M-learning - from a van!

I gave talk today about 'mobile learning', working from my VW campervan in remote parts of Scotland, with mobile, hotspotted laptop, solar power on roof & storage battery. Next time, plan to give that talk, about freeing learning from tyranny of place, from my campervan.

While on the move, doing nearly 200 miles from Brighton to Cape Wrath at the extreme NW edge of Britain, we (Gil, Doug the dog and I) used a lot of tech and learned a lot.

The idea had been brewing for some time. Buy a van and get out there but it was watching Nomadland that sparked the purchase. There really is a social and demographic movement around this, especially in the US and now elsewhere. Not just the vacation van but the living and working van, a house on wheels. My young friend Lewis lives in an old, red Post Office delivery van. It was cheap and buying a house in Brighton impossible without external support. He watches no TV, reads a lot, has a community of similar friends, works when he needs to top up his funds, and sets off when he can, to Scotland, wherever. On a grassy mound behind a huge deserted beach on the northern coast of Scotland I had a long conversation with Noreen, from Northampton, who, before Covid, sold her house, bought a van and was sitting here with her beautiful alsatian, clearly at ease with the world. “My kids and mates thought I was mad…” she said, “but it’s easily the best thing I’ve ever done. I’m living, nor proving anything, not answerable to anyone, that’s the point.” Occasionally she’d go back and stay with her now grown-up kids but soon wanted to back on the road. She put me on to ‘park4free’, an app that layers free parking spots for vans on to Google maps. Her van was full of things she had made from shells and wood. She had made it her home. All she needed was fuel and food.

We did our van research online, found the van online, made the purchase with an online transfer and off we went. First trip was to Canterbury, at the end of a year-long pilgrimage to St Martins, the oldest Church in the English speaking world. We parked in the long-stay car park (recommended in Britstops, a book with free or cheap overnight stops), which was empty and had free buses running to and from the city. It was blissful and we ironed out a few things, like the right bedding, storing things so they don’t rattle and so on. Then the big one - up to Scotland and the N500, 500 miles of stunning landscape. We checked the weather runes, the van was made ready, and off we went. Doug the dog loved it. The van was his den and he was with his family. He ran on deserted beaches and barked happily, without rebuke. A dog and a van are a perfect match.

Just a bit about the van comms. It has, on the dashboard, a screen that can be paired with your mobile, so satnav and calls can be made through the speaker system in the car. My front seat was incredibly comfortable and can be rotated 180 degrees to face back into the van. There’s a table inside the van. So the van becomes a mobile office, kitchen, dining lounge and bedroom. On the roof is a long solar panel that powers the lighting, fridge and water pump. You can also charge your mobiles and iPad from this 12V source. It never runs out. Powering a laptop requires more punch but OK if you’re hooked up in a campsite or have a storage battery.

Comms, either through wifi you find when you’re parked up (in Ullapool they had a town wifi service) or through your mobile as a hotspot, was fine. To be honest, for meetings, the mobile with 4G was adequate, even, as we found, at the very top of Ben Nevis. I managed to participate in board meetings (one, in a good way, the most important in the company’s history), gave talks at online conferences, made and took calls. It was all rather easy.

Google maps was, of course, invaluable, as was the app ‘park4free’. If we did need a campsite, you could find one and book it online. The history (clearances, Culloden, U-boats etc), geology (3 billion year old rocks and astounding formations), flora (wild flowers and orchids galore) and fauna (seals, deer, raptors, puffins, even a snow bunting in the snow at the top of Ben Nevis) were all available, in depth, online. Photography’s my hobby and I could load up and post images throughout the entire trip. I can honestly say that it was both exhilarating and satisfying. I haven’t felt this free and happy for a long time. Sure it was partly an escape from the straightjacket of Covid but it was more than this. It was a glimpse into another way of living, free from the trappings and tyranny of a fixed location. Every day gives you new perspectives. Everyone we met seemed happy, talkative, helpful. It was as much of a community as any fixed place. 

