geralt (CC0), Pixabay

There is a bit of a buzz going on at the moment around micro credentials. At the European Distance Learning Network (EDEN) annual conference this week, not only did Anthony Camilleri from the European MicroHE project deliver a keynote presentation on micro credentials but there was three follow up sessions based on the work of the projects

Anthony Camilleri says that “HEIs are increasingly confronted with requests from learners to recognize outside learning such as MOOCs as credit towards a degree. For those, students look for the most prestigious and up to date learning opportunities, which they often find online.” He believes the “recognition of micro-credentials can enhance student motivation, responsibility and determination, enabling more effective learning.”

However, it is noted that there remain barriers to the widespread development of micro credentials. These include scaling procedures for the recognition of prior learning, the emergence of parallel systems of credentials and open courses offered by universities do not necessarily award recognised forms of credit.

The MicroHe project is proposing a harmonised European approach to recognizing and transferring open education digital credentials thus enabling virtual student mobility, and “empowering students to adapt their learning portfolio to changing labour market demands and new technological trends.”

A further argument put forward for Microcredentials is that they provide “an alternative approach towards handling the development needs of the modern-day learner, not only helping individual competence development but also offer increased flexibility and personalization.”

Although the COVID crisis has focused attention on the potential (and possibly, the necessity) of digital course provision a major driver which predates the crisis is the speed of development of automation and AI. There are different predictions of the impact on jobs and perhaps more importantly the tasks with jobs. This diagramme is from a forthcoming publication produced for the Taccle AI project.

But, however it plays out, it seems likely that there will be a need for retraining or upskilling for a significant number of people, and also that there will be increasing demand for highly skilled workers. Microcredentials may well be part of the answer to this need and universities could have a key role in providing online education and training.

However, the question of who pays will be critical. It is interesting that FurtureLearn, the MOOC consortium led by the UK Open University, is getting in on the action. Previously attempts to monetarize their MOOCs has been through charging a fee for certification or extended access to content. But in a email circular this week they announced a new MOOC, run in conjunction with Tableau.

In the age of analytics, transforming large datasets into meaningful customer value is essential to effective data-driven business practice” they say.
“On our new microcredential, Data Analytics for Business with Tableau, starting 13 July, you’ll develop the in-demand data analytics skills you need to progress in your field as a business or data analyst.” The course lasts twelve weeks and is certified by the University of Coventry. It is targeted at early-stage or aspiring data or business analyst, business professional and business or arts graduates looking to start their first professional role. And the cost: 584 Euro for a twelve-week online programme. The course looks very good and the model of micro credentialing could well work. But the cost is likely to be prohibitive for many people, unless, of course there is funding for individuals doing such courses.

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.

JESHOOTS-com (CC0), Pixabay

There is an interesting article by Allison Dulin Salisbury in the Forbes magazine this morning. The article says that the Covid 19 pandemic is speeding the digital transformation of business, driven by AI and automation and quotes MIT Economist David Autor calling it an “automation forcing event.”

The combined forces of automation and dramatically altered demand are giving rise to a labor market “riptide” in which some sectors of the economy are seeing mass layoffs while others, like healthcare and tech, are still desperate for talent. Against that backdrop, education and training systems are underfunded and ill equipped to meet the demands of a more complex labor market and the shifting demographics of students.

And from the evidence of the last recession, it appears likely that it will be lower paid and lower skilled workers with jobs most at risk.

However, if the analysis of the problem is correct the answers proposed leave room for doubt. The article says: “The past few years have seen a flourishing of high-quality, low-cost training and education programs, many of them online. They are laser-focused on the needs of working learners.” Maybe so in the USA, but in Europe I am yet to see the emergence of flourishing laser focused online learning programmes. And there is plenty of evidence to suggest that online programmes such as MOOcs have more often been focused on the needs of skilled and higher paid workers.

Neither is the appeal to stakeholder capitalism and for the involvement of employers in the provision of training likely to result in big change. More interesting is the call for “investment in practices that help workers identify what career they want before they start an education program,” and to “align training to the competencies required to land a good first job.” This, the article says “means a focus on both discrete skills and broader “human skills,” like communication and problem-solving, that actually become more marketable amid automation.”

