Learning is a process, not an event... events mainly give the illusion of learning...

"Part of the problem with all this talk about 'learning experience' is it's questionable whether learning is actually experienced at all."

This brilliant quote, by Leonard Houx, skewers the recent hubris around ‘learning experiences’. Everything is an ‘experience’ and what is needed is some awareness of good and bad learning experiences. Unfortunately, all too often what we see are single event, over-engineered, media heavy, video, animation and single courses that research shows, result, not in significant learning, but… 

1) Clickthrough (click on this cartoon head, click on this to see X; click on option on MCQ) that allows the learner to skate across the surface of the content, 

2) Cognitive overload (overuse of media) 

3) Diversionary activity (infantile gamification). 

What is missing is relevant effort and cognitive effort, that makes one think, rather than click. There is rarely open input, rarely any personalised learning and rarely enough practice.

The single classroom experience, lecture or online course is seen as sufficient, when it is just the start of a process that will almost certainly fail without further effort, whether it through reinforcement, application and practice.

Media rich is not mind rich

The purveyors of ‘experience’ tend to think that we need richer single experiences but research shows that media rich is not mind rich. Mayer shows, in study after study, that redundant material is not just redundant but dangerous in that it can hinder learning. Sweller and others warn us of the danger of cognitive overload. Bjork and others shows us that learners are delusional about what is best for them in learning strategies and just pandering to what users think they want is a mistake. Less is usually more in that we need to focus on what the learner needs to ‘know’ not just  'experience'.

What is needed is a series of experiences. Video is rarely enough on its own, as your working memory lasts for around 20 seconds and can hold ¾ things in mind at a time. This means, that like a shooting star, your memories burn up behind you as you watch. The solution is to keep these videos short, and make sure there’s opportunities for effortful learning through note taking, active learning experiences, application and practice. We do this with WildFire, which grabs the narration from the video and uses AI to automatically produce active, effortful learning after you have watched the video.

Research shows process works

There are those who think that Learning and Development does not have to pay attention to this research or learning research at all. It is still all too common to sit in a room where no one has read much learning theory at all, and whose sole criterion for judgement on what makes good online learning is the ‘user experience’, without actually defining it as anything other than ‘what the user likes’. Lawyers know the law, engineers know physics and it is not really acceptable to buy into the anti-intellectual idea that knowing how people learn is irrelevant to Learning and Development. It is, in fact, the bedrock of learning design.

And research shows that it is extremely rare to learn much in a single event, what used to be called sheep-dip experiences. Effortful learning, active learning, desirable difficulties, retrieval practice, feedback, spaced-practice. The research is strong in evidence for effortful learning. Make It Stick is a good start but there’s a century and more of research that backs this up. It all points towards learning being a process not a single event.

Habits are process

Increasingly, online learning is diverging from what most people actually do and experience online. Look at the web’s most popular, habitually used services or experiences – Google, Facebook, Twitter, Instagram, YouTube, Whatsapp, Messenger, Amazon, Netflix. It is all either mediated by AI to give you a personalised experience that doesn’t waste your time or dialogue. Their interfaces are pared down, simple, and they make sure there’s not an ounce of fat to distract from what the user actually needs. Occam was right with his razor – design with the minimal number of entities to reach your goal. More than this, these services make it easy for you to use and continue using. It becomes habitual. 

Duolingo uses AI and notifications to do the same – to turn the learning experience into a habit. It knows who you are what you’ve done, importantly what you’ve not done. Notifications push you forward, remind and cajole you. Learning experiences on their own are failures, habitual learning experiences leads to retention and success.

Blended learning

Blended learning is so often just Blended Teaching, some classroom/lectures, supplemented by online. In truth there is unlikely to be blended ‘learning’ unless the blend is seen as a process, where retrieval, application and practice are part of the blend. You can’t just hold a Blended Learning ‘event’. Blended Teaching is an event, Blended Learning is a process.

Conclusion

Sure, events can act as a catalyst, motivate people, get them started but it is process that changes people. An experience can be a learning experience but all experiences are not learning experiences. Many are, inadvertently, designed to be the very opposite – experiences designed to impress or dazzle but end up as eye-candy, edu-tainment or enter-train-ment. Get this - media rich is not mind rich, clicking is not thinking, less in learning is often more. Single events, like lectures, conference talks, classroom and single online courses give the illusion of learning. Learning is a process not an event.

Starlink, 5G and AI – science fiction becomes fact – how this leap will transform global online learning...

I was out in my garden last month watching a stream of satellites pass in a line overhead. It was beautiful. 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.

How much faster is 5G?

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. 

Online learning everywhere

SpaceX's satellite internet system will offer still blazingly fast speeds of up to 1 gigabit per second and within the next year, Starlink will start betas in the northern latitudes within weeks and a public beta awards the end of the year. 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.

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. 

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.

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’ 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

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. In any case this is a rising tide for everyone.

Everyone wants Blended Learning, few know what it is....

We see calls for the future to be one of Blended Learning. I agree. It had the promise to shake us out of the ‘classroom/lecture-obsessed’ straight-jacket into a fully developed, new paradigm, where online, social, informal and many other forms of learning could be considered and implemented. This needed an analytic approach to developing and designing blended learning solutions. So what happened?

1. Blended bandage
Blended learning was really just the learning world coping with the onslaught of new ways of teaching and learning. It's an adaptive response to what is happening to the learning world as the real world changes around it. By real world I don't just mean Covid, I mean changes in attitudes, learner expectations, demographics, politics, but above all massive and rapid change in technology. Blended learning, as a concept, allowed the system to absorb all of this at a sensible pace, as it was a useful bridge between the new and the old. However, seeing it as some sort of bandage or compromise can quickly disabled the idea, as it can lead not to fresh thinking but a defense of old with a few new, adjunct ideas added on.