‘Autonomy’ is the word I’d use. The freedom of being on the move. It opens and stimulates the mind. You walk more, think more and if you want to focus on a topic, it allows you to take a deep dive, as you have the time to take the leap. You just find yourself thinking at a deeper level. We downloaded a motherload of Netflix stuff and podcasts but, to be honest, the real world was so spectacular and we did so much that we barely watched anything on a screen. I drifted into reading and writing more and was just as functional, if not more productive, as I was at home.

It’s not that we should all be living and working from vans. But that’s a real option, I think, for the young and maybe half and fully retired. The lesson is that learning, real mobile learning, can free itself from the tyranny of the clock and place. Most learning is asynchronous, done in your own time with you in control. Learning is a process not a live event and the idea of having to turn up for umpteen lectures per week (40% dont turn up anyway, even though they’ve paid), is an anachronism. It is certain that more people will be working from home post-Covid. Gardner predicts that 80-% of classroom training in the workplace will disappear. Young people will almost invariably learn this way in the workplace. Mobile learning turns out not to be learning from your phone, it is learning anything, anytime, anywhere.

Eric Mazur- peer and online learning

Mazur is Professor of Physics at Harvard but perhaps better known as an educator. He has taken a data-driven approach to his teaching and moved from lecture to peer learning then online learning, in response to that data. He uses pre-and post tests to assess the methods he uses.

As an evangelist for peer learning and online learning, he is an academic who has taken his research mindset into his practical teaching. Spurred on by research, such as Freeman (2014), showing that active learning results in higher attainment than lectures, he has constantly striven to improve his teaching, all on the back of proven, measurable results.

Peer instruction

Explained in his book Peer Instruction (1997) Mazure xplained how he used clickers to improve his teaching for many years. Rather than deliver long lectures, without interruption, he stops at key points and asks diagnostic questions. These questions tend to be natural language questions that really test the underlying principles of physics, rather than the application of formulas. Teachers/lecturers can use them diagnostically to assess the overall state of knowledge of the class. This, as Dylan Wiliam states, needs the use of clever 'hinge’ or diagnostic questions, that really do test understanding, as opposed to recall. This is precisely what Mazur does at Harvard with stunning results in attainment. If the histogram shows that many of the class have not understood the point, he arranges them into groups so that peer-to-peer learning can take place, asks the question again, then moves on. The data he’s gathered suggests that this approach has led to significant increases in attainment and some universities have since adopted this approach. Note that it is the feedback process that is important. Mazur claims that coloured cards work just as well.

Mazur also found that seating in classes has pedagogic consequences. Move poor performing students to the front of the class and they improve attainment, yet the attainment of high performing students is unaffected when they are moved to the back but when moved to the corners, the whole class does better.

Online learning

Mazur described the Nobel winners who teach as “being no better than dinner party commentators when it comes to teaching and education”. He has spent decades pushing active learning and interactive learning and after he redesigned and shifted his course at Harvard completely online during the pandemic, claimed “I have never been able to offer a course of the quality that I’m offering now. I am convinced that there is no way I could do anything close to what I’m doing in person. Online teaching is better than in person.”. Minimizing synchronous elements he found that learners had better attainment gains and felt better supported than face-to-face students. He suggested that, after seeing the gains, it is “almost unethical” to return to classroom teaching.

His approach is to use lots of regular, but small assignments, make it acceptable for students to fail and redo work, rely on peer pressure for engagement and completion. Students work through a structured online textbook, posing and answering questions online for each other then groups do assignments and present, in their own time, as groups. It is this freeing learners from the tyranny of the clock that he sees as a vital ingredient in his methods. Another advantage of being online is that there is no front to back seating in rows. “When you teach online, every single student is sitting in the front row” says Mazur. This tradical shift from peer learning in lectures to peer learning online, marked a second major another shift in his thinking.

Conclusion

Mazur is a world-class physicist and teacher. Rare in Higher Education, he has applied his experimental and data-driven approach in physics to teaching and learning. This has resulted in a series of practical teaching methods that have been widely applied in Higher Education and other contexts.

Bibliography

Mazur, Eric (1997). Peer Instruction: A User's Manual, Prentice Hall. ISBN 0-13-565441-6

Freeman, S., Eddy, S.L., McDonough, M., Smith, M.K., Okoroafor, N., Jordt, H. and Wenderoth, M.P., 2014. Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), pp.8410-8415.