Despite reservations, the argument is moving in the right direction. Put simply the Corona virus has on its own caused massive unemployment, with the effect likely to be magnified by a speed up in automation and the use of AI. This requires the development of large scale training programmes, both for unemployed young people and lower skilled workers whose jobs are threatened. Fairly obviously, the use of technology can help in providing such programmes. Nesta in the UK is already looking at developments in this direction. It will be interesting to see what national governments and the European Union will do now to boost training as a response to the crisis.

mohamed_hassan (CC0), Pixabay

As I expected there the flurry of reports on technology and learning in the lockdown is beginning to appear.

Fosway is a company operating in the corporate learning market.

In their report of a survey of HR professionals, among other things they find among other things:

• Traditional eLearning shows signs of waning both in terms of adoption but also significantly in terms of perceived success. Video content is the highest rated in supporting organisations throughout the COVID-19 crisis so far, closely followed by curated content. Bespoke eLearning, off-the-shelf courses, and blended learning are all reported to be less successful.
• Meanwhile, as people get used to working remotely and in virtual teams, collaboration is becoming a key priority. Eighty-four percent of L&D leaders think it is more important to integrate digital learning into other corporate platforms such as Microsoft Teams, Slack, and Trello.
• So-called learning experience platforms, as well as collaborative learning specialist platforms, are rated as the most successful systems after – predictably – virtual classrooms.

For what it is worth my not at all representative survey is finding that rapid (overnight) digitization has provided an immense challenge for many organisations. A particularly steep learning curve has been how to organise and manage distributed teams of employees. More on this to follow.

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.

artpolka (CC0), Pixabay 

I must be one of the few ed tech bloggers who has not published anything on the move to online during the COVID 19 lockdowns. Not that I haven’t thought about it (and I even started several posts). However it is difficult to gauge an overall impression of what has happened and what is happening (although I am sure there will be many, many research papers and reports in the future) and from talking with people in perhaps six or seven countries in the past few weeks, there seem to be contradictory messages.

So, instead of trying to write anything coherent here are a few stray and necessarily impressionistic thoughts (in no particular order) which I will update in the future.

Firstly, many teachers seem to have coped remarkably well in the great move to online. Perhaps we have over stressed the lack of training for teachers. Some I talked too were stressed but all seemed to cope in one way or another.

However digital exclusion has reared its ugly head in a big way. Lack of bandwidth and lack of computers have prevented many from participating in online learning. Surely it is time now that internet connectivity is recognized as a key public infrastructure (as the UK labour Party proposed in their 2019 manifesto). And it also needs recognising that access to a computer should be a key provision of schools and education services. Access to space in which to learn is another issue – and not so easy to solve in a lockdown. But after restrictions are lifted in needs remembering that libraries can play an important role for those whose liv9ng space is not conducive to learning.

One think that has become very clear is the economic and social role schools play in providing childcare. Hence the pressure from the UK government to open primary schools despite it being blatantly obvious that such a move was ill prepared and premature. I am not sure that the provision of childcare should not be a wider service than one of education. And maybe it has become such a big issue in the UK because children start in school at a very young age (compared to other countries in Europe) and also have a relatively long school day.

There is a big debate going on in most countries about what universities will look like in the autumn. I think this raises wider questions about the whole purpose and role of universities in society. At least in theory, it should be possible for universities to continue with online learning. But teaching and learning is just one role for universities. With the move to mass higher education in many countries going to university has become a rite of passage. Thus in the UK the weight attached to the student satisfaction survey and the emphasis placed on social activities, sports and so on. And this is a great deal of what the students are paying for. Fees in UK universities are now £9000 a year. The feeling is that many prospective students will not pay that without the full face to face student experience (although I doubt many will miss the full face to face lectures). I also wonder how many younger people will start to realise how it is possible to get an extremely good on line education for free and one thing during the lock down has been the blossoming of online seminar, symposia, conferences and to a lesser extent workshops).

Which brings me to the vexed subject of pedagogy. Of course it is easy to say that with the full affordances of Zoom (and whoever would have predicted its popularity and use as an educational technology platform) all we have seen is lectures being delivered online. Online teaching not online learning. I am not sure this is a good dichotomy to make. Of course a sudden unplanned forced rush to online provision is probably not the greatest way to do things. But there seems plenty of anecdotal evidence that ed-tech support facilitated some excellent online provision (mention also needs to be made on the many resources for teachers made available over the internet). Of course we need to stop thinking about how we can reproduce traditional face to face approaches to teaching and earning online and start designing for creative online learning. But hopefully there is enough impetus now for this to happen.

