years, are now consulting widely on the future of assessing graduate outcomes.” For some time now there has been disquiet about the numbers of graduates working in ‘non graduate’ jobs. And that raises questions – just like the graph above focusing on high skills occupations – on just what a graduate job is. André Spicer, professor of organisational behaviour at the Cass Business School, City University London has cited “studies suggesting that the jobs which require degree-educated employees have peaked in 2000 and may be going down” and notes that many people apparently employed for their high-level specialist skills end up doing sales and marketing or fairly routine generalist work.

All this of course is highly subversive. Officially we are moving towards a high skilled economy needing more graduates and requiring higher level apprenticeships. My feeling in country slick Spain with high youth unemployment is what we need are apprenticeships in areas like construction and hospitality – both because they are sectors which can provide employment and also where higher skills are desperately needed to improve quality and productivity. Yet for governments there is an awful temptation to launch programmes in new ‘sexy’ areas  like games technologies despite the scarcity of jobs in these fields.

Tensions in Learning Analytics

May 27th, 2016 by Graham Attwell

The debate around Learning Analytics seems to be opening up. And although there is little sign of agreement over future directions, the terms of discussion seem both broader and more nuanced than previously. I think some of this is in response to the disillusionment of early researchers and adopters.

In yesterdays OLDaily, Stephen Downes pointed to an excellent article by Bodong Chen. Bodong points to the surge of interest in Learning Analytics but cautions that: “The surge of this nascent field rests on a promise–and also a premise–that digital traces of learning could be turned into actionable knowledge to promote learning and teaching.

He suggests that: “One approach to understanding learning analytics is to recognize what are not learning analytics” including academic analytics and educational data mining. Instead, he says “learning analytics is more directly concerned with teachers and learners by attending to micro-patterns of learning.”

Bodong draws attention to a tension between learning and analytics “as two pivotal concepts of the field” He points out that “learning analytics deals with educational phenomena at multiple levels”. As an example he says: “collaborative knowledge building as a group phenomenon depends on contributions from individuals, but cannot be reliably inferred from individual learning.”

Understanding and accepting that “the meaning of learning analytics as a term is plural and multifaceted” is an important basis for future research. Within the only just emerging field of workplace Learning Analytics, not only is there the issue of individual and collaborative learning and knowledge development but also issues around proxies for learning. Whilst performance in practice might be seen as a possible proxy, performance may also be seen to involve a wider range of factors, including the working environment, the division of work and opportunities for practice. And the already established field of Performance Analytics seems at considerable tension to learning.

Lack of proxies a problem for Workplace Learning Analytics

May 3rd, 2016 by Graham Attwell
I’ve been spending a lot of time thinking about Learning Analytics lately and this is the first of four or five short posts on the subject. Its all been kicked off by attending the Society of Learning Analytics pre conference workshops last week – LAK16 – in Edinburgh. Sadly I couldn’t afford the time and money to go to both the workshops and the full conference but many of the presentations and papers from the conference are already viable online.
My interest in Learning Analytics stems from the EmployID project which is aiming to support scalable and cost-effective facilitation of professional identity transformation in public employment services. And in our project application under the EU Research Framework (Horizon 2020) we said we would research and develop Learning Analytics services for staff in Public Employment Services. Easier said than done! An early literature review revealed that despite present high levels of interest (hype?) in Learning Analytics in formal education there has been very little research and development in Workplace Learning Analytics: therefore my excitement at a workshop on this subject at LAK16. But sadly despite the  conference selling out with 400 attendees, we only had four papers submitted for the workshop and just 11 attendees. What this did allow was a lot of in-depth discussion, which has left me plenty of issues to think about. And of course one of the issues we discussed was why there is apparently so little interest in Workplace Learning Analytics. It was pointed out that there have been a number of work oriented presentations in previous LAK conferences but these had remained isolated with no real follow up and with no overall community emerging.
There was also a general feeling that the Learning Analytics community was weak in terms of learning theory and pedagogy, both of which were censored central to Workplace Learning Analytics. But perhaps most importantly Learning Analytics approaches in schools and Higher Education lean heavily on proxies for learning, for instance examination results and grades. With the lack of such proxies for learning in the workplace, Learning Analytics has to focus on real learning – usually in the absence of a Learning Management System. And that is simply very hard to design and develop.Yet having said that, most if not all of us in the workshop were convinced that the real future of Learning Analytics in in the workplace, with a focus on understanding learning including informal learning and improving both learning and the environment in which it occurs.
We agreed on some modest next steps and will be launching a LinkedIn Group in the near future. In the meantime the papers and presentation from the workshop can be found at http://learning-layers.eu/laforwork/.
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    Adult Education in Wales

    Learning and Work Institute is organising this year’s adult learning conference in partnership with the Adult Learning Partnership Wales. It will take place on Wednesday, 16 May 2018 at the Cardiff City Stadium.

    They say “Changing demographics and a changing economy requires us to re-think our approach to the delivery of learning and skills for adults. What works and what needs to change in terms of policy and practice?

    The conference will seek to debate how can we respond to need, grow participation, improve and measure outcomes for citizens, and revitalise community education.”


    Industry 4.0

    The UK Education Select Committee has launched an inquiry into the challenges posed and opportunities presented by the Fourth Industrial Revolution.The Committee is inviting written evidence on:

    • The interaction between the Government’s industrial, skills and digital strategies
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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.


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