Teaching: Why an Active-Learning Evangelist Is Sold on Online Teaching

https://www.chronicle.com/newsletter/teaching/2021-05-27

Little bits of transcendence?

Easy to get too esoteric over this Covid malarky but has something deep and oddly subversive occurred during Covid? Some sort of personal reassessment? It has for me.

Have people seen that work, even education, is not all that it used to be in our lives, that schools and offices, far from being rich social spaces, can be  unnatural and, at times, quite dull, even toxic? When forced to re-evaluate what we thought gave our lives meaning - education and work - have we come to experience joy in other things? Not the endless drudge of classrooms, uniforms, courses and exams but joy and sometimes learning in real places, with real people and real life? Was the car, bus, or train commute anything at best a daily dose of discomfort, at worst a serious threat to your mental health? Did you miss dressing for work, banal offices, in modern parlance your ‘leaders’ at work? Have you eaten better not being at work, seen more of your family? Has the whole offline-online balance of work, learning, eating and entertainment changed? It’s all more blended.

We had time to breathe, literally and metaphorically. Perhaps experience more beauty, the pure blue sky with birds not planes, deliberately suck in fresh air in streets without traffic, feel the earth beneath your feet, listen more, walk more, talk more, think more, read more, sleep more, cook more, watch more great drama. Even drop the things and people who turned out to be not what you thought they were. If I were honest, I haven’t really missed restaurants, early morning trains to London, office meetings or the canyons of Canary Wharf. I’ve travelled further, not in distance, to places I’d never seen, that were nearer and turned out to be dearer to me.

Now that it’s all threatening to surge back, I have a sense of dread. Then I speak to people who’ve had similar experiences - little bits of transcendence. They’ve had time to lift their heads and see all of this busyness and business for what it is - the illusion of progress. Things have changed and they’ve changed for the better.

Monkey’s mind plays pong - no hands. Frictionless interface. Here’s my musings on 10 possible, and probable, mind-blowing applications in LEARNING

This is the most fascinating video I’ve seen in 2021. It’s haunting me. Not because of what them monkey is doing, that’s astounding in itself, but what it points to in the future, that’s mind-busting.

What’s happening here? 

The monkey got  banana milk-shake rewards through a tube by learning to play ‘pong’ with a joystick. He got rather good. Remember that pong is a complex set of skills, where you have to anticipate the physics and movement of a bouncing ball off fixed and mobile objects. It requires good cognitive and motor skills. Then they pulled the joystick lead out of its socket and  simply read the data from a fine fibre array in the monkey’s brain using AI to translate those thoughts into action. They are literally using AI to mind-read. If this doesn’t blow your mind, what will?

So what are the potential consequences for learning?

1. Learn to move

Neurolink, who developed this technology, the robot that inserts the fibres, the fibre array and the AI that reads the brain signals see its immediate application in helping those with physical disabilities, missing, damaged or paralysed limbs. One can literally use your mind to operate robotic arms or legs. So we’re on the move.  But let’s also speculate on including those with dyslexia, dyspraxia, autism, ADHD. Could we also tackle issues of inattention, demotivation and persistence?

2. Learn by doing

Beyond the fantastically inclusive ideas that this enables disabled people to perform physical tasks in life, it also means they can ‘learn’ fine-tuned motor skills. You could play a musical instrument, conduct an orchestra, paint, play lots of sports, computer games and build things. You can learn to DO things. Note that learning to DO things can include doing things at any distance across the internet, even for able-bodied people, just by thinking them.

This is the instantiation of a famous experiment that took place 20 years ago by Pascuale-Leone (2001), where two groups practised piano, one on a real piano, the other just isn their head. Both groups resulted in similar brain changes as measured by FMRI.

Let’s take this a step further, we could ALL practice DOING things with AI software that formatively assess us, in realtime, provides coached feedback to improve our performance. This feedback can, of course be automated. Such coaching would be personalised, available at any time to anyone at any place, anytime. Behavioural skills could also be assessed. Want to know if I can do something. I need only think it and you need only interpret and assess it.