More thoughts to follow in another post and hopefully I can get some coherent ideas out of all of this

geralt (CC0), Pixabay

The news that IBM is pulling out of the facial recognition market and is calling for “a national dialogue” on the technology’s use in law enforcement has highlighted the ethical concerns around AI powered technology. But the issue is not just confined to policing: it is also a growing concern in education. This post is based on a section in a forthcoming publication on the use of Artificial Intelligence in Vocational Education and Training, produced by the Taccle AI Erasmus Plus project.

Much concern has been expressed over the dangers and ethics of Artificial Intelligence both in general and specifically in education.

The European Commission (2020) has raised the following general issues (Naughton, 2020):

• human agency and oversight
• privacy and governance,
• diversity,
• non-discrimination and fairness,
• societal wellbeing,
• accountability,
• transparency,
• trustworthiness

However, John Naughton (2020), a technology journalist from the UK Open University, says “the discourse is invariably three parts generalities, two parts virtue-signalling.” He points to the work of David Spiegelhalter, an eminent Cambridge statistician and former president of the Royal Statistical Society who in January 2020 published an article in the Harvard Data Science Review on the question “Should we trust algorithms?” saying that it is trustworthiness rather than trust we should be focusing on. He suggests a set of seven questions one should ask about any algorithm.

1. Is it any good when tried in new parts of the real world?
2. Would something simpler, and more transparent and robust, be just as good?
3. Could I explain how it works (in general) to anyone who is interested?
4. Could I explain to an individual how it reached its conclusion in their particular case?
5. Does it know when it is on shaky ground, and can it acknowledge uncertainty?
6. Do people use it appropriately, with the right level of scepticism?
7. Does it actually help in practice?

Many of the concerns around the use of AI in education have already been aired in research around Learning Analytics. These include issues of bias, transparency and data ownership. They also include problematic questions around whether or not it is ethical that students should be told whether they are falling behind or indeed ahead in their work and surveillance of students.

The EU working group on AI in Education has identified the following issues:

• AI can easily scale up and automate bad pedagogical practices
• AI may generate stereotyped models of students profiles and behaviours and automatic grading
• Need for big data on student learning (privacy, security and ownership of data are crucial)
• Skills for AI and implications of AI for systems requirements
• Need for policy makers to understand the basics of ethical AI.

Furthermore, it has been noted that AI for education is a spillover from other areas and not purpose built for education. Experts tend to be concentrated in the private sector and may not be sufficiently aware of the requirements in the education sector.

A further and even more troubling concern is the increasing influence and lobbying of large, often multinational, technology companies who are attempting to ‘disrupt’ public education systems. Audrey Waters (2019), who is publishing a book on the history of “teaching machines”, says her concern “is not that “artificial intelligence” will in fact surpass what humans can think or do; not that it will enhance what humans can know; but rather that humans — intellectually, emotionally, occupationally — will be reduced to machines.” “Perhaps nothing,” she says, “has become quite as naturalized in education technology circles as stories about the inevitability of technology, about technology as salvation. She quotes the historian Robert Gordon who asserts that new technologies are incremental changes rather than whole-scale alterations to society we saw a century ago. Many new digital technologies, Gordon argues, are consumer technologies, and these will not — despite all the stories we hear – necessarily restructure our world.

There has been considerable debate and unease around the AI based “Smart Classroom Behaviour Management System” in use in schools in China since 2017. The system uses technology to monitor students’ facial expressions, scanning learners every 30 seconds and determining if they are happy, confused, angry, surprised, fearful or disgusted. It provides real time feedback to teachers about what emotions learners are experiencing. Facial monitoring systems are also being used in the USA. Some commentators have likened these systems to digital surveillance.

A publication entitled “Systematic review of research on artificial intelligence applications in higher education- where are the educators?” (Olaf Zawacki-Richter, Victoria I. Marín, Melissa Bond & Franziska Gouverneur (2019) which reviewed 146 out of 2656 identified publications concluded that there was a lack of critical reflection on risks and challenges. Furthermore, there was a weak connection to pedagogical theories and a need for an exploration of ethical and educational approaches. Martin Weller (2020) says educational technologists are increasingly questioning the impacts of technology on learner and scholarly practice, as well as the long-term implications for education in general. Neil Selwyn (2014) says “the notion of a contemporary educational landscape infused with digital data raises the need for detailed inquiry and critique.”

