Starlink changes everything. It may be the most important form of learning technology of the century

I was out in my garden in May last year, watching a stream of satellites pass in a line overhead. It was beautiful. Starlink changes everything. In online learning it absolutely changes everything. A global network of satellites delivering high speed broadband means that anyone, anywhere in the world can get high-speed broadband.

How does it work?

There are over 1000 satellites up already. Target is 2027 for thousands more satellites. Why so many? Well, each has a small cone of coverage but it cuts latency. Lasers between satellites travel at the speed of light. This is much faster than optical delivery through cable and allows global distribution with very low latency. Note that this will not wipe out urban networks but is great for rural and low density markets. If you are worried about space debris, their satellites have propulsion, collision software and can be dropped to disintegrate when they come to the end of their life.

What does it cost?

Prices at the moment are £89 plus £439 for the dish and speeds at 50-150mbs. However, speeds will soon double and prices will fall. It has over 10,000 users in its US beta program and is also delivering services to users in the UK. You can sign up right now.

How did we get here?

It’s less than 30 years since Tim Berners-Lee invented the world-wide web in 1991. There was no broadband 20 years ago from today. It started in the UK on 31 March 2000 and for years it was kilobits then just 2megabits by 2005. 50 megabits was introduced in 2008, 100 by 2010. This was an amazing achievement and has revolutionised play, work and learning.

1G networks were the first, 2G networks added data for things like SMS messages, 3G internet added even more and 4G, what we currently use, much faster internet access that has enabled social media and streaming. With every gear change comes faster and more efficient delivery. 5G delivers much, much higher speed and bandwidth. 4G caps out at 100 megabits per second (Mbps), 5G caps out at 10 gigabits per second (Gbps). That means 5G is x100 faster than 4G technology, theoretically at least. 

But what does this Starlink move mean? 

To be honest, this is not really about 5G. Starlink is more important than 5G. It allows us to work and learn anywhere. It will allow people to move out of cities. High bandwidth, low latency, reliable internet will change how we work and learn. Its timing is perfect with respect to Covid. Now that we've been through the Great Pause and learnt to work and learn more at home, Starlink accelerates this process.

Rural business

First, It’s a great leveller. It delivers high-speed broadband to all rural areas, allowing work to migrate out of the cities, also boosting local businesses. Broadband will. No longer be an urban thing. This is in line with the political demands in countries where populations have voted for less globalisations and urbanisation, in favour for a more geographically, equal distribution of wealth. SpaceX had to reach certain delivery speeds in order to participate in the Federal Communication Commission's up to $16bn Rural Digital Opportunity Fund. 

Developing world benefits

More than this, it allows broadband to be delivered to anywhere on the planet. This include the whole of the developing world. This is mind-boggling and may free up the talent in those economies, bringing them into the fold. Anyone can produce anything and sell their talents online. The local becomes global.

Global online learning

Post-Covid, the world will undoubtedly have taken a shift towards online learning in schools, colleges, Universities and the workplace. Forget the conspiracy theories, 5G wireless technology stands for ‘fifth generation’ cellular technology. Tie this up with Starlink, a low earth orbit network of satellites delivering blistering speeds to everywhere in the world and the engine that is AI, and we have a perfect storm that will transform global, online learning.

SpaceX's satellite internet system will offer still blazingly fast speeds of up to 1 gigabit per second. It will offer satellite internet to the entire planet, including remote locations where internet isn't currently available. Its satellites are low enough, and move (not geostationary), to deliver this with no blindspots. That’s an astounding leap. A couple of orders of magnitude better and global coverage. In terms of delivery and the user experience in online learning, this means a lot. In short, we can get online. learning anywhere.

Ultra low latency

We spend a lot of time watching that little circle spinning on our screens. Technically it’s called latency, the time taken to find, identify and transfer data. 5G will make this all but disappear. This matters when you’re delivering complex online learning, whether it’s video, simulations, AI, VR or AR.

The Media Equation: How People Treat Computers, Television and New Media Like Real People and Places by Byron Reeves and Clifford Nass, two Stanford academics, is full of juicy research on media in learning. It provides a compelling case, backed up with empirical studies, to show that that people confuse media with real life. This is actually a highly useful confusion: it is what makes movies, television, radio, the web and e-learning work. But their research also supports the case for 5G. 35 psychological studies into the human reaction to media all point towards the simple proposition that people react towards media socially even though, at a conscious level, they believe it is not reasonable to do so. They can't help it. In short, people think that computers are people, which makes online learning work.

Why is this relevant to 5G? Well in real life we live in real time. We don’t encounter little spinning circles, except when waiting on a late train or in a queue, and who wants that? Hearteningly, it means that there is no reason why online learning experiences should be any less compelling - any less 'human' in feel - than what we experience in the real world and the classroom. As long as a media technology is consistent with social and physical rules, we will accept it. Read that last part again, 'as long as a media technology is consistent with social and physical rules'. If the media technology fails to conform to these human expectations - we will very much not accept it.

The spell is easily broken. Nass & Reeves showed that unnatural ‘pauses’ inhibit learning. If the media technology fails to conform to our human expectations - we will NOT accept it. This is a fascinating lesson for online learning. We must learn to design our courseware as if it were being delivered in real-time by real people in a realistic fashion. The effectiveness of the user experience on an emotional level will depend as much on these considerations as on the scriptwriting and graphic design. It all has to work seamlessly, or the illusion of humanity fails. This has huge implications in terms of the use of media and media mix.

A simple finding, that shows we have real life expectations for media, is our dislike of unnatural timing. Slight pauses, waits and unexpected events cause disturbance. Audio-video asynchrony, such as poor lip-synch or jerky low frame-rate video, will result in negative evaluations of the speaker. These problems are cognitively disturbing. They lower learning. All that disappears with 5G.

Flawless streaming

Streaming will become much easier and almost flawless, allowing online learning to deliver whatever media is necessary at whatever time is optimal for learning. Note that this does not open the floodgates for over-engineered multimedia in learning, Media rich is not necessarily mind-rich. Many see video as the killer app for 5G. It is one but video is rarely enough on its own in learning. It will certainly boost LXP, personalised delivery of any media type.