4. Thinking skills 

This may also apply to other cognitive skills such as speaking and writing. We are moving towards a world where we do not have to use a physical interface, keyboard, mouse or touch screen towards voice, already available in our cars and home on our phones, with voice activation and voice assistants, such as Google Assistant, Siri and Alexa. This will move towards invisible interfaces straight from brain to screen or machine. We all have a phonological loop. Close your eyes and say ‘I am Scottish’ in a Scottish accent. You can do this because you have an internal voice as a feature of working memory. That can be read and with AI translated into words on a screen or speech.

5. Tricky skills

Maths is an area of catastrophic failure. The vast majority never get beyond basic numeracy, even then, calculating an average or understanding a logarithmic scale on a graph is beyond many. You can’t progress in maths unless you master pre-requisite skills, as it has high dependencies on prior knowledge. Imagine a system that reads what you think, diagnoses the misconception, corrects that misconception through feedback, worked examples and so on, then asks you to try things within or just beyond your level of competence at that exact moment. Personalised, adaptive maths, globally scalable from the cloud, could massively accelerate and increase attainment and massively reduce early drop-out.

Let’s take another different skill, learning a second language, another area of catastrophic failure. All kids in the UK and US get years of language education, yet few could ask for a sandwich in that language, never mind hold a basic conversation. Imagine being able to try that language, privately, without public embarrassment and have your thoughts read, interpreted by AI and constructive correction and feedback, say correct pronunciation, position in sentence or endings. Personalised, adaptive, language learning, with immersive practice available, to everyone at any time, would revolutionise language learning.

6. Critical skills

Now imagine cognitive skills, where you can engage your mind in conversation with an expert, who can tune there reprises to your level of skill. Now, transformers that encode and/or decode natural language, such as GPT-3, BERT, BART,  MegatronLM, Turing-NLG, We saw an interesting example some years back when IBMs Watson debated with a national debating champion. These transformers can generate text and start to show how complex interactions with humans, drawing upon huge databases of existing text. Digital Einstein is a recent example of this. Imagine being able to just conjure any famous writer, scientist, artist, whoever, and start asking them questions, in your mind. Your questions will be interpreted and answers based on their archived works, used to provide meaningful answers.

7. Translations

Learning is often hindered by the lack of available teachers and resources in m minority languages. Text to speech and speech to text are limited to mainstream languages. Facebook has recently managed to get AI to learn how to translate any language just by exposing the software to speech in that language. This would free all of the above and liberate those who feel trapped an unsupported in their own first language. 

8. Write to minds

Now let’s take a final leap. And it is a big leap. Almost the above is about reading minds, what of we can write to minds. This is already there with neural ink and other invasive technologies, but not at the semantic or skill level. Imagine being able to pick up maths or a second language very quickly in days or weeks not months and years. Wouldn’t that be desirable? Hell yeah.

9. Mental health

Let’s take another leap and suppose that breakthroughs allow us to write to brains in a way that reduces or eliminates depression and other widespread disorders. Think for a moment about the vast reduction in human suffering that would follow. There is no doubt that education has been increasing mental health problems, inducing stress and in some case suicide. Almost every major institution has killed or helped kill young people. That’s sobering.

10. Anything, anywhere, anytime

You may be thinking, could ALL learning be liberated by such technology? The answer is probably yes. Time will tell and we don’t yet know how long it will take. One thing we do know is that these innovations are now coming thick and fast. Combined with other physical, global innovations, such as Starlink, a global network of low level satellites that give high speed, 5G, internet coverage to the whole world with no blindspots, and we have an educational network that excludes no one.

Conclusion

They used to say that information wants to be free. That’s done. Most information. Is free. We should now ask whether education wants to be free. Teaching is a means to an end, the relatively permanent change in the long-term memory of the leaner. If we can automate that process, make it frictionless, personalised available to anyone, at anytime, anywhere, we should. Learning longs to be free. Let’s not let our conceits hold that back.

Bibliography

Pascual‐Leone, A., 2001. The brain that plays music and is changed by it. Annals of the New York Academy of Sciences, 930(1), pp.315-329.

