Archive for the ‘politics’ Category

Language courses and science, technology, engineering and maths subjects cut

September 16th, 2020 by Graham Attwell
jet engine, jet, airplane

LittleVisuals (CC0), Pixabay

Over the past few years there has been great emphasis placed in the UK on the importance of science, engineering, technology and maths (STEM) for the future development of the economy. there has also been attention placed on the poor record of language learning in the country. And education – and especially the vocational further education colleges have been urged to ensure that employability is high on te agenda.

It is surprising then to see the latest report from the UK nation Audit Office which has found that “Some colleges have stopped teaching modern languages courses and some science, technology, engineering and maths subjects, while others have significantly decreased employability activities.”

As a report on Sky News says, the Aidit Office report the reason being that core funding for the college sector has fallen and its financial health “remains fragile” – with an increasing number of colleges across the UK under financial pressure due to the coronavirus crisis.

The report warned that mental health and careers support for college students had also reduced.

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Accountability and algorithmic systems

September 3rd, 2020 by Graham Attwell
programming, computer language, program

geralt (CC0), Pixabay

There seems to be a growing awareness of the use and problems with algorithms – at least in the UK with what Boris Johnson called “a rogue algorithm” caused chaos in students exam results. It is becoming very apparent that there needs to be far more transparency in what algorithms are being designed to do.

Writing in Social Europe says “Algorithmic systems are a new front line for unions as well as a challenge to workers’ rights to autonomy.” She draws attention to the increasing surveillance and monitoring of workers at home or in the workplace. She says strong trade union responses are immediately required to balance out the power asymmetry between bosses and workers and to safeguard workers’ privacy and human rights. She also says that improvements to collective agreements as well as to regulatory environments are urgently needed.

Perhaps her most important argument is about the use of algorithms:

Shop stewards must be party to the ex-ante and, importantly, the ex-post evaluations of an algorithmic system. Is it fulfilling its purpose? Is it biased? If so, how can the parties mitigate this bias? What are the negotiated trade-offs? Is the system in compliance with laws and regulations? Both the predicted and realised outcomes must be logged for future reference. This model will serve to hold management accountable for the use of algorithmic systems and the steps they will take to reduce or, better, eradicate bias and discrimination.

Christina Colclough believes the governance of algorithmic systems will require new structures, union capacity-building and management transparency.I can’t disagree with that. But also what is needed is a greater understanding of the use of AI and algorithms – for good and for bad. This means an education campaign – in trade unions but also for the wider public to ensure that developments are for the good and not just another step in the progress of Surveillance Capitalism.

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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‘.

 

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Gap between rich and poor university students widest for 12 years

July 31st, 2020 by Graham Attwell

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.

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AI and Young People

July 17th, 2020 by Graham Attwell

Last December, the Youth Department of the Council of Europe organised a seminar on Artificial Intelligence and its Impact on Young People. The aim of the seminar was to explore the issues, role and possible contributions of the youth sector in an effort to ensure that AI is responsibly used in democratic societies and that young people have a say about matters that concern their present and future. The seminar looked, among other things, into three dimensions of AI”

  • AI and democratic youth participation (including young people’s trust/interest in democracy)
  • AI and young people’s access to rights (including social rights)
  • AI and youth policy and youth work

According to the report of the seminar, the programme enabled the participants to put together their experience and knowledge in proposing answers to the following questions:

  • What are the impacts of on young people and how can young people benefit from it?
  • How can the youth sector make use of the capacities of to enhance the potential of youth work and youth policy provisions for the benefit of young people?
  • How to inform and “educate” young people about the potential benefits and risks of AI, notably in relation to young people’s human rights and democratic participation and the need to involve all young people in the process?
  • How does AI influence young people’s access to rights?
  • What should the youth sector of the Council of Europe, through the use of its various instruments and partners, do about AI in the future?

Not only is there a written report of the seminar but also an excellent illustrated report. Sadly it is not in a format that  can be embedded, but  it is well worth going to the Council of Europe’s web page on AI and scrolling to the bottom to see the report.

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European Union, AI and data strategy

July 9th, 2020 by Graham Attwell
lens, colorful, background

geralt (CC0), Pixabay

is the rapporteur for the industry committe for European Parliament’s own-initiative  on data strategy and  a standing rapporteur on the World Trade Organization e-commerce negotiations in the European Parliament’s international trade committee.