AI mediated learning

AI delivered learning will also be easier as realtime calls to cloud-based AI services opens up smart solutions in learning. This opens up a new world for adaptive learning, feedback, chatbots, automated notifications based on xAPI, learning in the workflow. Specifically, it allows access to services, such as OpenAI API to tap into AI on demand. This means smarter, faster and better online learning. We free ourselves from the current presentation of flat, linear experiences. The process, and learning is not an event but a process, will be sensitive to each individual learner. Personalised learning becomes a reality. I mention Starlink in my book AI for Learning.

New user experiences

New user experiences and processes will be possible when we free ourselves from the tyranny of latency and slow speed internet. The promise of blended learning that can deliver great simulations, immersion and whatever one has delivered in the real world or classroom is now possible. New business models will emerge. New forms of learning with full immersion, AI, personalisation will emerge.

New devices

Rumours have it that Apple will be offering a ‘glasses’ or AR device. In any case, wearables, watches and small devices are now everywhere. 5G allows high speed access to and from these devices. This is not just about smartphones, it frees up fast internet speeds to all devices. We can link learning to devices that provide the context for learning. Where are you, what are you doing, then this is what we can do to help. This all becomes possible wherever you are indoors or outdoors, anywhere on the planet. 

Conclusion

The great leaps in learning technologies were writing, the alphabet, printing, broadcast media, computers, the internet and now AI and data. But this is the Internet with a difference. It's universal and global. Higher performance and improved efficiency empower new user experiences and connects new industries. This is not about boosting learning. It is about changing the very nature of education and learning. The implications for the poorer regions of the world are obvious, as it could be a great leveller. The tides rise with the gravitational pull of the moon, this is a rising tide that also comes from space, for everyone, one that doesn’t ebb.

Head, Hand and Heart by David Goodhart

My favourite Tweet of this plague year?

“There was never any lockdown. There was just middle-class people hiding, while working-class people brought them things.” 

It hit a Covid nerve because the people doing all the heavy lifting were the low-paid carers, nurses, supermarket staff, cooks, bin-collectors, bus and delivery drivers. Goodhart has written an unusual book, that should be read by all educators, at all levels – schools, colleges, Universities and workplaces - that exposes the straight-up hypocrisy behind an economic system that rewards knowledge workers at the expense of all others. Educational stratification has not created a better world, it has divided us and rewarded people unfairly. Inequalities have stretched societies to breaking point.

His is a plea for something I’ve fought for all my life, the rebalancing of society, economics and rewards away from the Head (cognitive work) towards the Hand (making and manual work) and Heart (health and care work). We have reached what he calls 'Peak Head' (which shouts out for metaphorical use!), the focus on funnelling everyone towards University degrees on a single route towards a single, cognitive elite. Many of the innovations in our past, such as the spinning jenny and steam engine were not driven by the University system. Entire economies in the east, China, South Korea and Taiwan, were built, not on a University system (they came later) but by a more rounded approach to development. 

It is not as if this elite has served us well. We saw their disastrous foray into Iraq, the financial crisis that nearly ruined us all, Brexit, Trump – we’re witnessing the fall-out. The danger he sees, is that this elite will suffer badly when technology replaces their work, quicker than it may replace the refuse collector or child-carer. What he recommends is policy built around the Heart, Hand and Head triumvirate.

Our educational system is hopelessly lop-sided towards the University sector. I spent years as an unpaid Director in The University for Industry trying to deliver basic skills, set up a £55 million charity for vocational learning, was a Trustee of City & Guilds, sponsored a youth football team and have always felt an affinity towards the talent that is squandered through straight snobbery and self-interest. It’s one of the reasons I voted for Brexit.

Goodhart explains how this hideous hostage taking of society, property and money has evolved and backs up arguments by Caplan in education, that too much money is completely wasted on signalling in Universities and that alternatives have to be found, even just on the basis of avoiding social unrest. Trump, Brexit, the gilets jaunes; all show that there is deep dissatisfaction among people who did not go to ‘Uni’. This deification of HE has been at the expense of the majority who do not go there. In my travels around campuses, here and abroad, you don’t have to walk far to find homeless people sleeping in the doorways of student accommodation. 

As we emerge from Covid, at last we have a book that has some ideas about the future. I don’t agree with everything he says, and would be much more radical, demanding blended learning and blended working as the default. But he’s pretty much on message for me. Note that this is not a page turner. It’s well written but analytic.

His The Road to Somewhere was a precursor to this book and one of the few books that actually explained why Brexit happened, naming the University system as one of the problems. This second book asks us a much more serious question. What are we going to do when Covid is over? Back to school with the same old satchels? Back to slabbing out lectures in exchange for crippling debt? Back to inhuman commutes and boxy offices? Back to flying here there and everywhere? Or a better sense of the common good?

He contrasts the centrifugal forces of hyper-globalisation stretched supply chains and the free movement of goods and capital, with a more centripedal set of ideas around the local, social stability and solidarity.

We seem to have lost the ability to create our future differently and fairly. It’s all groundhog day nostalgia for a past that was now clearly dysfunctional. Head, Heart and Hand – remember those three words when you put your bins out, buy something in a shop, order a takeaway and go out into the world, especially when you vote. I know, it's all a bit polemical but in serious times, you need to do some serious reading. 

From Nazi Punchcards to the Cambrian Explosion of LMSs and now LXPs - a short history of enterprise learning software

 

Introduction

The LMS (Learning Management System) and now LXP (Learning Experience Platform) have lots of roots, best seen historically as growing from several roots; hardware, software, business software, connectivity and pedagogy.

Hardware

Early hardware developments ranged from punch-card systems to mechanical devices There had been a series of experimental attempts at what was called CAI (Computer Assisted Instruction). IBM had a prototype LMS, the Hollerith System. Tom Watson, CEO of IBM flew to meet Hitler in 1939 and sold him a primitive, punch-card, Learning Management System, called the Hollerith system. As told in in the excellent book ‘IBM and the Holocaust’ by Edwin Black, it stored data on skills, race and sexual orientation. Jews, Gypsies, the disabled and homosexuals, were identified and selected for slave labour and death trains to the concentration camps. The LMS did not start well. Skinner in 1954, came up with something called a teaching machine. The whole idea behind which was to teach classroom subject such as maths, spelling etc. using a mechanical device that would also surpass the usual classroom experience. 

