Sunday, October 31, 2021

HyFlex, Hybrid, Fusion or Blended learning - lots of names, few know what it is....

Lots of terms flying around by arrivistes for what has been discussed for decades -  Blended learning. We now have Hyflex, Hybrid, or Fusion Learning. Who cares? The problem is that few know what these mean.... most fall into simple dualisms.

HyFlex seems to be the worst of both worlds, hanging ion to the old while disliking the new. As Dr Stephanie Moore says, "It's like looking at the desirable affordances of two modalities and throwing it all out the window ". Hybrid merely suggests some fix between two modalities, like a hybrid car - sometimes electric, sometimes petrol. Fusion? No, just no. Blended Learning is enough - let's stick to this term.

I agree with the Blended Learning approach and have designed many such blends, even a mathematical tool that determines optimal blends. It has 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. That's why we developed this tool. 

So what happened?

1. Muddled by metaphor
It all got muddled by metaphor. Blended learning started to fail when it got bogged down by banal metaphors. I've heard them all - fusion, hyflex, hybrid... I've heard to described as cocktails and alloys. Within the ‘food metaphor’ we got courses, recipes, buffet learning, tapas learning, smorgasbord, fast food versus gourmet. The problem with metaphor-driven blended learning is who is 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.

2. Blended bandage
Blended learning (whatever you want to call it) was really just the learning world coping with the onslaught of new ways of teaching and learning. The more recent terms Hyflex, Hybrid and Fusion were the learning world coping with the onslaught of Covid. It is 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.

3. Blended learning is not blended TEACHING
Blended Learning also turned out the very opposite of Blended Learning theory, namely Blended TEACHING. Teacher/lecturer/trainers 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.

4. Velcro learning
Dozens of definitions of blended learning then float around, most of them muddle-headed, as they are 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. We see this in the Zoom + model rapidly adopted during Covid.

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. We have designed a tool that does precisely this.

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.

Tuesday, October 26, 2021

Learning Experience Design

My last book was ‘AI for learning’ in which I explained the massive role that AI has already played in learning and how it will shape the learning landscape of the future. In that book I explained how learning experience designers will have to upskill to deal with the new world of AI, data, learning analytics and the complexities of new AI interfaces such as voice, AI mediated and adaptive content. The technology is about to become much smarter and much more complex. Learning designers will have to understand how AI will shape interfaces and content.

This new book, Learning Experience Design, sees learning design as grounded in learning theory and evidence, so that appropriate experiences are selected, then professionally designed. This moves us from the old to the new, seeing experiences as more than just flat pieces of media but a whole world of learning experiences that motivate and result in lasting change to long-term memory. 

The book is about the sheer range of possible learning experiences, as well as what media and learning theory lies behind their use. 

Chapter 1 looks at what Learning eXperience Design is through each of those three words – ‘Learning’, ‘eXperience’ and ‘Design’.

Chapter 2 looks at who LXDs are, where they come from and what they do. It digs into the design process and the practical challenges LXDs have to face.

Chapter 3 covers the learning theory behind LXD and looks at emotion, attention and motivation, what you need to know to design learning experiences. Not all experiences are optimal learning experiences and without a knowledge of the science of learning, it is too easy to design the illusion of learning.

Chapters 4 to 7 deal with interfaces, text, graphics, audio, video and animation. Learning Experience Design needs knowledge of the media and technology through which learning takes place.

Chapter 8 shifts gear into engagement, questions and feedback. Good learning experiences need to push into effortful learning.

Chapters 9 to 12 takes effortful learning to another level through scenarios, simulations, AR, VR, games, gamification and social learning.

Chapters 13 and 14 bring everything together through practice, transfer, workflow learning, curation and data.

It has a ton of learning experiences, based on evidence-based research and practice, as well as lots of DOs and DON"Ts.

Available here on Amazon.

Also some recent podcasts...

The Curious Case of Benjamin Bloom! bit.ly/3FEdYk8 Pragmatists & practice bit.ly/3aAK5mk Behaviourists bit.ly/3iUnINE Cognitivists bit.ly/3oUxOBK

7 ways AI & Data are transforming learning

Tesla passed $1 trillion market cap today so it is now worth more than Pfizer, Aztrazeneca, GSK, ExxonMobil, BP, and IBM combined. The only companies now worth more than Tesla are Apple, Microsoft, Google and Amazon. Their common denominator is that their underlying tech is now AI. Europe is falling behind, as we'd rather regulate than innovate.

Those who claim to ‘know’ where AI is going, and how fast, are being constantly challenged. 

So where is it going on learning? Well the main area of focus is NLP (Natural Language processing). AI is moving fast on several fronts here.

Data

Tesla has what seems to be an outrageous valuation. Yet what is being valued is not traditional car production, it is the driving data it harvests and the promise of a world where the very concept of vehicles and transport will be transformed. This will happen in learning. The data we gather will feed into optimising future learning experiences, as processes not events. This is why AI, or rather AI that uses data, will shape the future landscape of learning. Data will lie at the heart of all learning experiences. I explain this in my new book ‘Learning Experience Design’.

AI is the new UI

I’ve written about this in ‘AI for Learning’ and ‘Learning Experience Design’, the reshaping of UX as almost all interfaces are now mediated by AI - all social media, Netflix, Amazon, Google, YouTube - almost everything you do online. This is now happening in learning thorough LXP systems. In addition, voice interfaces are now in smartphones and on devices in cars and homes. It is getting better, faster and is scalable. AI is changing our whole relationship with technology, making it more human.