2. Blended learning became blended TEACHING

Blended Learning books also turned out the very opposite of Blended Learning theory, namely Blended TEACHING. Teacher/lecturer/trainer authors simply sliced and diced existing ‘teaching’ practices and added a few online extras. Attempts at defining, describing and prescribing blended learning were crude, involving the usual suspects (lectures/classroom plus e-learning). It merely regurgitated existing 'teaching' methods. Blended LEARNING is not Blended TEACHING.

3. Muddled by metaphor

It also got muddled by metaphor. Blended learning started to fail when it got bogged down by banal metaphors. I've heard them all - blended cocktails, meals, even alloys. Within the ‘food metaphor’ we got courses, recipes, buffet learning, tapas learning, fast food versus gourmet. The problem with metaphor-driven blended learning is that who's to say that your metaphor is any better than mine? I’ve even seen the 'fruit blender' metaphor, trying to explain the concept in terms of a fruit smoothie! Let me put forward my own food metaphor. What do you get when you blend things in a metaphoric mixer, without due care and attention to needs, taste and palette? Blended baloney. That is often what we get with models as metaphors - dull, tasteless sausage meat. Blended LEARNING is not a metaphor.

4. Velcro learning

Dozens of definitions of blended learning then floated around, most of them muddle-headed, as they were simple delivery dualisms:

   Blend of classroom and e-learning

   Blend of face-to-face and e-learning

This ‘velcro’ approach to blended learning simply took the old classroom paradigm and added an online dimension. It was an attempt to simply use the definition to carry on doing what you did before with some extras. The problem with a definition that fixes a delivery mechanism in advance of the blended design e.g. classroom or ‘f2f’ is that you’ve already given up on rational design.

5. Broad dualisms

A slightly better approach was to broadly define the world of learning into two inclusive categories:

   Blend of online and offline

   Blend of synchronous and asynchronous

   Blend of formal and informal

The problem with these definitions is that they are looser but still wide components that may not be needed in an optimal blend. These definitions are simply too general, in that they simply divide the universe into two sets. However, the real issue with all of these definitions is that they are really definitions of blended INSTRUCTION not blended learning. We need to look at the concept from a broader learning perspective with definitions that rise above ‘instruction’ to concepts that encompass context.

6. Flipped classroom

This is just one species of blended learning and a rather simplistic version. Again, however, the focus is on blended ‘teaching’ not ‘learning’. It’s yet another fixed dualistic formula. The concept is primarily about switching the focus of teaching away from exposition towards more Socratic f2f methods. It served a purpose in proposing a radical rethink but still fits the old lecture/classroom/f2f v online dualistic mindset.

7. 70:20:10

This is a more sophisticated version of blended learning in that it emerges from theory and studies that show how people actually learn in practice, as opposed of supply type models of teaching. Around 70% of learning comes from experience, experiment and reflection, 20% from working with others and 10% from planned learning solutions and reading. It’s common in organizational learning, it proposes and explained in superb detail in 702010 towards 100% performance by Arets, Jennings and Heijnen. Now we’re getting there but again these percentages apply more to workplace learning than education. It’s a great shift away from traditional, flawed mindsets about how people learning but needs further work to be useful across the entire learning landscape. Blended learning has certainly taken root but it has no defined shape, theory, methodology or best practice. You can call anything a blended solution.

8. Sophisticated
All of the above are either metaphors, simplistic dualisms, or subsets of blended learning. Don't mistake the phrase for an anlaytic theory. Blended learning is so often used as a platitude. It is an old mindset that smothers the idea before it has had the chance to breath. What happened to analysis? Blended learning abandoned careful thought and analysis, the consideration of the very many methods of learning delivery, sensitivity to context and culture and a matching to resources and budget. It also needs to include scalability, updatability and several other variables. What it led to were primitive, dualistic 'classroom and e-learning' mixes. It never got beyond vague 'velcro' models, where bits and bobs were stuck together (now that's a metaphor). You need to work towards an 'optimal' blend. 

9. Analytic
Truly analytic Blended Learning is not a back of an envelope exercise. It needs a careful analytic process, where the learners, type of learning, organisational culture and available resources need to be matched with the methods of delivery. It has INPUTS, decision making and OUTPUTS. Until we see 'Blended learning' as a sophisticated analytic process for determining optimal blends, we'll be stuck in this vague, qualitative world, where the phrase is just an excuse for old practices. Your blend may have no lecture or no classroom components. It may have no online components. But most will be an optimal blend where good teaching and learning theory is applied, alongside analysis of what needs to be taught, who you are teaching and the resources for delivery.
10. ’Veil of ignorance’
In practice, to do blended learning, one has to apply what called the ’veil of ignorance’, an idea that goes back to Kant, Locke, Rousseau and more recently John Rawls. You have to go through a thought experiment and imagine your course, workshop, whatever, as having NO pre-set components. Now do some detailed analysis on what type of outcome you want from this in terms of your ‘learning’. Only then, having rid yourself of personal preconceptions and institutional forms of delivery, can you really start to rebuild your course/learning experience. So you start with an analysis of the learning and learners, then take into consideration your resources envelope, with a full cost analysis. Also include long-term sustainability issues such as updatability and maintenance. To construct a blended learning experience you have to deconstruct your natural bias to do what you or your institution have always done and reconstruct the learning experience from scratch.