Writing in Social Europe she says:

Building a human-centric data economy and human-centric artificial intelligence starts from the user. First, we need trust. We need to demystify the data economy and AI: people tend to avoid, resist or even fear developments they do not fully understand.

Education plays a crucial role in shaping this understanding and in making digitalisation inclusive. Although better services—such as services used remotely—make life easier also outside cities, the benefits of digitalisation have so far mostly accrued to an educated fragment of citizens in urban metropoles and one of the biggest obstacles to the digital shift is lack of awareness of new possibilities and skills.

Kampula-Natri draws attention to the Finnish-developed, free online course, ‘Elements of AI’. This started as a course for students in the University of Helsinki but has extended  its reach to over 1 per cent of Finnish citizens.

Kampula-Natri points out that in the Nordic countries, the majority of participants on the ‘Elements of AI’ course are female and in the rest of the world the proportion exceeds 40 per cent—more than three times as high as the average ratio of women working in the technology sector. She says that after the course had been running in Finland for a while, the number of women applying to study computer science in the University of Helsinki increased by 80 per cent.

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Is graduate pay a true measure of the quality and relevance of courses?

July 8th, 2020 by Graham Attwell
learn, school, balloon

geralt (CC0), Pixabay

That education policy in the UK is confused is nothing new, neither given the rapid turnover in education ministers is it surprising. But the latest turn, although rhetorical at the moment, is both strange and worrying.

In the last two weeks both the Prime Minister, Boris Johnson, and the Education Minister Michelle Donelan have criticised the quality and relevance of university courses. Johnson talked about “low-value courses” in his major set-piece speech on economic recovery post-Covid-19 while Donelan said that too many students “have been misled by the expansion of popular sounding courses” with what she described as poor standards and “no real demand from the labour market”.

Clearly most of this rhetoric is ideological. Johnson is talking about more funding for Further Education Colleges, which have been starved of funding through the period of austerity. However, it is being suggested that one motive may be that university cities tend to vote Labour, but in many of the towns in which the Conservatives won new seats in the election last November, there are not universities but are Further Education colleges.

To justify the talk of low value and poor quality courses the government produce various data as evidence. There are different surveys looking at issues related to satisfaction and student outcomes. The first is the student satisfaction survey conducted in every university. Although comprehensive it is doubtful that this survey has much greater validity than the happy sheets I used to hand out at the end of staff development workshops. Universities go to great lengths to make sure students are happy, through various gimmicks and social events.

The Graduate outcomes for all subjects by university (LEO) survey is undertaken by the Office of National Statistics (ONS). It surveys the employment and earnings of higher education graduates using matched data from different government departments. It is interesting that the ONS describes the survey ads “experimental.”

Although interesting the sheer number of variables impacting on graduate earnings after finishing at university render the findings meaningless when compared to subject sample sizes. After Donelan’s speech, former universities minister Jo Johnson tweeted salary data is about as useful a guide to course quality as an MP’s majority.

Of course, one of the “experimental” findings is that students undertaking STEM subjects have higher earnings that those doing humanities and arts. And the strong suspicion it is humanities and arts courses that Johnson and Donelan are firing at.

Many would probably argue that earnings are not the best proxy for judging course quality in any case. But it is interesting that the Graduate Outcomes survey, through a series of reflective questions. found that graduates of creative arts courses are more likely to be using skills learned during their course in employment than their peers who studied maths, biology, or physics.

 

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What policies are needed to respond to the recession?

June 19th, 2020 by Graham Attwell
architecture, skyscraper, glass facades

MichaelGaida (CC0), Pixabay

I attended an excellent webinar on Thursday from the UK Centre for Cities. The webinar, presented by Elena Begini and entitled ‘How will the recession affect different parts of the country?’, provided an analysis of the latest labour market data, both around the numbers unemployed and those furloughed and receiving government funding.

