LinkedIn is the most boring but probably most useful social network I belong to. I can’ say though I am very interested in spending a lot of time embellishing my professional profile. And I guess its the same for a lot of other people. I guess thats why LinkedIn has developed an algorithm which they offer to write a summary of your profile for you, based they say on “your accomplishments.”

And although a bit gushing, I decided that the AI version of me was not too embarrassing to add to my profile. Here you go:

I’m passionate about providing a quality education, to improve learners learning and to empower teachers. As an experienced L&D professional I have a wide range of skills which can be utilised in all areas of education but particular skills in: Learning Technology; Education; Assessment Systems development for educational providers; Educational Policies & Procedure writing and review. My experience in both the public and private sectors as well as my background in Further Education has provided me with a vast knowledge base to support staff and students on the whole. The combination of these experiences would be invaluable and useful within any educational institution or company.

One of the results of the rapid deployment of Artificial Intelligence is an increased focus on the relation between humans and machines.

The Economist has published a podcast of an interview with Nobel prize-winning author asking about what his new book “Klara and the Sun” reveals about people’s relationship with machines. They say “he argues that people’s relationship to machines will eventually change the way they think of themselves as individuals.”

And the University of Westminster Press have published a new book, Marx and Digital Machines: Alienation, Technology, Capitalism, by Mike Healy. This book explores the fundamental contradiction at the heart of the digital environment, they say, “technology offers all manner of promises, yet habitually fails to deliver. This failure often arises from numerous problems: the proficiency of the technology or end-user, policy failure at various levels, or a combination of these. Solutions such as better technology and more effective end-user education are often put into place to solve these failures.”

Mike Healy argues that such approaches are inherently faulty drawing upon qualitative research informed by Marx’s theory of alienation.

The book which is distributed under the terms of the Creative Commons Attribution + Noncommercial + NoDerivatives 4.0 license with copyright retained by the author(s) is available for sale in paperback format or for free download in a variety of digital formats.

Tony Bates has released a series of five 40-50 minute keynotes which an be downloaded without cost from the Commonwealth of Learning’s online institutional repository for learning resources and publications, OAsis, under a Creative Commons license. The subjects of the keynotes are:

1. Developing quality blended learning courses
2. Digital learning and the new economy
3. New technologies and their potential and limitations for teaching and learning
4. Ten lessons for online learning from the Covid-19 experience (based on research findings)
5. Online learning in the (k-12) school sector

The intention is that these can be streamed during virtual conferences, included in education and training programs, or watched individually. As James Clay says on Twitter: “I think this is an interesting concept for future online events. However there is a difference between YouTube or Netflix and an online conference. How do you add value to an event so that it is more than just streamed video?”

I went to a couple of events last week that were trying different formats. One was a professorial inaugural lecture by Bob Harrison who, it seems insisted on prerecording his presentation so he could actively participate in the accompanying chat. The other was the OECD conference on AI and the Future of Work, where the real value was not presentations as such but great (and well prepared moderation of panels of speakers, with limited opportunities for particpant questioning.

However, coming back to Tony Bates’s video keynotes, the real value I see with these is with remixing. They are released under a Creative Commons attribution, share alike license which means they are free to remix. This allows using (in my case short) clips from the video in Open Educational Resources for a MOOC we are developing on AI for vocational teachers and trainers and part of the taccle AI project. I’m going to have a go this afternoon.

mamir_k94 (CC0), Pixabay

The UK operates a central university admissions service, called UCAS. Today they have released their analysis of institutional and subject admissions for 2020. In an article in the online Higher Education newspaper, WONKHE, Sander Kristel, Chief Operations Officer at UCAS, points out some of  the more striking features of the data.

He reports that Artificial Intelligence degrees have grown by more than 400 per cent in the past decade – from just 65 acceptances in 2011 to 355 acceptances in 2020.

As he says:

This growth will be music to the ears of employers according to research from the Industrial Strategy Council, which highlighted the adoption of automation as the biggest driver of a shift in skills and estimated that 39 per cent of the activities that people are paid to do in the UK today could be automated by 2030, with current technology creating demand in technology-related occupations such as software development.