Software

There were other notable events around software such as the famous AI conference in 1956 at Dartmouth, where several projects emerged, even the first chatbot. There was a long period of experimentation before usable computers came along. This experimentation is summarised by Atkinson & Wilson (1969) with 21 papers looking at the then trends in CAI. The experimentation was especially strong in the military, as explained by Fletcher and Rockway (1986). PLATO and its rival TICCIT, were largely confined to academic experimentation although there were some corporate examples. All of this played a role, albeit it slow and relatively minor, as part of this period of experimentation. 

Down to business

Then home computers, made possible by the mass production of the microprocessor in 1971, led to an explosion of activity in the 1980s. But it was the IBM PC that game real impetus to CBT (Computer Based Training), when released in 1981, along with a rack of consumer computers such as the Commodore 64. This gave rise to an embryonic computer based training industry. My first learning programme, to teach Russian, was in the early 1980s on a Commodore 64. Other machines such as the BBC Micro in the early 80, in the UK, were seen immediately as having educational uses.

There were many programmes produced and distributed on floppy discs of various sizes. Other storage devices such as interactive videotapes, Videodiscs, laserdiscs, CDi and CD-ROM were used to store very larger amounts of data and media. There was a burst of creative activity, as video, audio and images could be used with the overlay of text from computers.

Then came networked enterprise systems, with client-server structures. IBM was a hardware then a software company but competed directly with Microsoft on software with their Lotus Smart Suite, Lotus 1-2-3, Lotus Notes and so on. This was a rival to Office, the last release being 2014! SAP was an early 1975 a spin off from IBM that stuck to ERM software. Microsoft was a software company built on their operating system then Office software that came along in 1988. Cisco 1984 out of Stanford, a networking company. Enterprise software became the norm, as it did for learning. All of these set the scene for learning systems that operated at the enterprise level.

LMS Cambrian Explosion

This all led to the Cambrian explosion of LMS, in 1999-2001, tracked in detail by Brandon Hall. Between 1999 and 2001 the sales of LMSs took off. Brandon Hall published a specification list and before long there were around 250 systems. On top of this HR companies like SAP, Peoplesoft and Oracle entered the LMS market. Then a split emerged between the LMS (corporate) and VLE (education market) with e-college, Blackboard and WebCT.

There were eventually two main groups. Those that developed out of client-server, training systems and those that were born on the web. Saba, Click2Learn, Pathlore, Learnframe and Thinq were originally client server and had to be rewritten for the web. They often used Java applets, client-end software and plug-ins, with a client-server back-end for administration. The born on the web group included Docent, KnowledgePlanet and Teamscape, which had web browser interfaces. They had the advantage of being more scalable, easier to roll-out and maintain, with fewer technical changes. Later open source LMSs emerged, the most successful being Moodle. This in turn was forked and corporate versions created. In late 2001 the market was made more complicated by the introduction of the LCMS (Learning Content Management System). These vendors claimed to have additional functionality around authoring, learning object repositories and dynamic delivery. The distinction was soon blurred as the LMS vendors adopted these features. Interestingly, the learning object approach has returned with micro-learning, 20 years later.

At the same time ADL and others came up with de facto standards. It is important to note that there are few real standards in e-learning: what we have instead is a collection of specifications, guidelines and reference models, a set of de facto (not de jure) standards. Across the range of LMSs on offer there were varying degrees of adoption of AICC, IMS and SCORM. Then there were accessibility standards, an increasing demand, especially in the public sector.

Dominant model

At the start, Brandon Hall issued a specification list that led to procurement against the list and so their complexity grew. Brandon Hall reported 27 LMSs in 1998, 50 in 2000 and by 2003 they had selected 70 LMSs. There were many more and the market continued to grow. Since then there have been lots of failures, mergers and acquisitions but it remains a large $7 billion market, having shifted to a SaaS model. For the last 20 years this has been the dominant model but there has always been dissatisfaction on integration, lack of data and shortfalls on functionality and delivery. 

As repositories for content, they were more about management than learning. There had always been dissatisfaction with the model, based on its poor interface, sign-ons, clumsy menu systems and delivery of ‘courses’. In a sense, they still mimic classroom courses, managing them after they had been converted to online. They fail to provide the flexibility needed in the workplace on both push and pull, moments of need and more sophisticated pedagogy, especially around motivation.

Learning Experience Design

Learning Experiences came from a different root. An early mention of Learning Experience Design is by McLellan (2002) who, prophetically, mentions Harvard Case Studies, simulations, virtual reality, artificial intelligence and recommends the rehabilitation of the emotional side of learning. She mentions Pine and Gilmore (1999), who talk of the ‘Experience Economy’, transformative experiences, that change us in some way. This line of thought was heavily influenced by the idea of attention and experiences that people were getting in games, imagery, TV, film on the web.

There was also a growing interest in UI and UX. The web was delivering a UI experience that was personalised, used recommendation engines and looks slick. The LXP world was similarly data-driven and started to sue recommendation engines, AI, sentiment analysis.

We need also remember the deep roots of media design from Radio, TV and Computer Games. The web delivered media and multimedia experiences that the learning community wanted to mimic. Hence the rise of video with Netflix /YouTube interfaces, audio had its roots in distance learning with the School of the Air in Australia, now as podcasts.

Another development was the rise of corporate social platforms, such as Yammer and Slack. These were eventually folded into the likes of Teams. There was also a move by Microsoft, SAP and others to focus more on workflow products.

Shift to LXP

The move from LMS to LXP came from a specific line of thought that had been around for 30 years - namely performance support. Gloria Gery (1991) defined this 30 years ago, in 1991, as EPSS – Electronic Performance Support Systems. Jay Cross (2011) worked tirelessly on this concept and more recent practitioners such as Bob Mosher (2011) have focused on moments of need and innovative forms of curation and performance support. The 70:20:10 movement spearheaded by Charles Jennings and Jos Arets have also helped highlight the need for real traction in the workplace with more of a mixture of formal content and informal techniques.

