Archive for the ‘Wales Wide Web’ Category

Understanding the changing Covid-19 labour market

August 26th, 2020 by Graham Attwell
looking for a job, work, silhouettes

geralt (CC0), Pixabay

Yesterday I attended a webinar organized by the UK Association of Colleges in their Labour Market Observatory Series. The subject of the webinar was Using Job Posting Analytics to understand the changing Covid-19 labour market.

Understanding labour markets is a hard job at the best of time and the Covid-19 pandemic and the resulting lockdown have disrupted the economy with unprecedented speed and scale. As Duncan Brown, Senior Economist from Emsi, explained, raditional labour market statistics take time to emerge, especially to understand what’s going at regional and local level, and real-time indicators become all-important. Duncan Brown, talked through what their Job Posting Analytics – derived from collecting (or scraping) around 200,000 new, unique job postings from job boards across the internet every week — can tell us about where and how the labour market is changing and what to look for as we move into the recovery.

First though he explained how the data is collected using bots before being cleaned and duplication removed, prior to using algorithms to analyse the data. He pointed out that there are limitations to the data derived from job adverts but compared to the time taken for official labour market data to emerge, for instance through the UK National Office of Statistics Labour Force Survey (LFS)job posting analytics can provide an almost real time snapshot view of the labour market, and is easily projected at a local level.

My notes on the webinar are somewhat patchy but here are a few take home points, particularly from a question and answer session that followed Duncan Brown’s presentation.

There was a huge fall in online job adverts in April and May with the lockdown – as high as 80 per cent in some sectors and localities. Since then there has been a steady recovery in the number of jobs being advertised online but this recovery is uneven between different sectors and different cities and regions.

As examples offers of employment in the food and hospitality. Industries remain dire and aerospace is also still badly hit. On the other hand, job advert volumes in manufacturing have substantially recovered and, perhaps understandably there is an increase in jobs adverts in health care.

There is considerable differences as to how far the volume of job adverts has recovered (or otherwise) in different cities. In general, it would appear that those cities with the largest percentage of office work and of commuters are doing worse: London in particular.

One area of the labour market that Emsi is focusing on is skills demand. They have developed their own skills directory, which Duncan Brown said, now contains over 3000 skills and are running a project funded by Nesta to see if these skills can be clustered around different occupations. Yet despite the so-called pivot to skills, he said there few signs that employers were. Moving away from the traditional emphasis on qualifications. However, qualification demands often did not appear in job adverts but rather tended to be assumed by both employers and job applicants. For instance, someone applying for a job as an accountant would presume that they needed formal qualifications.

Although there have long been predictions over the impact of automation and AI on employment, Duncan Brown said there was little evidence of this. His feeling is that, at least in the UK, the existence of relatively cheap labour in many sectors where it would be relatively easy to automate tasks, was a disincentive to the necessary investment. He thought that labour costs may have been kept down by immigration. He pointed to car washes as an example of an area where far from advancing automation had actually gone backwards.

The slides from the presentation and a recording of the webinar will be available from 27 August on the Association of Colleges website.

 

Marginal voices and non-dominant epistemic stances in open education

August 20th, 2020 by Graham Attwell

One way or another I have been involved in the open education debate for many years. Pontydysgu were a partner in the first projects Cover image for Open at the Marginssponsored by the European Commission to promote firstly open source software and subsequently open educational resources. And since then, some fifteen or so years ago we have published everything under a Creative Commons license. And slowly over the years the debate has shifted, over the past years looking at the meaning of open education practices.

More recently a debate has emerged over diversity and over non-dominant epistemic stances in open education. Now, many of those voices in the debate have contributed to an open book entitled Open at the Margins with the subtitle: Critical Perspectives on Open Education. The book is edited by Maha Bali, Catherine Cronin, Laura Czerniewicz, Robin DeRosa, and Rajiv Jhangiani and is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

The description of the book says:

Open education is at a critical juncture. It has moved on from its northern roots and is increasingly being challenged from its own periphery. At the same time, it finds itself marginalised and under threat in an educational sector infiltrated by corporate interests. However, rather than bunkering down, becoming blinkered or even complacent, the editors of this volume believe that the voices from the periphery should be amplified. This book represents a starting point towards curating and centering marginal voices and non-dominant epistemic stances in open education, an attempt at critical pluriversalism. It is a curated collection of 38 blog posts, lectures, talks, articles, and other informal works contributed by 43 diverse authors/co-authors and published since 2013. Each of these contributions offers a perspective on open education that can be considered marginal and that challenges the dominant hegemony.