Higher Education is exacerbating, not fixing problems, in teaching - much of it can be automated

The first step in finding a solution is to admit the true nature of the problem. In Higher Education we need to admit that the fundamental problem is that those that teach are not teachers but researchers. Lecturing is easy, teaching is hard and they often don’t have the motivation, skills or time to do what is necessary to teach effectively. Providing tons of Learning Design training and support is not the answer. On the whole this will increase time and costs. It’s time to take a more radical step, and rebalance the system back towards what it used to be.

The current model, the researcher who has to teach, is baked into the system. At its worst you have world class researchers who can’t teach at all. I knew a physicist who was taught by Peter Higgs (Nobel Prize Winner) and described him as “completely incapable of teaching at all”. At Harvard, Erc Mazur described the Nobel winners who teach as “being no better than dinner party commentators when it comes to teaching and education”. Mazur who has spent decades pushing active learning and interactive learning, after shifting his course at Harvard completely online during the pandemic claims...

“I have never been able to offer a course of the quality that I’m offering now. I am convinced that there is no way I could do anything close to what I’m doing in person. Online teaching is better than in person.”

But let’s focus back on the core problem, which is the idea that every teacher has to design their own course from scratch. No other area of human endeavour adopts such an individualistic, and therefore costly and inefficient, approach to delivery. Research requires internal intellectual reflection, attention to detail and full analysis, long-form academic writing, with a skew of personality types towards introversion and not great communication skills. Teaching requires strong social skills, emotional intelligence, good communication skills, the ability to simplify content and provide constructive feedback.

Research is the foundation of Higher Education, so what does it say about this problem? Astin’s longitudinal study (1993) on 24,847 students at 309 different institutions, analysed the correlation between ‘faculty orientation towards research’ and ‘student/teaching orientation’. The two were strongly negatively correlated. The student orientation was also negatively related to compensation. “There is a significant institutional price to be paid, in terms of student development, for a very strong faculty emphasis on research” he concluded and recommended stronger leadership to rebalance the incentives and time spent on teaching v research. Note that this does not say that some researchers are not good teachers, nor that some teachers are not good researchers, only that, as Astin claims the research shows that there may be a large statistical mismatch. Note, that this is also not to decry either researchers or teachers, simply to point out that there is a negative correlation. 

Large studies from HEPI and HEA also show student dissatisfaction with the quality of teaching, with around a third reporting disappointment around the teaching, poor interaction, poor communication and interaction with faculty and far too little feedback. One could add to this the evidence that very large numbers of students fail to attend lectures, still the primary pedagogic method in Higher Education globally. Imagine the restaurant business reporting that 40% of their customers failed to turn up for their meals, even after they had paid for them in advance. That would be unthinkable.

How did this happen?

There has been a steady pendulum swing in Higher Education away from teaching towards other activities in terms of funding, status and rewards. Over 50 years ago Jenks and Riesman (1968) showed that salary shifts, promotion and funding suppressed teaching in favour of research. Non-research faculty numbers shrank and, as tracked by Massey & Zemsky (1990) teaching time was literally swapped with research and other professional activities. They described this as ‘output creep’. Boyer (2006) also tracked the year after year swing away from teaching towards research. It was exacerbated in the UK when a large number of Polytechnics were converted into research-based Universities.

The system is now geared towards teaching undergraduates to become post-graduates and faculty, not degree completion. In a profound sense, the research-driven, teaching agenda is punishing teaching and therefore the majority of students. It sometimes exhibits itself as blaming the students, seeing them as the problem. It is rarely discussed but poor teaching puts enormous pressure and stress on students, with high drop-out rates and increasing levels of mental health problems. I have seen plenty of heart-breaking evidence of this.

Breaking the link

Until we break this link, efforts to support faculty with professional learning design will simply plaster over the problem. Recording a bad lecture is a start but not any real solution. However, it may improve even a bad lecture. Yet some Universities still, in this digital age, do not record lectures (my son can testify to this). Yet the advantages are clear; Available 24/7, rewind if your attention drops, rewind if you didn’t understand, rewind if English is your second language, pause if you want to look something up, access to linked online resources on same device, pause to take good notes, fast forward (even 1.25 speed), if known or irrelevant, watch several times for increased retention, watch when in right attentive state for learning, watch if you have been ill, watch for revision as exam approaches, not wasting time travelling to and from lecture, academics can focus on tutoring and feedback, multiple uses in courses, MOOCs etc., data gathered on who, what, when and how long watched, can be subtitled for the deaf, can be translated and subtitled and can be delivered online at any scale, at almost no cost. What’s not to like?