7 great things Duolingo teaches us about good online learning

Luis von Ahn is the brains, driver and innovator behind Duolingo. From Guatemala, he’s a mathematician and computer scientist on a mission to keep language learning free. The story is fascinating. It was valued at $1.5 billion at the end of 2019 and their revenues have risen through the pandemic from $400,000 per day to $600,000 per day, with only 20% of revenues in the US. They have x50 more users than their nearest competitor and x5 the revenues. So what's behind the success?

1. Habit

Doulingo is all about making learning habitual. This is the magic dust. I’ve written about h-learning before and it has a long theoretical history going back to Locke and James. The daily tasks and streaks are achievable and you get visual rewards as you progress. The behavioural science behind the formation of habit is also good. This is driven by good design but mostly by clever AI.

2. Adaptive

The primary problem in language learning is motivation. This is where design and AI come in. The bite-size learning chunks and highly visual sense of progress and completion of levels is exactly what drives users forward. This is the good side of gaming. I’ve been involved in adaptive learning for years and really do believe that it offers huge promise in efficacy in learning. 

3. AI drives pedagogy

Duolingo employ high-end AI experts and pay top dollar for this expertise. The personalisation and adaptivity is sophisticated, as it knows what you’ve learnt and, importantly, if you’ve been absent, what you’ve forgotten. This is important. If you don't learn for a few days, it know that you've forgotten and pulls you back a little. Algorithmic personalisation may have more to do with rectifying forgetting than learning.

4. AI drives engagement

But the real application of AI is even more interesting in 'notifications'. They are extremely sophisticated as, algorithmically, they decide what to say and when to say it. This is the clever use of data to automate the learning process, to keep people going. They notify you regularly, but not too much. But the most effective notification is the ‘final warning’. If they feel you have dropped off, a timely message, making you feel slightly guilty, works wonders. They are constantly looking at data to increase habitual learning.

5. User experience

This matters. Simple, clean, plenty of white space, consistent palette, no teacher face or teacher avatar, simple progress bar at top of screen. Then there’s scoring, levels, daily goals, completions, green for success, red for failure. Duolingo also works superbly well on mobile and has keyboard input as an option. 

6. Learning experience

No clumsy drag and drop, open input for full phrases and sentences, allows people to type what they hear, remediation when you fail, sentence as audio when you get it right, not scared of repetition, single day streaks, spaced practice. They work hard at this. I’ve seen it improve year after year.

7. Learning wants to be free

Throughout this whole journey, from late 2012, the primary aim was to keep the service fundamentally free. This was and still is their mission. They are all zealots for free education and hire top-end people at good salaries, who believe in this mission. Keep it free, well largely, as only 3% of users pay the subscription – learning wants to be free.

Innovation

Duolingo went through some serious innovations and pivots. Luis invented CAPTCHA which was successful in digitising books and newspapers and was keen on similar free solutions to problems that, as a by-product, solved other problems. With Duolingo he tried selling translations but that market was commoditised. He then tried ads at the end of each module, so as not to interrupt the learning process. But his final pivot was subscriptions to avoid ads. This solved the problem. 

Critics

His critics, who say that Duolingo doesn’t teach you languages, miss the point he thinks. Most of these apps are about picking up the basics. Learning a second language is a mountainous task and Duolingo aims at the foothills. Their goal is to get that process kick-started and aim for intermediate level B2, and they’re getting there. B2 by the way is the level of English required to work at Google. He also claims, rightly, that the enormous sums spent in schools, trying to teach languages is a disaster zone, with a tiny fraction ever getting any functional proficiency. Remember, Duolingo is free.

Competitors

There are other apps. 

Memrise is perhaps better at dialogue with more video clips but clumsier interface and design. It also uses AI and has a Fremium model to add features such as a grammarbot, pro chats, difficult words, speed review, listening skills, learning stats and more.

Babbel is a German alternative but a subscription service. The voice recognition software (uses AI) can be a bit annoying but it also now adopting AI as the driver. It a more traditional structured lesson approach.

Bussuu is London based and another AI-driven app that operates a Fremium model. It is flashcard based but a more social app, allowing you to speak into the app.

There’s debate about what is best but my point is that all use AI to drive pedagogy, go for the bite-size thing, focus on habit and motivation. I still prefer Duolingo.

Does Higher education need a Reformation?

Last year I visited Wittenberg and that famous door where Luther pinned his 95 theses. It was to change the world, irreversibly. I have written about the important and lasting roles of religious leaders such as Confucius, Buddha, Jesus and Mohammed, as well as religious educators such as St Augustine, Luther, Calvin and Ignatius. Much of what we see in the calendar, structure, hierarchy and teaching in our Universities is deeply rooted in their religious origins. In may ways academe was never revolutionised by the reformation. It was already, by then, a network of institutions that carried on without interruption. My argument is that it is due its Reformation.

Whatever you may think of Peter Thiel, he’s smart. I don’t just mean business smart but intellectually. PayPal entrepreneur, first investor in Facebook, predictor of the financial crisis and so on… impressive CV. Sure he’s an extreme libertarian, with some extreme views, but we need people who pop our conventional bubbles. So, when I heard him utter the following in an interview, it hung around in my head, until I was compelled to expand on it… Here’s the phrase, ‘Higher Education is like the Catholic Church on the eve of the Reformation’. That’s a damn interesting observation. I've written about Illich, who drew parallels between schools and the church in Deschooling Society but Thiel captures both a diagnosis and treatment in this one phrase. He’s talking Reformation.