Less welcome news, however, is that although the ratio of UK male acceptances to UK female acceptances across all Science, Technology, Engineering and Maths subjects has shrunk from 1.34 in to 1.06 over the last decade, there has been little progress made in closing the gap for computer science (6.2 in 2011, relative to 5.7 in 2020), perhaps related to the significant amount of growth in this subject overall.

Pavlofox (CC0), Pixabay

There is growing research and debate over how technology – particularly AI and automation – will result in changes to the world of work. LMIC  (I think it stands for Labor Market Information Centre – but I couldn’t find anything about the name of their website)  in Canada has a project to set up an ongoing annotated bibliography. And, although there is a focus on north American literature and reports, the site is useful for anyone interested in this topic.

“The future of work is a hot topic and the focus of many initiatives in recent years. Addressing gaps in labour market information (LMI) ensures that policy makers and stakeholders can help shape the future of work. For Canadians, information to help them adapt to this fourth industrial revolution is essential.

geralt (CC0), Pixabay

The debate goes on. Here is the latest discussion organised by the OECD. On February 1 from 1600 to 1700 CET. Go here to register.

“What do we know about the impact of AI on the labour market? Will it further automate jobs and, if so, which ones? Will it improve job quality, or worsen it? And what will AI mean for disparities in the labour market? Will we be able to harness the opportunities that it offers to reduce inequalities or will we instead see inequality rise even further? This session will take stock of what we know about the impact of AI on the labour market and what we might expect to see in the future, including as a result of the Covid-19 crisis.”

I am copying this from Stephen Downes’ ever informative OLDaily newsletter digest. It features an article entitled What is machine learning? – A beginner’s guide posted on the FutureLearn website.

This is quite a good introduction to machine learning. If you don’t know what it is and would like a quick no-nonsense introduction, this is it. Machine learning is depicted “as the science of getting computers to learn automatically.” It’s a type of artificial intelligence, which means essentially that they are software systems that “operate in an intentional, intelligent, and adaptive manner.” The third point is the most important, because it means they can change their programming based on experience and changing circumstances. The article talks about some types of machine learning systems and outlines some application in the field. It’s FutureLearn, so at the end it recommends some course tracks for people interested in making this a career, and just to dangle a carrot, the web page lets you know the median base salary and number of job opening for the program in question.

geralt (CC0), Pixabay

A recent MIT Technology Review Insights reports on a survey of 301 business and technology leaders around their use and future planned us of Artificial Intelligence. The survey confirms that the deployment of AI is increasing, not only in large companies but also in SMEs. It also points to the emergence of what is known as edge  comput9ing, using a variety of devices closer to the applied use than cloud computing allows and capable of near real time processing.

38% report of those surveyed report their AI investment plans are unchanged as a result of the pandemic, and 32% indicate the crisis has accelerated their plans. The percentages of unchanged and revved-up AI plans are greater at organizations that had an AI strategy already in place.

AI is not a new addition to the corporate technology arsenal: 62% of survey respondents are using AI technologies. Respondents from larger organizations (those with more than $500 million in annual revenue) have, at nearly 80%, higher deployment rates. Small organizations (with less than $5 million in revenue) are at 58%, slightly below the average.

Cloud-based AI also allows organizations to operate in an ecosystem of collaborators that includes application developers, analytics companies, and customers themselves.

But while the cloud provides significant AI-fueled advantages for organizations, an increasing number of applications have to make use of the infrastructural capabilities of the “edge,” the intermediary computing layer between the cloud and the devices that need computational power.

Asked to rank the opportunities that AI provides them, respondents identify AI-enabled insight as the most important (see Figure 2). Real-time decision-making is the biggest opportunity, regardless of an organization’s size: AI’s use in fast, effective decision-making is the top-ranked priority for large and small organizations.

For small ones, though, it is tied to the need to use AI as a competitive differentiator.

Again, the need for real-time data or predictive tools is a requirement that could drive demand for edge-based AI resources.

Survey respondents indicate that AI is being used to enhance current and future performance and operational efficiencies: research and development is, by a large margin, the most common current use for AI, used by 53% of respondents, integrating AI-based analytics into their product and service development processes. Anomaly detection and cybersecurity are the next-most-deployed AI applications.