Martin Weller (2020) is concerned at “the invasive uses of technologies, many of which are co-opted into education, which highlights the importance of developing an understanding of how data is used.”

Audrey Watters (2018) has compiled a list of the nefarious social and political uses or connections of educational technology, either technology designed for education specifically or co-opted into educational purposes. She draws particular attention to the use of AI to de-professionalise teachers. And Mike Caulfield (2016) in acknowledging the positive impact of the web and related technologies argues that “to do justice to the possibilities means we must take the downsides of these environments seriously and address them.”

References

Caulfield, M. (2016). Announcing the digital polarization initiative, an open pedagogy project [Blog post]. Hapgood. Retrieved from https://hapgood.us/2016/12/07/announcing-the-digital-polarization-initiative-an-open-pedagogy-joint/

European Commission (2020). White Paper on Artificial Intelligence – A European approach to excellence and trust. Luxembourg: Publications Office of the European Union.

Gordon, R. J. (2016). The Rise and Fall of American Growth – The U.S. Standard of Living Since the Civil War. Princeton University Press.

Naughton, J. (2020). The real test of an AI machine is when it can admit to not knowing something. Guardian. Retrieved from  https://www.theguardian.com/commentisfree/2020/feb/22/test-of-ai-is-when-machine-can-admit-to-not-knowing-something.

Spiegelhalter, D. (2020). Should We Trust Algorithms? Harvard Data Science Review. Retrieved from https://hdsr.mitpress.mit.edu/pub/56lnenzj, 27.02.2020.

Watters, A. (2019). Ed-Tech Agitprop. Retrieved from http://hackeducation.com/2019/11/28/ed-tech-agitprop,  27.02.2020

Weller, M (2020). 25 years of Ed Tech. Athabasca University: AU Press.

crystal710 (CC0), Pixabay

I liked Jess Cartner Morley’s article ‘The fashion show is over: what I have learned from twenty years of catwalks’ in the UK Guardian newspaper this morning.  The fashion editor says:

There are no real-life catwalks this season, with the first all-digital London fashion week kicking off on Friday, and online-only events scheduled for Paris and Milan next month. Most probably no physical shows for the rest of the year, with September’s fashion weeks looking unlikely. And after that, who knows? Will social distancing and recession kill the catwalk for ever?,…….

But I will really, really miss fashion shows. They have brought me so much joy. My entry to fashion week coincided with the moment the catwalk was evolving from its second half of the 20th-century form – a chic but rule-bound, elite, inward-focused parade that served a clique of editors and buyers – into a stadium-sized pop cultural carnival.

This seems a remarkable similarity to the academic conference. When some twenty five years ago I started going to such conferences, they were very serious. Even getting a paper accepted was a hard business. And then there were discussants also taking their role seriously. There was one Emeritus professor who used to turn up a particular conference every year and if he attended a session at which you were presenting you had to be worried. But the funding driven demand for ever more publications and the resulting plethora of new journals and conferences catering for this need has turned academic conferences if not into stadium sized cultural carnivals but certainly large arena sized. And although the social events are better than ever I am not convinced the quality of many conferences has improved. Neither does inclusion seem to have been a major consideration. Most participants in conferences at least at an international level are dependent on grant funding from their university and in many cases that has been in short supply in recent years especially for young and emerging researchers.

Will social distancing and recession kill the academic conference for ever. I don’t think so. But they are under yet more pressure in terms of the cost both in terms of money but also the environment. True: some conference organizers don’t have the knowledge and experience to run online conferences, True too that some online conferences – trying to copy the face to face event have failed perhaps to present such a compelling vision of what an online conference could be like. But others – for instance Alt-C who already have a great deal of experience of organizing online events – have nee superb (Alt-C even managed a fine Karaoke social online). As we become more experienced I am sure we can find new (and better ways) of ‘doing’ conferences. This might include looking at what period of time they take place over, it might include moving away for just paper presentations (basically lecturing) to a real discussion over the key ideas and findings being presented.