Costs

What Thiel went on to explain, was that like the Catholic Church, HE had turned into a global, institutionalised phenomenon that demanded increasingly large sums of money from people, for an experience that is much the same year after year. The cost of indulgences as well as the transfer of productive wealth into the non-productive church, was a major catalyst for the Reformation. People were literally becoming indebted to the level of indenture to the church. This was impoverishing the populace while enriching the institutions. $1.6 trillion of student debt in the US. and similar problems arising in Europe? Even the rich, were handing over huge sums, not to charity but to the Church. This is reminiscent of hedge-fund manager Paulson, who recently wrote a cheque for over $400 million to Harvard. This is buying personal prestige (used to be salvation), not in any way moral progress.

Promises

The insidious side of the Catholic Church was the threat, that if you didn’t pay up, you were damned. This same powerful idea has been nurtured by University-educated politicians and HE lobbyists. If you don’t get a Degree, you’re damned as a failure. They perpetuate the myth, that if you don’t go to University, you’ll go to some sort of economic hell, never being admitted to the heaven that is gainful employment. Bryan Caplan has written, in The Case Against Education, a solid case showing that this promise is largely (approx. 80% signalling). If he is right, then huge amounts of money, that could be usefully spent elsewhere is being wasted.

Monastic campuses

Like the enormous building projects by the Catholic Church, Universities are spending untold sums of money on monumental buildings. The occupancy rate of their existing property is already ridiculously low, as it was and is with churches, yet the capital budgets keep on rising. It would be more accurate to say, that like the Catholic Church, campuses have become huge, self-sufficient, monastic communities, almost towns within cities. Board and lodging has become a significant revenue stream for many institutions. In some cities they almost overwhelm everything else. With University Rankings they also have their Cathedrals; Ivy League in the US, Oxbridge in the UK.

Teaching as preaching

The dominant pedagogy is still the lecture, basically a sermon to a compliant audience. There’s a lectern, a lecture, designed for the one-way transmission of knowledge, surely as far from contemporary needs as one can imagine. Stuck with a Medieval pedagogy, founded, through necessity in an age when there were no books, the dominance of the lecture lives on as a shameful, religious, pedagogic fossil. Even worse is not recording lectures. Imagine a journalist not publishing their pieces in print or a novelist not putting their work into print? Denying students access to that lecture for revision, note taking, reflection, rewinding (especially if students are being taught in their second language) and so on, is pedagogically bankrupt.

Crisis of relevance

We seem to have reached a position where HE has drifted in terms of relevance, whether it is the degrees offered, the way they are taught or the exaggerated promises. It seems to have lost its way a little, just like the Church in the 16th century. Rather than serve our needs it often seems to be serving its own needs. With falling enrolments, suspicion about the worthiness of a degree when everyone has one and the high cost, is leading to arguments that question its relevance.

Scriptoria

Higher Education's increasing distance from practical skills, unless they involve high salaries (medicine, vets, engineering, law, architecture…) has turned them into seminaries, with the academic priesthood writing ever more obscure manuscripts for smaller and smaller audiences. The scriptoria and libraries are being flooded by manuscripts, most of which are read only by the authors and reviewers. It has become increasingly scholastic, moving in decreasing circles of relevance. The ballooning world of third rate Journals, which are rarely read, and full of low-level research has happened as the incentives have been around publication (no matter where) rather than teaching and learning.

Undue political influence

We have politicians who almost universally went to University, leaders who largely went to just two Universities and many Ministers who did one particular course at Oxford, PPE, a medieval hangover (replacement for Classics). Maybe the idea of a trained Priesthood for politics isn’t too far-fetched. Beyond this David Goodhart in his book The Road to Somewhere identifies an emerged 'graduate class' that now dominates politics and the professions imposting their views on others. Brexit indicated that many had had enough of this views. 

Academic dominance

Like the scholastic age (the Dark Ages) this has also led to the decimation, in some economies, of vocational education, which they are desperately trying to revive. As HE sucks the life out of vocational learning, we find ourselves in Europe with HE heavy economies struggling, while the German, Austrian and Swiss economies thrive. Hold on – isn’t that where the Reformation hit originated and spread from? Luther, Calvin, Knox… There are serious questions being asked about so much time and money being spent on abstract, academic pursuits at the expense of other needs in society, such as those who do not go to college, healthcare, social care and so on.

Calendar

Off for Christmas? Off for Easter? The University calendar is punctuated by holidays, largely determined by religious and agricultural concerns. The Michaelmas terms starts on the feast day of St Michael, the start of the academic year. This adherence to a rigid timetable with only one entrance date per year makes the system primitive and inflexible. It meant that workload for faculty and students couldn't be spread more reasonable across the sort of timetable that the rest of society had adopted.

Anti-technology

The Catholic Church was none too pleased when the printing revolution produced Bibles in local languages and thinkers who questioned their authority. They found themselves losing control of knowledge; its censorship, means of creation, production and distribution. That’s because the Reformation was, in part, amplified and accelerated by a technology revolution – printing. Similarly, the resistance to the use of technology in teaching and learning has led to little more than recording lectures and resources on a Virtual Learning Environment (VLE). They were ill-prepared for Covid, rushing to replicated lectures on Zoom and struggling with the more sophisticated forms of online learning that have been around for decades, including online assessment.

Conclusion

The Church, which taught in Latin, kept their power by excluding people from reading in their own languages, suddenly found that people were not only reading scripture in their own languages but also writing and challenging the orthodoxy. The Enlightenment came fast on its heels. Now we have a technological revolution that is no less Copernican, the internet, which democratises, decentralises and disintermediates the learning game. I expect this revolution to have a similar effect on HE, driving access to knowledge and learning through a new means of creation, production and distribution. Rather than accepting increasing costs, we should demand lower costs, better access, and a future where education is not seen as built on elitism and scarcity but on scale and abundance. One beneficial effect and almost immediate effect of the reformation was a push for universal education and access. That stuck. This, in our modern age, is what we need in tertiary education. What I’m arguing for is not the extinction of HE but a Reformation. The Reformation did not destroy Christianity and its ethos. It was strengthened by shedding its obsession with money, indulgences, outdated processes, hierarchy, priesthoods and elitism. In fact, the Reformation led to the rapid expansion of our Universities and a change in their character, awy from religious centres towards more secular, intellectual environments. We need something similar today - a rethink about their purpose, processes, pedagogy and payment.