Large organizations have additional priorities: 54% report heavy use of robotic process automation to streamline business processes traditionally done by humans, and 41% use AI in sales and business forecasting. For organizations with AI strategies, 40% rely on robotic process automation, and 42% use AI to estimate future sales.

ColiN00B (CC0), Pixabay

It does not seem likely that we are going to participate in any face to face conferences in the near future. But conferences are continuing online and in some ways there are increased opportunities for sharing ideas and knowledge. Anyway that was a preamble for the latest abstract that I, together with Sohia Roppertz and Ludger Dietmer have submitted for the 4^th Crossing Boundaries on Vocational Education and Training in 2021.

1        Introduction

The growing use of Artificial intelligence (AI) and other technological innovations are leading to a fundamental change in the world of work, as tasks previously performed by humans can now potentially be performed/assisted by computers and computer-controlled machines (Brynjolfsson & McAffee, 2014; Dengler & Matthes ,2018).

This digital transformation places VET under high pressure to adapt (Seufert, 2018), to provide professional action competence within non academic technical, social, commercial and other occupations. VET schools and their teachers and trainers have the central task of preparing learners for the changing world of work.  Technological change also is impacting the organisation of  VET schools through the introduction of big data and e-government and at the implementation level in connection with e.g. adaptive learning systems and learning analytics (Seufert 2018).

Against this background, the question arises how vocational school teachers and trainers can be prepared for these tasks. While a survey undertaken through the Taccle AI project found most vocational teachers and trainers recognised the importance of AI, there are presently few opportunities for professional development (Author, forthcoming).

This paper reports on work in progress through the EU Erasmus Plus funded Taccle AI project examining the impact of AI on Vocational Education and Training, led by the University of Bremen Following initial research and the development of a Resource Toolkit, the project is developing a Massive Open Online Course (MOOC), to be offered in English and  Germany and expected to be launched May 2021.

In section two of the paper we will examine the vision behind MOOCs and in section three will look at the different dimensions of a MOOC for professional development for teachers and trainers around AI. This will be followed by a discussion of how cooperative and project related MOOC design can support teachers and trainers in developing their professional practice. Finally we will draw some initial conclusions based on our work.

2.       Theoretical background

The first MOOC, led by George Siemens and Stephen Downes was in 2008 around the topic of Connectivism. According to Downes (2012) it was based on the realization that the use of distributed open resources would support – with ease – an attendance in the thousands. The vision grew out of the idea of Open Education, where everybody could access free online courses. The idea quickly took off, especially with the launch of Coursera and Udacity. Although the founders of these companies saw their innovation as disruptive to traditional education institutions, universities have been quick to pick up on the potential of MOOCs. In Europe one of the biggest MOOC providers is OpenLearn, through the UK Open University leading a consortium of educational providers.

2.1       Vision behind MOOCs

There has been and continues to be discussion over pedagogic approach to MOOC design, with advocates of so called cMoocs emphasising the active contribution of participants, using digital platforms and technologies while so called xMOOCs, for example from Stanford University, are more focused on the transmission of knowledge.

MOOCs are increasingly being used for professional development, for instance by companies like Siemens, and for teachers and trainers.

3. MOOCs and AI – two dimensions

There are two key dimensions to the AI MOOC.

3.1       MOOCs as a Way to Learn about AI

The first is MOOCs as a way to learn about AI. This in turn has three key foci. After an initial introduction the course will examine both the impact of AI on the Changing world of Work and its implications in terms of skills, tasks and consequently curriculum. The second focus will be on the use of AI for teaching and learning in VET. The final section will examine the ethical implications of AI for VET.

3.2       Artificial Intelligence powered MOOCs

The second key dimension will be the integration of AI into the MOOC platform. While this work is still under development it is intended to incorporate Natural Language processing for the production of materials and Learning Analytics within the MOOC Platform.

4.             Implementation of cooperative and project related (more interactive) MOOCs design in professional development of VET teachers and trainers

New forms of learning are needed for AI in VET. MOOCs including practice and project-based learning can be used both in VET courses and for training teachers and trainers. The paper will discuss how MOOCs can be designed through a new didactical approach to teaching and learning.