Elena explained that in the first month between March and April there was very rapid increase in the numbers employed and furloughed but of the main impact Covid 19 crisis was on those cities with weaker economies mostly in the north of England

Between April and May the increase in unemployment was slower. But in this month, it was the stronger city economies in the south of England that were hard hit. London and Basildon both joined the 20 hardest hit cities in terms of unemployment COVID 19 has spread out across most cities. Interestingly those cities hardest hit by unemployment are also those with the most furloughed workers. To a certain extent this depends on whether jobs in a city are able to be undertaken from home. In Wales Cardiff and Swansea have relatively lower rates of both unemployment and furloughed staff whilst in Newport the rates are higher, presumably reflecting a higher percentage of office worker in Cardiff and Swansea while a higher percentage of industrial enterprises in Newport.

These broad trends are also reflected in the percentage of self-employed workers who have applied for government assistance.

Type of employment is important. Crawley and Reading are both major and previously relatively economically strong cities close to London. But while Reading has (only!) 25 percent of jobs hit by the recession, Crawley has 38 per cent reflecting the importance of the aerospace industry (and particularly Gatwick airport) to the city.

It also should be noted that all cities have fast rising unemployment of young people although once more there is wide variation, for instance very high rates in northern cities and relatively low rates in Oxford and Cambridge.

One of the strengths of the Centre for Cities is that they not only analyze the data but put forward policy measures o respond to the research. Elena suggests the scale of the recession means there is an urgent need for active intervention. Austerity is not an option.

But because of the different trajectories in different cities the policy response needs to be differentiated.

For those cities which are relatively strong economically, there is the potential for a quick “bounce back”. This requires enhanced career support both for those seeking jobs for which they are already qualified or for employment in jobs with similar skill requirements.  Secondly there is the need for grants for those seeking retraining or upskilling (and also courses are needed to support this). For places with weaker economies the priority is job creation with a particular focus on the green economy and on infrastructure development.

I have written this from my notes taken during the webinar so apologies for anything I have missed or for misreporting. A recording of the webinar is available for the Centre for Cities web site together with the data and their analysis.

 

 

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Vocational courses not advanced enough

June 12th, 2020 by Graham Attwell
training, education, vocational training

geralt (CC0), Pixabay

The Centre for London, a ‘think tank’ for the English capital, has released an interesting new report on further education in London.

The report finds that further education in London is hampered because:

  • It is underfunded: there are more learners in Further Education than in Higher Education in London, but spending on adult education, apprenticeships and other work-based learning for over 18s has fallen by 37 per cent since 2009/10.
  • There are not enough learners: the proportion of working age Londoners in Further Education has fallen by over 40 per cent since 2014 – only one in 13 Londoners were in further education in 2019.
  • Funding can be restrictive: grants for learners and colleges have been reduced or replaced with loans, and providers continue to be funded by annual contracts based on the number of learners in the previous year.
  • Making savings impacts teaching: As of February 2019, 29 per cent of London’s colleges were Ofsted rated as requiring improvement or inadequate, compared to just six per cent of London’s schools.
  • Courses are not advanced enough: 99 per cent of learners are taking courses at level 3 or below (equivalent to A-Level) and three quarters at level 2 (equivalent to GCSE) or below.
  • There are not enough new apprentices: Despite government investment in apprenticeships, London has half as many apprenticeship starts as the rest of the UK, and many of these new starters are not new to the labour market.
  • It has not responded to employers’ needs: the number of learners and apprentices in areas with skills shortages has barely changed since 2014/15.

The fall in the number of learners is worrying, but only to be expected given the sharp fall in funding for FE. Nevertheless a better understanding of what exactly is going on would be further data regarding how many people in London are participating in learning. It is possible that part of the fall is due to people pursuing online programmes, although I doubt that this accounts for all of the shortfall.

I am not convinced by the finding that FE has not responded to employers needs – in the long time I have been involved with vocation education and training employers have always said that (although I suppose it is possible that VET provision has never met employers needs).

The point about courses not being advanced enough is one that I have heard in other parts of the UK. I wonder if it is because it is more expensive to provide more advanced courses, or simply that many learners are not equipped to start on more advanced provision.

 

 

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No Justice, No peace

June 3rd, 2020 by Graham Attwell

This video was made almost two years ago. It seems prophetic today.

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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.

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    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.

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    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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    News from 1994

    This is from a Tweet. In 1994 Stephen Heppell wrote in something called SCET” “Teachers are fundamental to this. They are professionals of considerable calibre. They are skilled at observing their students’ capability and progressing it. They are creative and imaginative but the curriculum must give them space and opportunity to explore the new potential for learning that technology offers.” Nothing changes!

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