Why learning analytics? Dashboard trap, decision making, how to start, false idols...

Why learning analytics?

The problem with Learning Analytics, is that it can be as much of a trap than saviour. While it tops the poll of future trends in online learning it suffers from ‘dashboard dogma’. Many presentations around learning analytic are full of dashboards with no end of pie charts and donuts, but this is the confectionary of data analytics. If your end point is a ‘dashboard(s)’ you’re merely looking through the window of the bakery.

Trends

Learning Analytics leapt in at Number 1 on Donald Taylor’s International Survey. What’s interesting is the next four positions, as they are all related:

 1 Learning Analytics

 2 Personalised/adaptive learning

 3 Collaborative/social learning

 4 LXP (Learning Experience Platforms)

 5 Artificial Intelligence

I’ve been working solely on this cluster of things for the last six years and want to tease out a simple point – they have to be seen as a whole as they are all intimately related:

 1 fuels 2/3/4/5

 4 is the delivery platform for 1/2/3/5

 5 really matters

Dashboard trap?

Beyond numbers of people taking courses, literally ‘bums on seats’, which is to measure the wrong end of the learner, learning has never been particularly analytic. Few collect detailed data to describe learner behaviour with even basic analysis. Fewer still delve deeply into that data for insights to inform, predict or prescribe future decision making and action. It is not clear that dashboards improve the situation much. It is still a descriptive ‘bums on seats’ approach to data. Visualisation, in itself, means little. One visualises data for a purpose - in order to make a decision. It often masquerades as doing something useful, when all it is actually doing is acting as a cul-de sac.

The dashboard on your car is there primarily so that you can regularly monitor your speed. A secondary and less regular use is to monitor fuel. Even rarer are signals to indicate when temperature rises, oil or tyre pressure needs attention. In fact, most of the data use in a car works invisibly, on your engine, brakes and other systems. In other words, it automates the use of data. As cars have become more sophisticated they take tasks away from you and use data to automate processes. This will reach its zenith with self-driving cars. In learning, no one dies, so we can move towards automation much quicker.

The learning world attracts ‘people’ people, with an interest in the development of others, rather than many from a scientific or analytic background, with an interest in systems and data. This, in a sense, pushes learning professionals away from learning analytics. We must overcome this reliance on qualitative perceptions and judgements, including the old and laboured Kirkpatrick schema, which is statistically naive. 

It is time to move towards a more serious, data-led approach. But relax, this does not mean becoming an expert in data or statistics, as the technology does all of the computation and heavy lifting on the maths and stats. Learning professionals will not be analysts but consumers of data and data-driven automation. The analysis will largely be done for them.

Decision making

In the end this is all about decision making. What decisions are you going to make on the back of insights from your data? Storing data off for future use may not be the best use of data. The least efficient use of data is storing it in pots with dials on the front. Perhaps the best use of data is dynamically, to create courses, provide feedback, automatically deliver adaptive learning. 

The world is becoming more data-driven, organisations more data-driven and even at the level of the individual, personalised service is an expectation. Almost everything you do online is data-driven (search, all social media, Amazon, Netflix etc). Yet learning remains stubbornly resistant. But it is time the learning world responded by being sensitive to this need for data as fuel, and algorithms as the rocket, that will allow us to boldly go to places we have never been before.

Data is everywhere. You are a mass of data points, your face is data for face recognition, your body a mass of data points for healthcare, your behaviours area data points for online organisations, you network online with other people and information which are all data points, your car is a data point for GPS. You are and live in a sea of data. This is also true of learning. What you know, when you learnt things, how well you know things, your performance. Like it or not, you are all masses of data points. This doesn’t diminish your humanity, it informs decision making and can make life easier and more productive.

If you have a LMS (Learning Management System) you will, most likely, have been gathering data under the SCORM specification. Unfortunately, this has an old and severely limited capability, as it focuses on who did what, when and did they complete courses. If you have been using Kirkpatrick, you will most likely have been gathering the wrong data with little analysis. It is time for a rethink.

Moving beyond this specification, xAPI has been defined by the same people who gave us SCORM. This is a new specification more suited to the current landscape of multiple sources for learning and a more dynamic view of how people learn, along with a need for many more types of data than in the past. Similarly with then shift from the LMS to LXP. That is why LXPs and learning ecosystems have appeared. The world has moved on, organisations have moved on, the technology has moved on and so learning professionals should move on.

This means leveraging data to be more focused, efficient and aligned with your organisation’s strategy. It should lead to better decision making, more action, more automation and provable impact on the business – not just dashboards.

How to start?

Don’t think just dashboards. They trap you in a world of reading what IS the case, rather than deciding what SHOULD be the case. We need to derive an OUGHT from an IS and push them beyond dashboards to decisions, actions and the automation of process.

What we need is strategic view of data use. Here’s the good news, a schema has existed for a long time in data science, classifying data use into five areas:

5 Levels of data use in learning: 

 Level 1:  Describe

 Level 2:  Analyse

 Level 3:  Predict

 Level 4:  Prescribe

 Level 5:  Innovate

This allows you to think ambitiously about data, moving beyond mere description (dashboards) towards using to help improve and shape teaching and learning. 