This summer I am taking part in two online conferences. For both I could not justify paying the full face to face fee plus flights and accomodation, neither would I have been enthusiastic at yet more travel. So to paraphrase Jess Cartner Morley: I’ll be binge-watching the next season of academic onferences from here, at home on my laptop. And I can’t wait.

This post by Sophia Roppertz and Ludger Deitmer is part of the TaccleAI project for “‘Improving the Skills and Competences of VET teachers and trainers in the age of Artificial Intelligence.” It describes what is clled a ‘Deep Reinforcement Learning Project” in a German Vocational Education and Training school.

The topic of the project was Deep Reinforcement Learning – preparation of the topic “artificial intelligence” and implementation of an agent in the game “Sonic the Hedgehog”. Sonic is a computer game series of the Japanese publisher Sega. The classic main parts of the series are characterized by fast 2D jump ‘n’ run passages. There you control the blue game character Sonic The Hedgehog through so-called “zones”, which are divided into individual “acts”. In all Sonic games, rings are collected, which the main character loses when touching an opponent. If he is hit without rings, you lose an extra life. In the classic main games, after using up all extra lives and continues, you have to start all over again after a game over.

The task of the student group was to implement an agent into the game and finally to give a project presentation about the project. To accomplish this overall goal, some intermediate goals had to be achieved:

1) Acquire an understanding of artificial intelligence and neural networks

2) Gain advanced knowledge of the Python programming language

3) The AI should master different levels independently

How is the project structured?

Trainees of the vocational school “information technology assistants” (German: “Informationstechnische*r Assistent*in”) took part in the AI project. The AI project took place in the second year of training within the framework of the learning field “Planning, implementing and evaluating projects” (practice). The total time required was 160 hours per school year. The project meetings usually took place on a full day of lessons. The students had the opportunity to work in the computer room or in the corresponding workshops of the school. During this time, a teacher was present to provide support but did not actively participate in the project.

As part of the KI project, the students were given a presentation on project management by the responsible teacher. With this knowledge team rules were established, field analyses were made, a target matrix was created, a schedule and work packages were created. The individual work packages were assigned performance specifications and outputs that had to be delivered. Responsibilities for the work packages were also defined. Furthermore, the students were assigned roles within the project group: e.g.

Team speaker: Moderates the group work and makes sure that everyone can get involved, that the topic is worked on consistently, and that the team rules are observed.

Timekeeper: Makes sure that the timetable is respected.

Foreign Minister: Communicates with people outside the team, maintains contact, and involves people.

What do the trainees learn in the project?

The trainees were able to acquire both technical and social skills in the course of this project. On the one hand, they learned project-oriented work in a group, they set themselves goals and divided and organised their work independently. On the other hand, they independently dealt with a programming language (Python) that was new to them and learned its basics to the extent that they were able to understand, modify, and create programs. In addition, the trainees have dealt with the basics of neural networks and the different terms of machine learning, so that they were able to present the basics to their fellow students and explain the terms. They acquired this knowledge mainly by watching videos. They used textbooks less because they mostly dealt with the AI topic in a very mathematical way and the mathematical knowledge of the students was not sufficient for this.

They have dealt with the topic “Deep Reinforcement Learning” and were able to program an agent to such an extent or to change existing programs in such a way that this “agent” learns to improve “his” game. In the end, they got so far into the programming of the “agent” that they were able to explain to their classmates which parameters they had to adjust/change so that their “agent” could improve his game.

Reflection and Recommendations for other teachers

The supervising teacher reports in the interview that basic knowledge in the field of AI is becoming increasingly important for information technology assistants since, in the context of the digitalised working world, processes are increasingly influenced by algorithms and the use of computers. In addition, many of the students attend the technical secondary school (In Germany: Fachoberschule für Technik) after their vocational schooling in order to subsequently complete a corresponding course of study. Since the students have to deal with the topic of artificial intelligence at the latest then, it makes sense to deal with it already in the vocational school. In the project documentation, the students report that it was surprisingly easy to acquire basic knowledge about AI. However, they emphasize that the deeper immersion in the subject matter was an obstacle, as more complex mathematical knowledge would have been necessary. The students report that reading about this AI content sometimes led to lower motivation and productivity. Overall, however, the students report that the choice of project was a good decision and that they have gained an advanced understanding of AI and its practical implementation.