In addition Degreed and some other companies entered the corporate market. The LMS vendors are now busily transforming their LMS into an LXP or building an LXP from scratch. The LMS vendors are moving towards being LXPs and the LXO+P vendors are having to become LMSs. They will, in the end be single platforms and tools.

These new platforms use the technology of the day, AI and data, to signpost, recommend and automate workflow processes. xAPI will replace SCORM and data-driven approaches will push the old static forms of delivery aside. We live in the age of algorithms, and just as everything we do online is mediated by AI and personalised by using personal and aggregated data, so it will be with learning. This is outlined in my book AI for Learning.

Learning Technology - attempt at Tech-OLOGY and History

What distinguishes us as a species is tools and technology. More accurately, what distinguished the many species that we evolved from and co-evolved alongside us is technology. It is not that other species such as birds and primates, do not use tools, but the first of our genus Homo habilis (handy man) through to Homo sapiens (knowing man) are simply the most successful of these competing species. We had better tools and technology.

We see technology as a noun, not a discipline or subject. There is no -ology for techn-ology, stuck as it is somewhere between science and engineering. Yet this is an area of human endeavour that has shaped history, economics, sociology, psychology and philosophy. What we need is a focus on Techn-ology, like Archaeology, Geology, Biology or Sociology. We need a deeper understanding of techn-ology in terms of its history and role in history.

To this end we can look towards the science of techn-ology as uncovering certain laws of technology, not laws as in physics, chemistry or biology, but rules that emerge from the way we invent, develop, deliver and use learning technology.

Learning technology

But there is one type of technology that differs from the rest – learning technology. At key moments in our history, fundamental technologies were invented that unlocked massive cultural growth. 

1.   Learning technology has cultural & economic impact

2.   Learning technology is a multiplier

3.   Learning technology extends cognition

4.   Learning technology replaces teaching with learning

5.   Learning technology scales

6.   Learning technology is enables new pedagogies

7.   Learning technology draws from consumer technologies

8.   Learning technology melds hardware and software

9.   Learning technology can be both good and bad

10. Learning technology gets declassified

Learning technology has cultural impact

There have been many attempts to read history as being catapulted forward in economic cycles caused by innovations in technology. What no one has ever done is apply that logic to learning technologies, yet technological advances may have led to specific advances in stone axe technology and cave images, that required the teaching and learning of sophisticated skills. Writing, a skill that had to be formally taught and learned, undoubtedly led to cultural and economic change, as did the alphabet, that tweak to writing that gave eastern Mediterranean culture a central role in early science, philosophy and literature, especially in Greece, a cultural root that reverberates down to us today. The world was in a steady state during the Dark Ages when writing technology was stuck in manuscript production, in the hands of a priestly class, but sprang into life with printing, causing a Scientific Revolution and Religious Reformation. The era of mass schooling and mass production of pencils, pens, paper, notebooks, chalkboards, literally educated the masses, increasing the cultural capital of the world. Then came calculators and computers that sped up technological progress. It got us to the moon and energized economies and the management of capital. Hot on its tail, as this process is exponential, came the internet, which globalized finance, economics, production and consumption. Finally, we are in the era of AI and data. We are already feeling the pressure in the age of algorithms. For the first time we have learning technology that doesn’t just help us tech and learn – it can learn itself. We are only just getting to grips with the idea that learning is not the sole domain of our genus but of the very technology we have created.

On the mechanics of technological change, a seminal text is Schumpter's Theories of Economic Development, where cycles of economic development are seen as being driven by innovative technology as their cause. Carla Perez in Technological Revolutions and Financial Capital expands on the idea to identify specific cycles of over-effusive investment, slumps, then a period of fruitful investment that results in significant improvements in productivity. In other words, we overestimate technology in the short-term, underestimate it in the long-term. There is a parallel process with learning technologies. Technologies are invented, then go through a period of non-learning use, eventually being applied in teaching and learning. It is when a technology is used in teaching and learning that the multiplier effect works through to economic growth.

Learning technology is a multiplier

These learning technologies; language, writing, printing, computers, the internet and now AI, released exponential growth in knowledge and learning. The ability to learn, document, write, calculate, explain, plan and execute most of what we normally think of technology (mechanical, electrical, chemical and physical) relied and still relies on learning technologies that underly their ideation. The great leaps forward in the history of our species have been on the back of these leaps of the imagination, the invention of technologies that allow us to use and document our imaginative output to further civilisation. It has given rise to great art, science, advances in medicine, finance and every other human achievement. 

Learning technology is a cultural and economic multiplier. It is not simply additive. It is the root cause for paradigm shifts. These shifts are often seen in terms of materials (stone, bronze, iron, water, steel, steam, silicon chips) or mechanical devices (weapons, ships, steam engines, looms, cars, domestic devices, airplanes, rockets, satellites, computers, tablets, smartphones), when what lies beneath their development is learning, enabled by learning technologies. The more obvious visible, physical manifestations, are in fact, the effects or products of that wider and deeper learning. Learning has been progressively accelerated by learning technologies and that has had a compounding effect on output. With each successive development of the technology, from cave paintings, writing, alphabets, printing, computers, the internet and AI, we get an acceleration.

Yet learning technology is mostly ignored in favour of the crude, mechanical history. We think of technology in terms of one form of technology – the obvious and physical. We still fail to recognise that the history of technology has a hidden story of cognitive effort and progress that made this surface technology possible. Beneath the physical manifestation of technology lies cognitive technology that the brain itself uses to create and share ideas – learning technology. “At a few times in history, people have hit upon technologies that multiply, indeed exponentiate the growth of knowledge” said Stephen Pinker. They are inflection points in the history of our species.

Learning technology extends cognition

Where does the mind stop and the rest of the world begin? asked Chalmers and Clark in The Extended Mind. Their examples include the use of pens and computers to learn and do things. 