Level 1: Describe

What does learning data tell us about what is happening?

Data that describes what is the case, describing learners, their behaviour and the technology is descriptive. That’s what dashboards do. This is the simple world of tracking and visualisation. Don’t get stuck with dashboards only – they are merely descriptive. 

Level2: Analyse

What does learning data tell us about why it’s happening?

Analysis gives you deeper insights into data, evaluation, business performance, ROI and may, even at a simple level, provide useful insights in terms of informing decisions and action. Don’t worry, the software should do the analysis for you – you don’t have to become a data scientist!

Level 3: Predict

What does learning data tell us that is likely to happen?

Data that predicts what your organisation or group or individual learner performance are likely to be can predict performance, predict dropout and recommend action. Recommendation engines drive most of what you do online (Google, Social Media, Amazon, Netflix). This allows you to deliver personalised learning.

Level 4: Prescribe

What does learning data tell us should happen?

This is where data makes things happen. Nudges and other push techniques can be executed, spaced practice applied, personalised and adaptive learning applied. The software literally uses data to enact something for real. This is how data is actually used in the real world, to automate processes.

Level 5: Innovate

How can learning help us innovate?

Beyond our basic four levels, lies the use of data for more innovative uses in learning such as sentiment analysis, content creation, curation and chatbots. There is a wide array of data-driven techniques that can be used to bring learning into the 21^st century.

False idols

One can decide to let the data simply expose weaknesses in the training. This requires a very different mindset, where the whole point is to expose weaknesses in design and delivery. Is it too long? Do people actually remember what they need to know? Does it transfer? Again, much training will be found wanting. To be honest, I am somewhat doubtful about this. Most training is delivered without much in the way of critical analysis, so it is doubtful that this is going to happen any time soon.

One could also look for learning insights into ‘how’ people learn. I’m even less convinced on this one. Recording what people just ‘do’ is not that revealing if they are clickthrough courses, without much cognitive effort. Just showing them video, animation, text and graphics, no matter how dazzling is almost irrelevant if they have learnt little. This is a classic GIGO problem (Garbage In, Garbage Out). 

Some imagine that insights are buried in there and that they will magically reveal themselves  - think again. If you want insights into how people actually learn, set some time aside and look at the existing research in cognitive science. You’d be far better looking at what the research actually says and redesigning your online learning around that science. Remember that these scientific findings have already gone through a process of controlled studies, with a methodology that statistically attempts to get clean data on specific variables. This is what science does – it’s more than a match for your own harvested data set. 

Business relevance
Learning departments need to align with the business and business outcomes. Looking for correlations between, say increases in sales and completed training, gives us a powerful rational for future strategies in learning. It need not be just sales. Whatever outcomes the organisation has in its strategy needs to be supported by learning and development. This may lift us out of the constraints of Kirkpatrick, cutting to the quick, which is business or organisational impact. We could at last free learning from the shackles of course delivery and deliver what the business really wants.

Another model is to harvest data from training in a diagnostic fashion. To give a real example, they put the employees of a global bank through simulation training on loan risk analysis and found that the problems were not what they had imagined - handing out risky loans. In fact, in certain countries, they were rejecting ‘safe’ loans - being too risk averse. This deep insight into business process and skills weaknesses is invaluable. But you need to run sophisticated training, not clickthrough online learning. It has to expose weaknesses in actual performance.

Business 
You may decide to just get good data and make it available to whoever wants to use it, a sort of open data approach to learning. But be careful. Almost all learning data is messy. It contains a ton of stuff that is just ‘messing about’ – window shopping, In addition to the paucity of data from most learning experiences, much of it is odd data structures, odd formats, encrypted, in different databases, old, even useless. Even if you do manage to get a useful clean data set, You have to go through the process of separating ‘Personal’ from ‘observed’ (what you observe people actually doing), ‘derived’ making deductions from that data, ‘analysed’ (applying analysis to the data). You may have to keep it ‘anonymised’ and the privacy issues may be difficult to manage. Remember, you’ll need real expertise to pull this off and that is in very short supply. A LRS (Learning Record Store), such as Learning Locker, is a good start.

Conclusion

There’s a ton of learning technologists saying their new strategy is data collection in 'learning record stores' and 'learning analytics'. On the whole, this is admirable but the danger is in spending this time and effort without asking ‘Why?’ Everyone’s talking about analytics but few are talking about the actual analysis to show how this will actually help increase the efficacy of the organisation. Some are switched on and know exactly what they want to explore and implement, others are like those that never throw anything out and just fill up their home with stuff – but not sure why. 

Learning analytics is too often seen as 

 Level 1:  Describe - Dashboards

 Level 2:  Analyse - Insights

 Level 3:  Predict - Foresight

 Level 4:  Prescribe - Action

 Level 5:  Innovate – Innovative actions

Of course, all of the above is fine in theory. In practice, organisations have different capabilities. As usual with new paradigms, there is a maturity curve, although that involves a wider set of criteria, including:

 People/culture

 Systems/processes

 Technology/resources

Having spent the last few years doing all of the above, I think we are about to enter a new era, where smarter software (AI/data-driven) will deliver smarter solutions. I now see real clients use data, not just to produce dashboards, but to drive engagement, learner support, content creation, curation, assessment, sentiment analysis, chatbots and so on. My book ‘AI for learning’ will be appearing soon. Happy to help with any of this stuff… DM me on Twitter or contact me on the form here…

So what makes a good online conference?

The conference industry went into deep freeze. It literally ground to an absolute halt. But like many who experience a life threatening event, it has led to some reflection and change in behaviour. Having presented at hundreds of face to face conferences and many online conferences, I’ve been surprised at the lack of discussion on the topic. Then again, to misquote a famous quote "It is difficult to get a man to understand something when his junkets depends upon his not understanding it."