The book is free for download from the Rebus Community website. I havent read it yet but its on my list for this weekend. If it lives up to its description it is a very welcome and necessary contribution to the debate.

 

AI and Algorithms: the UK examination debacle

August 20th, 2020 by Graham Attwell

This article was originally published on the Taccle AI web site.

There’s a lot to think about in the ongoing debacle over exam results in the UK. A quick update for those who have not been following the story. Examinations for young people, including the O level and A level academic exams and the more vocationally oriented Btec were cancelled this year due to the Covid19 pandemic. Instead teachers were asked to firstly provide an estimated grade for each student in each subject and secondly to rank order the students in their school.

These results were sent to a government central agency, the Office of Qualifications known as Ofqual. But instead of awarding qualifications to students based on the teachers’ predicted grades, it was decided by Ofqual, seemingly in consultation or more probably under pressure, by the government to use an algorithm to calculate grades. This was basically based on the previous results achieved by the school in each subject, with adjustments made for small class cohorts and according to the rankings.

The results from the A levels were released last week. They showed massive irregularities at an individual level with some students seemingly downgraded from predicted A* *the highest grade, to a C or D. Analysis also showed that those students from expensive private schools tended to do better than expected, whilst students from public sector schools in working class areas did proportionately worse than predicted. In other words, the algorithm was biased.

As soon as the A level results were announced there were protest from teachers, schools and students. Yet the government stuck to its position, saying there would be no changes. The Prime Minister Boris Johnson said “Let’s be in no doubt about it, the exam results wed have got today are robust, they’re good, they’re dependable for employers”. However, concern quickly grew about the potential of numerous appeals and indeed at the time it would take teachers preparing such appeals. Meanwhile the Scottish government (which is autonomous in education policy) announced that they would revert of the teachers’ predicted grades. In England while the government stood firm demonstrations by school students broke out in most cities. By the weekend it was clear that something had to change and on Monday the UK government, responsible for exams in England and Wales, announced that they too would respect teacher predicted grades.

The political fallout goes on. The government is trying to shift the blame to Ofqual, despite clear evidence that they knew what was happening.  Meanwhile some of the universities who are reliant on the grades for the decision over who to offer places to, are massively oversubscribed as a result of the upgrades.

So, what does this mean for the use of AI in education. One answer maybe that there needs to be careful thinking about how data is collected and used. As one newspaper columnist put it as the weekend “Shit in, shit out”. Essentially the data used was from the exam results of students at a collective school level in previous years. This has little or no relevance as to how an individual student might perform this year. In fact, the algorithm was designed with the purpose not of awarding an appropriate grade for a student to reflect their learning and work, but to prevent what is known as grade inflation. Grade inflation is increasing numbers of students getting higher grades each year. The government sees this as a major problem.

But this in turn has sparked off a major debate, with suspicions that the government does in fact support a bias in results, aiming to empower the elite to attend university with the rest heading for a second class vocational education and training provision. It has also been pointed out that the Prime Ministers senior advisor, Dominic Cummings, has in the past written articles appearing to suggest that upper class students are more inherently intelligent than those from the working class.

The algorithm, although blunt in terms of impact, merely replicated processes that have been followed for many years (and certainly preceding big data). Many years ago, I worked as a project officer for the Wales Joint Education Committee (WJEC). The WJEC was the examination board for Wales. At that time there were quite a number of recognized examination boards, although since then the number has been reduced by mergers. I was good friends with a senior manager in the exam board. And he told me that every year, about a week before the results were announced, each exam board shared their results, including the number of students to be awarded each grade. The results were then adjusted to fit the figures that the boards had agreed to award in that year.

And this gets to the heart of the problems with the UK assessment system. Of course, one issue is the ridiculous importance placed on formal examinations. But it also reflects the approach to assessment. Basically, there are three assessment systems. Criteria based assessment means that any students achieving a set criterion are awarded accordingly. Ipsative based assessment, assesses achievement based on the individuals own previous performance. But in the case of UK national exams the system followed is norm referenced, which means that a norm is set for passing and for grading. This is fundamentally unfair, in that if the cohort for one year is high achieving the norm will be raised to ensure that the numbers achieving any particular grade meet the desired target. The algorithm applied by Ofqual weas essentially designed to ensure results complied with the norm, regardless of individual attainment. It has always been done this way, the difference this year was the blatant crudeness of the system.