Cognitive technologies, such as speech, writing, alphabets, mathematics, audio, video and other media, allow our minds to directly create, express, manipulate, distribute and scale our thoughts. They also allow our minds to listen, read, understand and learn. The pen, pencil and keyboard and touchscreen can be seen as extensions of consciousness. As tools they are almost part of one’s mind and body. Some philosophers have put forward this idea of extended consciousness or cognition as an alternative theory of consciousness. Once written, the object is then a piece of captured consciousness that can be read by others. It is this creation of another archived realm that allows us to escape the tyranny of time and place. The written word can be read at any time in any place. It becomes an object in itself, the creation separated from its creator. This is how learning escapes the tyranny of the human teacher.

Whether as learner or teacher, learning technology extends the mind in several dimensions. First and foremost, it changes long-term memory, the fundamental aim of learning. With that change we escape the tyranny of time by being able to think about the past as history and future possibilities. The faculty of imagination is fuelled by knowledge and skills. We can also escape the tyranny of location and learn about places beyond our place of residence, even planet. It also provides the ability to learn to read and write, learn other languages, appreciate other cultures, learn mathematics, science, appreciate art. Some see learning technology as literally an extension of consciousness, the pen or smartphone as part of consciousness.

Many technologies were extensions of and protection of our bodies, clothes, homes, domestic appliances, tools, weapons, transport, glasses. Some, however, are extensions of the mind; pens, pencils, erasers, print, books, computers, smartphones, digital assistants and so on. Language appeared millions of years ago, writing thousands, printing hundreds, broadcast media a hundred or so years, and in just decades we’ve seen computers, the internet and AI appear. We are now seeing the exponential invention of ‘cognitive’ technologies. 

Learning technology replaces teaching with learning

This is a matter of degree but there can be no doubt that writing, printing, broadcast media, computers, the internet and now AI and data, have to different degrees replaced the need for a physical teacher. Most learning no longer takes place in the presence of a teacher but in other contexts made possible by learning technology. We read, write, watch videos, hear podcasts, access the vast knowledge base on the internet and now use voice assistants, all in the absence of other humans. With each successive stage of learning technology, the act of learning has changed. The locus of learning has shifted away from the live, synchronous teacher to asynchronous learning. This is an uncomfortable truth for many but a truth nevertheless.

Learning technology scales

As learning technology evolved, its scalability increased. As soon as we invented writing, we freed learning from the tyranny of space and time. Knowledge could be captured, distributed and be made available to many others in different places, at different times. This was accelerated with printing, as identical copies could be mass produced and distribution could take place at national and international levels. This scaled up even more with broadcast media, such as radio and TV. It went global with the internet. Another dimension of scalability is now possible with personalisation, with AI and data-driven learning.

Learning technology is enables new pedagogies

New pedagogic techniques are enabled by new learning technologies. The humble pencil and eraser allows one to fail, erase and retry, allowing one to fail as one learns. That is a good, simple example of how a piece of technology can enable a pedagogic advance. Cutting, pasting, spellcheck, grammar check, synonym selection and editing tools all help one to write. Allowing learners to do cognitively effortful learning on a computer allows them to do things on their own free from doing it at a specific time and place. AI and data-driven systems allow pedagogic techniques like personalisation, deliberate practice, spaced practice and motivational pedagogies such as behavioural, nudge theory to be delivered. In general, there is a wider set of pedagogic options that can be blended into an optimal blend suited to specific target groups of learners, and types of learning.

Learning technologies draw from consumer technologies

Few technologies were ever designed specifically for learning. Early writing was almost exclusively used to ‘account’ for the products of agriculture and other goods, exchanges and treaties. Manuscripts were for religious consumption only. Printing was initially restricted to Biblical and other related texts. Broadcast media were mostly about news and entertainment. Computers were, and are still largely, the technologies of work and play. The internet became an agora for information, e-commerce and social media. AI and data are used for practical purposes in the mediation of interfaces such as Google, social media, Netflix and Amazon. They have all been used for teaching and learning but this came later and on a smaller scale. But size is not everything. It is the fact that they could be used to learn that gave all of these technologies real potency. In every case, learning turned out to be the killer application.

Learning technology melds hardware and software

The tendency is to see technology in mechanical, material terms. We see this in the many books about technology, such as Usler's The History of Mechanical Invention. The word technology comes from the Green Tekhne (art, craft) and logia (writings). My definition of ‘learning technology’ includes both hardware and software, as almost every piece of modern hardware has, as an integral part of its function or output, something that can loosely be called software. The hardware of pens, pencils, erasers and paper have writing as their software. Printed books and papers have writing and images as their software. YouTube has video content as its software. The internet has every media type as its software, as well as code that controls the logic of delivery. In all of these cases the hardware is inseparable from the software and must be seen as being entwined as technology. Of course, in most discussions of technology there is a bias towards physical, tangible, mechanical devices, but as James Gleick has shown in his book ‘The Information’, many of our most important advances have been intangible technologies, such as writing, alphabet, audio, images, video, software and social media.

Brian Arthur's The Nature of Technology, sees combinations of technology as the deep driver of technological innovation. It is especially true of learning technology. The long history of learning technologies from the pigments, brushes, pots and lamps used in cave drawings have always been combinations. Writing instruments, whether brushes, pens or pencils, need pigments or inks to transfer writing to yet another form of technology, papyrus, parchments or paper, which in turn allow is to replicate texts as software to be read. Combinations of different technologies - presses, metallic letters, ink and paper - gave us printing, with copied texts being the readable software. The computer brought together different media; text, graphics, audio, video, animation and now VR and AR in a combined, multimedia device as media of the mind. The internet brought these to a global audience for learning, with Wikipedia for text, YouTube for video, podcast services for audio and many other free learning resources, such as MOOCs, Duolingo, Khan Academy. So learning technology has always been a combination of technologies, physical and psychological, right through to the modern smartphone, which is a learning device among other things.