Yet I’m hearing academics and business leaders reconsider their annual spend. They are shifting that spend to other forms of researching and marketing. Flying large numbers of people all over the world now looks increasingly odd, if not immoral, not only in terms of the virus but also in terms of climate change and efficacy. The sight of a swarm of private jets at Davos disgusted many but that is nothing compared to the day in, day out, climate denying activity of the conference business. Let’s not kid ourselves that these are practical venues, the perennial attraction of Vegas, Orlando and Hawaii remain dubious.

The common denominator to all this is that cramming huge numbers of people into rooms in conference centres has several major problems. First they have to get there, increasingly from all corners of the globe, exacerbating climate change. Secondly, the risk of accelerating contagion in a pandemic. Third, it is not clear that the current model is that useful. There are many other reasons for questioning these old habits, and habits they are. Two examples of bad habits, that always surprise me; first, seeing 'posters' at academic conferences, it always seems so school-like, so adolescent. second, the literal reading of a paper from a lectern. Do we really have to travel thousands of miles to see this stuff? 

Perhaps, far too little use is made of online conferences.

So what makes a good online conference? 

We know a lot about what works here... online has, in fact a several advantages - cost, time, more audience participation, links, able to leave presentation easily, post-conference learning and follow up... and so on... but they have to be run differently Having been involved with a few, here’s my thoughts…

1. Needs a compere

A physical conference has the building to hold it together. There is a sense of place and you choose from a schedule, which rooms to go to… Online I value a MC or compere with the presence, communication skills, organisational skills, often with a touch of charm and humour, to motivate people and provide guidance and help. They need to be comfortable in front of a camera and be concise and clear communicators. Throughout the conference, they can feed back themes that have arisen, marshal views from attendees and stimulate discussion and online participation. They also need to be able to cope with things that go wrong…

2. Accept that shit happens

In physical conferences, speakers screw up all the time, can’t find/operate their PowerPoints, overrun, go back or too far forward on their slides. Online you can have complete centralised control. You can also troubleshoot internally and externally. For example, speakers can be muted, unmuted at a distance, slides ready. Even attendees can get help, usual problems being audio. A good behind the scenes producer, with technical skills really does help make things flow.

3. Speaker performance

You can rehearse a speaker on timing, eliminate overlaps, allow links to external content

and signal to a speaker on timings much easier online than you can on a stage. A quick run through of slides, check that the speaker knows what’s happening with the tech and how to set up at home (near router, reasonable light etc) can make things more professional.

4. Participation

Rather than the wooden Q&A at the end of sessions, that often get ditched as the speakers overrun, you can engage before, during and after presentations, with varying levels of participation: formal Q&A, chat, moderated questions and so on. This can be a much higher level of participation than a real conference. Moderated question, I think, work best, even stopping in the middle to take a few.

5. Social events

Conferences are sold on the social networking side but witness the people who sit next to their colleagues in sessions and talk to the people they know and work with during the coffee breaks. During lunch, coffee breaks or with special breakout groups, it is possible to set up discussion groups or let social groups coalesce. These groups can carry on afterwards, as people share social media details. They can be topic based and chaired. Alternatively, you can encourage social media activity to get your messages and content out to a huge global audience. Let these groups form. Wenger talks a lot about these communities of practice – they can be encouraged. In my experience anyone who wants social interaction with the speakers and other attendees will be able to do so to a far higher degree than in a live conference.

6. Lightness

Given that communication is at a distance, I like it when the compere introduces some lightness to the proceedings. You can set up little competitions – spot the X, even ask for pics of attendees rooms (that works well) with prizes. It gives some social cohesion to the affair. I rather like the idea of making it more like a live TV show… how about a house band!

7. Anonymous exits

In physical conferences, people sit in a room but that can be a trap. When a speaker’s content is clearly not relevant or they’re poor presenters or reading from a paper, you can experience  a profound sense of boredom. In online conferences, with parallel streams, you can skip out anonymously. This makes online a much more convenient and time saving affair.

8. Repeat access

Talks and participation are easily recorded for future access. Indeed, the recording becomes trivial and in a format that is not the speaker like a matchstick person at distance on a stage but an intimate close-up with cuts to their slides. Miss a session and it will be available as a recorded event immediately afterwards.

9. Post-conference

I’ve given talks at hundreds of conferences around the world and am often shocked to see that most attendees don’t take notes. They WILL forget, not only what they think they will remember but even what sessions they attended. That’s how the brain works – it’s a forgetting machine. Learning Pool recently ran an online conference where they used their LXP software, integrated with Zoom to hold the conference within a learning environment. This allows follow up and learning from the event to a much higher degree than is possible with physical attendance. I like this idea of turning confer5enmces into richer learning experiences with more follow up.

10. Lower costs on both sides

On costs, both sides save a pile of money. For attendees, no travel, accommodation, subsistence, less opportunity loss. For organisers, no venue, food and less labour costs. It’s a win-win. Conference fees can be minimal or waived, as sponsorship money can pay for the much reduced costs. An interesting model has been tried during this pandemic, an online conference where 50% of the revenue is shared among the speakers.

.

Conclusion

Sure, some things will be lost, the drunken conversations and late nights in the Hotel bar, the chance to visit some foreign capital. But behaviours will change after this pandemic. People will not rush back to restaurants, cinemas, travel and cruises. On conferences, organisations and individuals will think twice before going back to things that were clearly bad for the planet. The online economy will grow – online learning, online shopping, online payments, online streamed entertainment and online conferences.