The article will explore the concept of additional qualifications within apprenticeship training and how such concepts can be adapted to different European vocational settings. It will show how the new arrangements affect the teaching and learning of  VET students (e.g. mechatronic apprentices), and new roles for VET teachers and trainers. Discussion will be based around examples, for instance the mechatronic students are working and learning in school based and training factory labs themselves developing AI projects (Author et Al, 2020a). This functional learning material allows student teams to plan, prepare, realize and demonstrate projects in which for example autonomous driving or robot functions are programmed, tested and presented to bigger audiences. These practice based developments will be incorporated in the MOOC.

5. Conclusions

This paper will examine the question of whether MOOCs are suitable for the continuing education of VET teachers and trainers in the context of Artificial Intelligence. It will also clarify what kind of MOOCs types and settings can be connected to projects, how MOOCs can be implemented by VET teachers and trainers and how they have to be structurally designed in didactical terms. This includes the question how teachers and trainers have to be prepared for such new learning arrangements in order to develop vocationally oriented MOOCss (Author at Al, 2020b).

References

Author, Bekiaridis, G., Author., Tutlys, T., Perini, M., Roppertz, S., & Tutlys, V. (2020a). Artificial Intelligence in Policies, Processes and Practices of Vocational Education and Training. Institut Technik und Bildung. https://doi.org/10.26092/elib/307

Author, Author., Tutlys, T., Author, & Perini, Marco. (2020b). Digitalisation, artificial intelligence and vocational occupations and skills: What are the needs for training teachers and trainers? In C. Nägele, B. E. Stalder, & N. Kersh (Eds.), Trends in vocational education and training research, Vol. III. Proceedings of the European Conference on Educational Research (ECER), Vocational Education and Training Network (VETNET) (pp. 30–42). https://doi.org/10.5281/zenodo.4005713

Downes, S. 2012, The Rise of MOOCs, https://www.downes.ca/cgi-bin/page.cgi?post=57911, accessed 15 December, 2020

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company.

Dengler, K. & Matthes, B. (2018). Substituierbarkeitspotenzial von Berufen. Wenige Berufsbilder halten mit der Digitalisierung Schritt. IAB-Kurzbericht.

Seufert, S. (2018). Flexibilisierung der Berufsbildung im Kontext fortschreitender Digitalisierung. Bericht im Auftrag des Staatssekretariats für Bildung, Forschung und Innovation SBFI im Rahmen des Projekts «Berufsbildung 2030 – Vision und Strategische Leitlinien» Zugriff unter: https://edudoc.ch/record/132323 (1.12.2020)

Author, (forthcoming). Artificial Intelligence and Vocational Education and Training – Perspective of German VET teachers. Proceedings of the European Distance and E-Learning Network Research Workshop, 2020 Lisboa, 21 – 23 October 2020.)

AI as I am sure you all know by now, is largely reliant on the black gold, data, and preferably lots of it. With the speed that things are developing at, its pretty hard to keep up with the world of AI and data. In the past I subscribed to the excellent free weekly MIT technology Review, but sadly that went the way of paid for subscription services.

But the London and Leeds based Open Data Institute continues to publish a free weekly newsletter, The Week in Data. And it tends to favour more a social approach than some other more technology heavy news services. Here is an excerpt from last Friday’s issue’

If you’re looking to stream an anxiety-inducing film about the rise of robots over your Christmas break, you may not think to look in the documentary category. But iHuman, a gloomy (and seemingly slightly dramatised) take on the world of AI, is released this week in cinemas and (and online), and sits firmly in the ‘documentary’ genre. Film-maker Tonje Hessen Schei speaks to a range of interviewees, including Elon Musk’s computer scientist, to explore what will happen ‘when robots become smarter than humans’. It has been described by The Guardian as ‘an eye-opening film if your anxiety levels are up to it’. We’d love to hear – once you’ve had a look – whether it filled you with joy, dread or a painful amount of eye-rolling.

You can subscribe to The Week in Data here.