Learning technology can be both good and bad 

The pen may be mightier than the sword but most technology, also learning technology, still has ethical consequences. These ethical dimensions are fairly muted compared to weaponry, carnage of driving cars and fossil fuels in engines. We continue to drive cars in the face of the undisputable fact that nearly 1.5 million people die horrific deaths every year in car crashes. The figure for those maimed and injured is much higher. This is the casualty equivalent of an annual World War. Many other technologies, have similar ethical dichotomies. Plastic syringes may save lives but plastic may be killing our oceans. Bitcoin and blockchain may be innovative technologies but as havens for money laundering and tax evasion, along with energy needs harmful to climate change, are a consequence. Learning technologies are nowhere near as lethal but few would deny that there are downsides. Paper production means felling trees and is one of the most polluting manufacturing processes we have ever invented. Billions of plastic bricks have been produced by a famous Danish toymaker. The internet and AI have given us ethical issues that are well known.

Even the humble LMS has had a genocidal side. Tom Watson, CEO of IBM flew to meet Hitler in 1939 and sold him a primitive, punch-card, Learning Management System, called the Hollerith system. As told in in the excellent book IBM and the Holocaust by Edwin Black, it stored data on skills, race and sexual orientation. Jews, Gypsies, the disabled and homosexuals, were identified and selected for slave labour and death trains to the concentration camps.

Although some present education is always intrinsic good, it is not without its ethical problems. At one level it can be argued that it sometimes increases social inequalities and uses time and money that would be better spent elsewhere. It has also been used for ideologies that have proved harmful, at the outer extremes of the political spectrum. The hideous genocides of Stalin, Mao Tse Tung and Pol Pot were the result of an educated class producing ideas that were used to literally eliminate entire strata of populations. The learning technology of propaganda has been used to educate and, even worse, ‘re-educate’ dissenters. It is clear, then, that learning technology is not always an intrinsic good. It can be a pedagogic trap, even destructive force.

Learning technology gets declassified

We also have to recognise that what we see as technology tends to fade and be declassified as technology. Anything invented before we were born is often seen as just being there and not categorised as technology. So writing, pens, pencils, erasers and paper are de-technologised. Books, magazines and printed materials are seen as worthy precursors to new technology, ignoring the fact that they were the technology of their age and seen with similar levels of suspicion an condemnation. Chalkboards are worthy, PowerPoint is unworthy. Broadcast media such as film, radio and TV have now achieved that standing as technology with a certain prestige, compared to new media. Even more traditional services on the internet are regarded with fondness when compared to the products of AI and data. Time is a great healer and the technology of the day now quickly becomes the technology of yesterday and not really technology at all.

In my next piece, I outline the history of learning technology. This will be followed by pieces on each stage.

Stage 1 Prehistory

Stage 2 Writing

Stage 3 Printing

Stage 4 Broadcast media

Stage 5 Computing

Stage 6 Internet

Stage 7 AI and data

Lifelong learning is a conceit. Life is not a course. To live is to learn

Every year we get a slew of reports full of platitudes about ‘Lifelong Learning’, usually, of course, by people who make a living from selling paper qualifictions. 'Lifelong Learning' trips off the tongue (beware of alliteration) but it’s a glib, confused, if not misleading, phrase. No real person describes themselves as a ‘Lifelong Learner’ – it would sound pompous, even ridiculous. To be honest, I’ve come to believe that Lifelong Learning is NOT a 'thing', just the rhetoric one sees in reports and PowerPoints. It has become a tired old phrase, a construct only used by educators. But it is an educational conceit. Educational institutions have no intention of letting their models go which is why they play little role in real Lifelong Learning. That’s because Lifelong learning has little to do with ‘lifelong schooling’ or ‘lifelong formal learning’.

Myth of reskilling

The myth is that we will be reskilling as we change careers every few years. No we don’t and no we won’t. Know that quote “65% of children starting primary school today will enter into jobs that don’t currently exist” That was made up, a complete fiction. Even if true, the idea that Universities are the solution to this need is ridiculous. Few adults go back into formal education. 

Extended schooling

In truth, most of us, after being put through the wringer of intense schooling, can’t wait to see the back of it. Even those who extend schooling for another three or four degree years are often weary of the endless diet of formal learning and exams. If Lifelong Learning means more and more qualifications, forget it. Lots of people are now being prompted and pushed into being academic, when they’re not, prolonging their schooling, when the evidence suggest that it neither raises their productivity nor enriches their lives. Lifelong learning, so far, has meant extending schooling. Of course, the answer to bad schooling is always more schooling. We may even want less learning. More people are getting ‘schooled’ for longer and longer. But to what end? Signalling. Credential inflation is the wasteful result.

Reframe learning

We need to reframe lifelong learning and recognise that very few return to years of formal schooling. Lifelong learning needs to recognise that you have had a heavy dose of formal learning at school, possibly college or University, then go on to gain the skills to be a more autonomous, self-directed learner. As Winston Churchill observed ‘I am always ready to learn although I do not always like being taught’.

Few grown-ups yearn for the student experience and those that do would do better doing it online. Adults do not want to be infantilised by this sort of jargon. They’re adults not learners. The older you get the less inclined you are to want to cram and sit exams, as you know you’ve forgotten most of what you previously learnt. I’m all for recommending that people remain curious throughout their lives but life is not a course.

In my lifetime, I‘ve seen the Lifelong Learning lobby dismantle vocational learning in favour of University for all – well not really all, as they killed off support for adult learners (which is what Lifelong Learning was supposed to be about). They talk the talk but at the end of the day – the focus has been on 18 year-old undergraduates. That’s a shame. For all the rhetoric they default back to their own little world.

Life is for living, not learning 

Lifelong Learning is a shallow phrase as it assumes that we need something we don’t. For many, the book group or film club is formal enough, a group that encourages you to read something new and different. Life, for most, is for living, not learning. We learn to lean without formal structures, following our interests and curiosity. To present lifelong learning as a return to college and formal qualifications is largely credentialism. Most adults become more autonomous as learners. The Long Tail of lifelong learning for most is to learn within the workplace or turn to the web and free resources to learn through tools like Google, YouTube, Wikipedia and the available and growing abundance of free resources and services. 

Lifelong learning, for most, is the Long Tail of informal learning through work, self-development and interests. Technology will continue to increase opportunities to learn for the curious. To live is to learn.