Thiel – Critique of Higher Education… it offers the same thing year after year, at a higher and higher price...

Peter Thiel was the co-founder of PayPal, first outside investor in Facebook and has since invested in many companies including LinkedIn and Yammer. He describes himself as a conservative-libertarian and espouses original views on business, social structures and education, that many find, if unpalatable, certainly interesting.

Zero to One

In his book on entrepreneurship, Thiel is critical of those who imagine that entrepreneurship can be taught. This, he thinks, is flawed, as “The paradox of entrepreneurship is that such a formula necessarily cannot exist: because every innovation is new and unique.” He doesn’t think that successful, network businesses can be built by MBA types, who are drilled in seeing what is the case, rather than the all-important absences or gaps. He is also critical of educational systems that drive competition, an obsession with grades, which in turn lead to conformity. The best minds in the world now focus on driving people towards careers in online advertising or the unproductive, and risk averse world ,of law and finance. This he thinks limits, rather than encourages personal ambition and progress.

Critique of Higher Education 

He has likened Higher Education to the Catholic Church on the eve of the Reformation, “you have this priestly class of professors that doesn’t do very much work, people are buying indulgences in the form of amassing enormous debt for the sort of the secular salvation that a diploma represents." He asks young people to think again about the burden of student debt, and sees it as a form of ‘indentured servitude’. Like the Catholic Church, Higher Education turned into a global, institutionalised phenomenon that demanded increasingly large sums of money from people, for an experience that was much the same as it had been for decades. The cost of indulgences, as well as the transfer of productive wealth into the non-productive church, was a major catalyst for the Reformation. People were literally becoming indebted to the level of indenture to the church. This was impoverishing the populace while enriching the institutions. Thiel thinks this has happened in Higher Education.

Salvation

The insidious side of the Catholic Church was the threat, that if you did not pay up, you were damned. This is mirrored by the modern threat that if you do not get a Degree, you’re damned as a failure, sent to some sort of economic hell, never being admitted to the heaven that is gainful employment and wealth. Criticising Higher Education is like “saying there’s no Santa Claus” claims Thiel. This is a feature of all bubbles, believes Thiel, where ‘groupthink’ takes over and false assumptions become absolute beliefs, and even debate of the negative consequences is seen as “party-pooping”.

Conformity

Higher education, he thinks, is a bubble fed by a vague abstraction - the word ‘education’. Is it an investment decision for a good job? Is it mere consumption, a four-year party? Or, as he thinks, an ‘insurance policy’ that is not worth as much as you think it is worth. He charges the system with conformity, a position also taken by Noam Chomsky. Diagnostically, Higher Education suffers, he thinks, from a massive failure of the imagination, a failure to consider alternative futures. The net result is that everyone conforms and marches in lock-step to college to do similar degrees which results in homogenisation and lot less freedom of action, as people believe that everything has been exhausted, and the likes of law and finance are the only possible ways forward. He adds that the lack of focus on teaching has turned the system into an “incredible racket”. 

Higher Education as bubble

Technology does more with less, education does the opposite, it offers the same thing year after year, at a higher and higher price. No one could really claim that the huge hikes in pricing reflect corresponding hikes in the value of University tuition. So what’s happening? Universities are complicit in this. They raise prices because they can, without attention to lowering costs through online learning, fourth semesters etc. In fact the quality of tuition may have fallen, with more students and less qualified lecturers, matched by salary inflation at the top, higher numbers of administrators and wasteful capital expenditure in largely empty buildings. Like the housing market, where people rushed to take out loans (mortgages) based on the belief that the value of their asset will always rise (or at least stay the same), many suffered a shock when the value dropped. Huge hikes in prices for the buyer, now seem unrelated to the real price of the degree. This is exactly what happened in everything from tulips to internet stocks and housing. 

There is, for Thiel, no compelling evidence that the future worth of degrees will be guaranteed. That is the mistake made in all bubbles. In a bubble, real demand is brutal, and in a buyers’ market may lead to degrees being simple indicators of ‘class’ rather than intrinsic value. Universities may be creating their own bubble, dislocating cost from real value. Institutional brand ranking may lead employers to dismiss degrees from institutions perceived as second-rate. In short, your degree may become a liability while your debt remains all too real. In short, HE has all the hallmarks of a bubble. Resistant to influence from the outside it is heading towards a crisis, especially for middle-class students who are amassing enormous amounts of debt. As financial pressure mounts, the Reformation needs to come from the outside.

Thiel fellowship

To action his beliefs, about the inefficiency and often irrelevance of college, Thiel’s Fellowship programme funded $100k to each of 20 people under 20, to create their own companies. The programme challenges the idea that college is the only path for young people.

Criticism

Thiel has backtracked on some of his more extreme positions, such as his attacks on multiculturism and diversity, expressed in the book The Diversity Myth and his Fellowship programme has not been the success he predicted. It has been criticised for replacing education with ‘get rich quick’ programmes. His extreme views on the role of women and their political liberation have been roundly attacked as antediluvian.

Influence

Thiel is a contrarian, and although many of his ideas seem outlandish, his critique of Higher Education articulates a growing dissatisfaction with the status quo. Many see his position as exaggerated but it is cogent and based on his not inconsiderable experience in investments and predicting the future. Whether he is right will be proven by future events.

Bibliography

Thiel, P.A. and Masters, B., 2014. Zero to one: Notes on startups, or how to build the future. Broadway Business.

Sacks, D.O. and Thiel, P.A., 1995. The Diversity Myth." Multiculturalism" and the Politics of Intolerance at Stanford. The Independent Institute, 134 Ninety-Eighth Avenue, Oakland, CA 94603.