So, there is a silver lining, despite the stress and distress caused for thousands of students. At last there is a focus on how the examination system works, or rather does not. And there is a focus on the class-based bias of the system which has always been there. However, it would be a shame if the experience prevents people from looking at the potential of AI, not for rigging examination results, but for supporting the introduction of formative assessment or students to support their learning.

If you are interested in understanding more about how the AI based algorithm worked there is an excellent analysis by Tom Haines in his blog post ‘A levels: the Model is not the Student‘.

 

Evolving Education and Careers: Share, Learn and Transform

August 3rd, 2020 by Graham Attwell

The job markets were already looking problematic at the start of the year. Researchers and policy makers alike were warning that automation and Artificial Intelligence were leading to changes in the tasks undertaken in different occupations, requiring new skills and competences. Employment in some occupations were threatened by these developments. This was resulting in the need for enhanced Careers Advice, Information and Guidance, in particular ensuring that adults has access to such services to help them transition to new jobs.

Now this has been amplified by the Covid019 pandemic. Many people’s jobs are furloughed, others have lost their jobs. The prospects for young people and graduates entering the labour market are particularly grim.

From 20 – 22 October DMH Associates are organizing a major online conference looking at these issues and more.

The conference web site explains that the world has experienced major economic, social and technology impacts. Societies everywhere are undergoing deep transformation.

Climate change, an ageing workforce and skills gaps are major issues that governments need to address. Only time will tell what the impact of the current health crisis will have in the medium and long-term. As a consequence, careers will evolve in response to a dynamically changing environment. How will this affect jobs, training, employment, the gig economy and/or unemployment in the future? We will be exploring forward-thinking approaches to careers support systems drawing on international good and interesting policies and practices.

For leaders, educators, career development, HR and employment specialists a fundamental question is: – how best can individuals be better prepared to adapt and prosper through lifelong learning and work? Individuals’ must be well equipped with the mindsets and tools they need to find and benefit from purposeful learning and work opportunities. Organisations working with young people and/or adults in differing contexts will need agile responses to meet citizens’ needs.

With all this in mind, time away to network with experts and like-minded colleagues is just what the doctor ordered. This year’s theme is Evolving Careers. Delegates will learn from experts and peers whilst sharing experiences, research and best practice to take back to the day job of helping to transform people’s lives.

The conference content includes international keynote speakers and breakout sessions hosted by leading experts and contributors

Session topics include:

  • Career-related learning in primary schools
  • An evolving curriculum in secondary, tertiary, vocational education and training (VET) and higher education settings
  • Future scoping careers
  • Digital innovations
  • Building Partnerships
  • How to Make a Difference to Those That Need Support Most
  • Youth Transitions: Creating Pathways to Success
  • Adults in the workplace
  • Labour markets: where next?
  • Tackling unemployment
  • Lifelong guidance
  • Social inclusion

Registration for the conference costs £25. There are already 210 delegates registered to attend from the UK, Ireland, Canada, Dubai, Australia, New Zealand, Germany, The Netherlands, Turkey and the USA.

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    Cyborg patented?

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    Racial bias in algorithms

    From the UK Open Data Institute’s Week in Data newsletter

    This week, Twitter apologised for racial bias within its image-cropping algorithm. The feature is designed to automatically crop images to highlight focal points – including faces. But, Twitter users discovered that, in practice, white faces were focused on, and black faces were cropped out. And, Twitter isn’t the only platform struggling with its algorithm – YouTube has also announced plans to bring back higher levels of human moderation for removing content, after its AI-centred approach resulted in over-censorship, with videos being removed at far higher rates than with human moderators.


    Gap between rich and poor university students widest for 12 years

    Via The Canary.

    The gap between poor students and their more affluent peers attending university has widened to its largest point for 12 years, according to data published by the Department for Education (DfE).

    Better-off pupils are significantly more likely to go to university than their more disadvantaged peers. And the gap between the two groups – 18.8 percentage points – is the widest it’s been since 2006/07.

    The latest statistics show that 26.3% of pupils eligible for FSMs went on to university in 2018/19, compared with 45.1% of those who did not receive free meals. Only 12.7% of white British males who were eligible for FSMs went to university by the age of 19. The progression rate has fallen slightly for the first time since 2011/12, according to the DfE analysis.


    Quality Training

    From Raconteur. A recent report by global learning consultancy Kineo examined the learning intentions of 8,000 employees across 13 different industries. It found a huge gap between the quality of training offered and the needs of employees. Of those surveyed, 85 per cent said they , with only 16 per cent of employees finding the learning programmes offered by their employers effective.


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