10 powerful online feedback (should be called feedforward) techniques

Most of the frustration experienced by learners is poor, slow or inadequate feedback; the embarrassment of being asked questions in a classroom in front of others, even one-to-one by a human tutor, the fear of asking questions in a classroom or in a Zoom session, as you’d feel stupid, the lack of opportunity to ask for clarification or ask questions in a Zoom lesson, classroom or lecture, the email reply that takes days to come back, that solitary mark A-D and brief comment on a piece of work or general and non-specific comments like ‘needs more clarification’.

The solution is good feedback. Feedback is the lubricating oil of teaching and learning. Feedback accelerates learning. It can therefore reduce the amount of time spent teaching. It motivates and propels learners forward. You need to work hard to keep learners on task, feedback is the spark and stimulus that gets them to the next stage. 

Technology can use feedback to propel online learning. We spend so much of our technology time to present linear, media ‘experiences’ that we forget about the locomotive power of feedback. Creating videos, graphics and screeds of text is easy, feedback is personal and hard. Yet there are methods that have emerged from recent technology that make it much easier. We need more focus on technology to deliver feedback as well as media.

There are many forms of feedback; confirmatory, explanatory, consequential, real-time, semantic, media specific, peer-to-peer, reflective, calls to action. It is a powerful aid to learning and should be used to power learners forward.

1. Confirmatory

Right, Correct, Yes, Wrong, Incorrect, No Try again. This feedback simply confirms whether you have succeeded or not.

2. Hints

Hints give snippets of information to nudge learners forward in a task. They are useful in making the learner think deeper about the problem. (Lavbic, Matek & Zrnec, 2017).

3. Explanatory

Go one step further and explain WHY you got something right or wrong. Note that even when it is right, reinforcing with different wording and extra information and explanations can be useful.  A Clark and Mayer (2016) meta-study shows that this is superior to no or corrective feedback.

4. Consequential

Feedback can lead to consequences in branched and other forms of simulations. Here you provide remedial or fast-track routing, depending on the response. This can be very sophisticated in adaptive learning where personalisation, through data and AI. uses these techniques.

5. Realtime

Feedback in real time is common in VR and real-time simulations and games, where consequences of decisions and actions are immediate as they would be in real life.

6. Semantic

You use AI to semantically interpret responses and act upon the meaning. Sentiment analysis has also been used to determine the subjective feelings of the learners to deliver feedback.

7. Media specific

You can choose to provide positive feedback in a specific confirmatory medium, like audio or video, using text or other forms of feedback for negative responses. This strengthens the memory of the positive act and avoids memories of negative responses.

8. Peer-to-peer

One way to scale feedback is to get one learners to peer review each other. In pairs or groups. There are systems that provide this functionality.

9. Reflective

Leaners can be asked to reflect mentally or write a reflective piece, as a forms of self-referential feedback. 

10. Call to action

Learner is asked to do something in the real world as a result of their online response. This can be a nudge towards practice and transfer. It may trigger an action in a spaced or retrieval practice system.

Thanks to Connie Malamoud who inspired me to write this blog.

Empathy… “sounds wonderful but the search for empathy is simply misled” Donald Norman

I was looking at design methodologies and kept seeing the word ‘EMPATHY’ pop up. It puzzled me. I’ve read my Hume and thought, yes, empathy is a subjective feeling. If I have empathy with someone, it means I feel for them. Then I realised they were not using the word in this sense. They meant, literally putting yourself in their shoes or minds. That I find odd. How would a 25 year old graduate designer put themselves into the mind of someone who fits gas boilers? What they actually meant was, think about where they work, what they have to do to for the job and how they access learning and what they need to learn that fits their background. This actually comes down to analysis. But this is a bait and switch.

Donald Norman says, of this call for empathy in design, that “the concept is impossible, and even if possible, wrong”. I was seeing empathy used in pieces that actually mentioned Norman as one of their heroes! Yet here he was saying it was wrong-headed. He is absolutely right. There is no way you can put yourself into the heads of the hundreds, thousands, even tens and hundreds of thousands of learners. As Norman says “It sounds wonderful but the search for empathy is simply misled.” Not only is it not possible to understand individuals in this way, it is just not that useful.

It is not empathy but data you need. Who are these people, what do they need to actually do and how can we help them. As people they will be hugely variable but what they need to know and do, in order to achieve a goal, is relatively stable. This has little to do with empathy and a lot to do with understanding and reason.

Sure, the emotional side of learning is important and people like Norman, have written and researched the subject extensively. Positive emotions help people learn (Um et al., 2012). Even negative emotions (D’Mello et al., 2014) can help people learn, stimulating attention and motivation, including mild stress (Vogel and Schwabe, 2016). Although excessive stress can be detrimental to learning and memory. We know that emotions induce attention (Vuilleumier, 2005) and motivation that can be described as curiosity, where the novel or surprising can stimulate active interest (Oudeyer et al., 2016). In short, emotional events are remembered longer, more clearly and accurately than neutral events.

But trying to induce emotion in the design process is just not that relevant. We are in such a rush to include ‘emotion’ in design that we confuse emotion in learning process with emotion in the designer. It also seems like lazy signalling, for not doing the hard analysis up front, defaulting to the loose language of concern and sympathy.

All too often we latch on to a noun in the learning world without thinking much about what it actually means, what experts in the field say about it and bandy it about as though it were a certain truth. This is the opposite of showing empathy. It is the rather empty use of language.

Bibliography

Norman, D.A., 2004. Emotional design: Why we love (or hate) everyday things. Basic Civitas Books.

Norman, D., 2019. Why I Don't Believe in Empathic Design.

Um, E., Plass, J.L., Hayward, E.O. and Homer, B.D., 2012. Emotional design in multimedia learning. Journal of educational psychology, 104(2), p.485.

D’Mello, S., Lehman, B., Pekrun, R. and Graesser, A., 2014. Confusion can be beneficial for learning. Learning and Instruction, 29, pp.153-170.

Vogel, S. and Schwabe, L., 2016. Learning and memory under stress: implications for the classroom. npj Science of Learning, 1(1), pp.1-10.

Vuilleumier, P., 2005. How brains beware: neural mechanisms of emotional attention. Trends in cognitive sciences, 9(12), pp.585-594.