In truth this digitising existing lectures and content into a VLE/LMS was a useful transitionary stage - digitise what you have. We now have to use better tech to improve teaching, not just mimic what we have. The current model, even with the help of Learning Designers, who do a brave and sterling job, is still a process full of resistance and friction. Until we break the ‘'all teachers must be researchers' link, it will continue to be a secondary consideration and learning design support will continue to be a finger in the dam.

Blended learning not Blended teaching

Let’s raise the stakes and bring in Blended Learning. Post-Covid there is a recognition that this should be the norm. Yet Higher Education has a very primitive view of Blended Learning, not as an optimal blend, but as a mixture of offline and online. I call this velcro design, online as an afterthought. This is not actually Blended Learning, it is Blended Teaching. True Blended Learning takes a deep analysis of the learners, types of learning, resources and constraints, then produces an optimal blend. This analysis can and should be automated. If you think that sounds utopian, read on.

Automating Learning Design

We’ve built such a system during the two years of Covid. It takes multiple INPUTS about your learners (distribution, first language, educational attainment, motivations etc), learning (contemporary taxonomy of learning), resources and constraints (available technology, human resources, teaching skills etc). It then uses a state-of-the-art analysis to produce an OUTPUT, which is an optimal blend. Note that this blend may not be a mixture of offline and online. It can be completely online or completely offline. It also produces scores, based on research on success criteria, from engagement to transfer.

More than this we’ve also been automating the production of online content. Using AI techniques that analyse your documents, powerpoints and videos, we can produce online learning in minutes not months. It also links out to external content automatically. This dramatically reduces the time and costs.

Another successful species of automation is adaptive learning, where adaptive courses deliver, not a linear course, but one where students vector through the course at different speeds, ensuring they stay at just the right level of challenge and do not suffer catastrophic failure. These courses are being delivered in the US and China, with proven increases in attainment and correlated falls in drop-out. Going back to my primary argument, why should every teacher invent a course from scratch, when low-cost-per-students online, adaptive courses already exist? The primary reason is, of course, culture. There is no real sharing culture in Higher Education teaching.

Beyond this, contemporary LXP (Learning Experience Platforms) can automate the delivery of learning, pushing and allowing students to pull learning as they progress. Learning is a process not an event. Yet event-based-learning, lectures, dollops of e-learning is what is usually delivered. 

Conclusion

Teaching is a means to an end, not an end in itself. Don’t see the automation of teaching as a threat but as something that frees us to do more research and produce better student results faster, with less mental pressure and at a lower cost. Higher Education should not accept low quality teaching or the description becomes an oxymoron. We now have the technology to hard bake proven, evidence-based pedagogy into the software, to do things human teachers could never do, on scale. We can use AI to personalise learning, deliver the right thing to the right person at the right time and deliver deliberate and spaced practice. My fear is that I see this happening in the US and China but not in the UK or Europe. We have the oldest and finest institutions in the world but that may now be holding us back on teaching. It is time we used smart software to deliver smart learning to make students smarter, faster and at a lower cost. That will increase equity more than any other initiative in Higher Education.

Bibliography

Astin, A. W. (1993). What matters in college?: Four critical years revisited. San Francisco: Jossey-Bass.

HEPI survey (2015) http://www.hepi.ac.uk/2015/06/04/2015-academic-experience-survey-2/

Jencks, C., & Riesman, D. (1968). The academic revolution. Garden City, N.Y: Doubleday.

Massy, W. F., Zemsky, R., & State Higher Education Executive Officers (U.S.). (1990). The Dynamics of academic productivity: A seminar. Denver, Colo: State Higher Education Executive Officers.

Boyer, E. L., & Carnegie Foundation for the Advancement of Teaching. (1987). College: The undergraduate experience in America. New York: Harper & Row.