When asked about what needs to happen on the part of the school and the teachers so that such projects can be practiced regularly, the teacher interviewed reported that, on the one hand, appropriate further training for the teachers is necessary. Besides the transfer of knowledge about AI, the joint development of teaching concepts should be more important. In addition, existing teaching materials should be jointly reviewed and classified. Useful material could then be made available to interested colleagues as Open Educational Resources. The exchange with product developers is considered desirable in the area of teacher training. In such a framework, the social, political, and sociological aspects of AI should be discussed more critically.

The teacher recommends that the students have a say in choosing the appropriate topic. Students need motivation and perseverance to work in project groups, so it is an advantage if the project tasks are linked to the students’ interests. In addition, clear evaluation criteria should be established and communicated transparently.

katielwhite91 (CC0), Pixabay

Even before the COVIP 19 crisis and the consequent looming economic recession labour market researchers and employment experts were concerned at the prospects for the future of work due to automation and Artificial Intelligence.

The jury is still out concerning the overall effect of automation and AI on employment numbers. Some commentators have warned of drastic cuts in jobs, more optimistic projections have speculated that although individual occupations may suffer, the end effect may even be an increase in employment as new occupations and tasks emerge.

There is however general agreement on two things. The first is that there will be disruption to may occupations, in some cases leasing to a drastic reduction in the numbers employed and that secondly the tasks involved in different occupations will change.

In such a situation it is necessary to provide pathways for people from jobs at risk due to automation and AI to new and hopefully secure employment. In the UK NESTA are running the CareerTech Challenge programme, aimed at using technology to support the English Government’s National Retraining Scheme. In Canada, the Brookfield Institute has produced a research report ‘Lost and Found, Pathways from Disruption to Employment‘, proposing a framework for identifying and realizing opportunities in areas of growing employment, which, they say “could help guide the design of policies and programs aimed at supporting mid-career transitions.”

The framework is based on using Labour Market Information. But, as the authors point out, “For people experiencing job loss, the exact pathways from shrinking jobs to growing opportunities are not always readily apparent, even with access to labour market information (LMI).”

The methodology is based on the identification of origin occupations and destination occupations. Origin occupations are jobs which are already showing signs of employment. Decline regardless of the source of th disruption. Destination jobs are future orientated jobs into which individuals form an origin occupation can be reasonably expected to transition. They are growing, competitive and relatively resilient to shocks.

Both origin and destination occupations are identified by an analysis of employment data.

They are matched by analysing the underlying skills, abilities, knowledge, and work activities they require. This is based on data from the O*Net program. Basically, the researchers were looking for a high 80 or 90 per cent match. They also were looking for destination occupations which would include an increase in pay – or at least no decrease.

But even then, some qualitative analysis is needed. For instance, even with a strong skills match, a destination occupation might require certification which would require a lengthy or expensive training programme. Thus, it is not enough to rely on the numbers alone. Yet od such pathways can be identified then it could be possible to provide bespoke training programmes to support people in moving between occupations.

The report emphasises that skills are not the only issue and discusses other factors that affect a worker’s journey, thereby, they say “grounding the model in practical realities. We demonstrate that exploring job pathways must go beyond skills requirements to reflect the realities of how people make career transitions.”

These could include personal confidence or willingness or ability to move for a new job. They also include the willingness of employers to look beyond formal certificates as the basis for taking on new staff.

The report emphasises the importance of local labour market information. That automation and AI are impacting very differently in different cities and regions is also shown in research from both Nesta and the Centre for Cities in the UK. Put quite simply in some cities there are many jobs likely to be hard hit by automation and AI, in other cities far less. Of course, such analysis is going to be complicated by COVID 19. Cities, such as Derby in the UK, have a high percentage of jobs in the aerospace industry and these previously seemed relatively secure: this is now not so.

In this respect there is a problem with freely available Labour Market Information. The Brookfield Institute researchers were forced to base their work on the Canadian 2006 and 2016 censuses which as they admit was not ideal. Tn the UK data on occupations and employment from the Office of National Statistics is not available at a city level and it is very difficult to match up qualifications to employment. If similar work is to be undertaken in the UK, there will be a need for more disaggregated local Labour Market Information, some of it which may already be being collected through city governments and Local Economic Partnerships.