Oudeyer, P.Y., Gottlieb, J. and Lopes, M., 2016. Intrinsic motivation, curiosity, and learning: Theory and applications in educational technologies. Progress in brain research, 229, pp.257-284.

Foreword to Conducting performance-based Instructional Analysis by Guy Wallace

Foreword to Conducting performance-based Instructional Analysis by Guy Wallace

There are two things that are in danger of extinction in learning, with all the focus on learning in the workflow and learning ‘experiences’. They lie at the ‘top' and ‘tail' of a learning programme.

The first, at the top, is the abandonment of analysis before you design a learning intervention. Detailed analysis seems to be out of fashion but its absence can lead to learning experiences that are simply illusory. Guy has a lifetime of experience which he brings to bear on the management and process of delivering a learning project. His focus on stakeholders, for example, is just one of many solid pieces of advice to guide the novice.

But it is at the tail that Guy’s method really shines. His obsession with ‘performance’ is so often swept under the carpet by those who think that learning is just about knowledge. How do we get what we know turned into actual practice and performance? This is what lies behind Guy’s methodology. He is relentless in chaining together a causality that leads to actual competence and performance.

It was refreshing to see someone who has been around long enough to remember Gilbert’s book on Human Competences and Gloria Gery on Performance Support. We are entering an age where AI and smart software can now deliver, push and pull instruction, to support learners when they need it. This puts learning much closer to performance. Transfer is that much easier when you learn at the very moment you put it into practice.

Analysis, process and performance - ignore them at your peril.

OEB debate on Higher Education... 7 mins each... here's my 7 mins worth...

 ‘This House Believes Universities, in Their Current Form, Are Unsustainable as Mass-participant Institutions’

We each had 7 minutes to put our case… here’s mine…

My 1st argument is PERSONAL

I have two sons – twins, now 27 years old – interesting experiment – one went to University and has a degree in AI, one did NOT. He hated school and University, sitting in lectures would have sucked then life out of him. The one who did not has done as well as the other, runs his own business, and employs graduates. And that’s my point. We need to create a system that works for everyone not just the academic kids. 

We have an estimated shortage of 40,000 nurses in the UK, so let me tell you another personal story, both my mother and sister were nurses. They would not have been nurses now. The degree qualification excluded working class women and men from that profession. It increases class inequalities. We have to stop seeing University, as some sort of religious imperative. Like Catholic indulgences, where you have to pay to get the piece of paper or you fall into the HELL of low status and precarious employment. We need a Reformation and this motion suggests that. 

We need to REBALANCE our education system more towards people like my son, sister and mother.

2nd  argument is POLITICAL

In 2010 Peter Turchin, a scientist at the University of Connecticut who uses maths to model historical change, made a startling prediction in Nature. He said, “overproduction of young graduates with advanced degrees” would lead to social unrest due to rising inequalities. TTurned out he was right. The evidence… Trump, Brexit, the Gilet Jaunes in France… The graduate class has not only screwed over the rest of the working population over, it actually looks down on them – calls them deplorables…  The two best books I’ve read on Brexit by Stephen Davies and David Goodhart argue that this is what is behind such social discontent – the rising inequalities between the professional, urban, middle-class graduate classes and the rest. It was the graduates in Wall Street who caused the financial crash, nor ordinary working people.

We need to REBALANCE the inequalities in society and unite our DIVIDED societies, divided now by education…and not look down on people just because they didn’t go to University.

3rd argument is ECONOMIC

We have demoted vocational skills, outsourced manufacturing skills to China and wonder why our economies are faltering. Yet the graduate barista is now the norm. The destruction of vocational education has been a moral disaster and disgrace. But not everywhere. And I tip my hat to Germany, Austria and Switzerland who have more balanced systems and, unsurprisingly the strongest economies in Europe. If you think that Universities drive economic wealth think again. Taiwan, South Korea, and China grew their economies in spite of having low University infrastructure. 

As Bryan Caplan here at Online Educa, 80% of this is SIGNALLING but the cost of that 80% is needed elsewhere for healthcare and spending on those in real need.

In the US the cost as of now is a staggering $1.67 trillion to the national debt and don’t think that forgiving student debt is the answer. Forgiveness would be a highly regressive policy. Full cancellation would put $192 bn into the pockets of the top 20% of earners and a measly sum to the bottom. It does not rebalance, it increases inequalities.

We need to REBALANCE the system economically for growth and prosperity, as it costs too much.

4th is PEDAGOGIC

My son did a degree in AI at a European University. Few of his lectures were recorded (despite the students pleading for them to be so). Two hours of high end calculus is not easy and actually a bad way to teach calculus. Online resources were rare. Universities, globally, are still trapped in the 1 hour lecture (only because the Sumerians has a 60-base number system), the essay is still a dominant form of assignment and assessment. Yet look at the scale of essay mills. You can buy a freshly written Masters thesis for less than €1000. And when it came to Covid the rush to the university of Zoom – exactly what you should NOT do in online learning was bizarre. This is ONLINE EDUCA folks we should have done better…

We need to REBALANCE towards online delivery. All courses should be Blended Learning and digital by default.

5th is CULTURAL

Lastly a cultural argument. Universities, as Jonathon Haidt, in his excellent book The Coddling of the American Mind shows, our universities seem to be producing people with less, rather than more, resilience in the real world. We had the unedifying spectacle of junior employees of a global publisher Random House/Penguin literally crying their little eyes out when they heard that they employer was publishing a book by Jordan Peterson. I was raised in a world where crying, when you couldn’t get your own way, was abandoned with diapers - not whenever a work colleague thought differently from you. Debate is being cancelled. Diversity of though no longer respected.

We need to REBALANCE towards freedom of speech and diversity of thought.

Finally…

We’re in this debate but how many of us did NOT go to University? This, I think, is a problem. We have produced a graduate class that speaks largely to itself, in bubble conferences for graduates, talking about US. But this DEBATE is not about US!  

This is ONLINE EDUCA, so let us  pedagogically REBALANCE towards vocational, towards online and blended learning, to prevent further political, economic, pedagogic and cultural damage. With my friend Brian, I recommend this motion to the House.