AI personalises

We know that personalised learning gives really significant advantages to large numbers of learners. We’d all love to have one-on-one teaching but that was never economically possible. It is now. Adaptive and personalised learning, enabled by AI, is now here at all levels in learning. CogBooks, a company I helped build has just been sold to Cambridge University Online and will power its online learning. LXPs, such as Learning Pool’s Stream, something I’ve been involved in, will deliver personalised learning to employees in the workplace and workflow.

AI teaches

Teaching largely addresses deficits in motivation and effort, learning is largely achieved by oneself. Took me a long time to truly understand this. It can create sense-making experiences for learners. The problem with traditional online learning is that it was essentially the presentation of content. It never really did what a good teacher does and that is create the opportunities for learning then allow and support you to make the effort to learn. AI enables both. We do this in WildFire.

AI learns

We used to have teachers and learners. Now we have teachers, learners and technology that also learns. Tesla learns as it aggregates driving data and uses that data to improve performance. The more we use Google the better it gets. The more we use personalised and adaptive learning the better it becomes for future students. We are no longer stuck on a plateau of human performance but on an upward trajectory of performance, making learning better, faster and cheaper.

Transformers

Transformers, such as GTP-3 are already useful in learning. We’ve been using them in WildFire for summarisation, content creation and question generation. This software is so powerful that just learning how to ask it questions or do things for you needs a new skillset - it is called ‘prompting’. These AI models have been trained with unimaginably large data sets. They have so much data in their training set that they, at times, transcend the ability of humans to create prose. They are now also entering the world of audio, images and video. They will literally be transformative.

Edge AI

The processing and application of AI on the ‘edge’, on devices, has really arrived. Look at the new Pixel6 mobile phone to see how AI is being delivered via chips in devices such as phones. It has a Tensor AI chip on-board; so translates, transcribes and does speech recognition blazingly fast. It can also erase unwanted objects on photos. These are seriously difficult tasks that require localised processing.

Conclusion

We can wallow in existing practices and technology and see modest but not substantial change in the efficacy and cost of learning. Or we can accept that the future is one where data, and what we do with that data, determines upward progress. A future that uses AI and data to create learning experiences as processes not events, improve interfaces, personalise, teach, support learning. All of this possible to wherever, whenever and to whoever. Technology, specifically AI and Data are finally delivering what we used to call Lifelong Learning.


Monday, October 18, 2021

THE GREAT BITCON

THE GREAT BITCON


I got the Blockchain and Bitcoin ‘bug’ around 2015, gave talks on the subject, even got married (should I say remarried) on Blockchain, paid for in Bitcoin. Then, volte face, I became a sceptic real quick and over the last few years, I’ve seen it get worse - huge projects trying to solve problems that already have adequate solutions or problems that don’t actually exist and now this period of speculative mania.

The Great Bitcon is a financial mirage, a shark that needs to keep afloat through dirty energy and liquidity to keep it afloat. That gold coin image is a complete con. As Nassim Taleb says, its worth is “exactly zero”. There is no common good here, in fact it is a dangerous, damaging piece of energy hungry speculation… and unsustainable.

As if to confirm the absurdity of Bitcoin as a currency, there’s been an experiment, on a real country -  El Salvador! Pick a small, poor South American, stagnant economically, with a horrific homicide rate, run by two massive drug gangs (MS13 and Barrio18) and a major land-route for drugs into the US - and give it a highly volatile virtual currency. Its capital San Miguel is the money laundering capital of central America  - hotels, nightclubs, car dealerships, right down to the hardware stores. What could possibly go wrong?

Former PR man, turned Dictator, Bukele, is what has gone wrong. Despite having brought inflation under control by pegging the ‘colon’ (you couldn’t make it up) to the dollar, he decides he wants to be Mr Cool. It’s a stunt. He has sacked the judiciary, put his henchmen in place, limited the power of the opposition and in true South American Dictator style - scrapped the limited term law for Presidents. A few weeks ago he gives everyone $30 in Bitcoin. You don’t solve the problem of poverty by foisting a volatile asset on poor people. Not that poor people get the money anyway.

So, how’s it going? It dropped 20% in the first day and is already trickling upwards into the hands of the rich and  gangs, with whom the President did a deal. Widespread reports of fraud in the wallet system has left people bewildered. Few businesses are accepting the currency and 15,000 took to the streets demanding it be stopped. They even destroyed a Bitcoin ATM.About half of El Salvadorians have no internet access, sure many have phones but the old and poor often lack the skills to use this stuff. It’s a process of exclusion not inclusion. I repeat, the last thing we want to do for poor people is get them involved in a highly volatile asset, when what they need is stability.

The great con works as there’s something in crypto for everyone, from the idle speculator to every species of ideologue. For Libertarians - no authority in control. For the Left - no corporates and banks in control. For the Right - no corporations in control. Why? Because no one is in control. That’s the real problem. It is, quite simply, speculation or to use old Marxist expressions, the purest separation of capital from production the world has ever seen, and its seen a few. A pure expression of greed from those that can least afford to lose - the young, women and ethnic minorities. The FCA rightly issued a warning this year NON-TRIVIAL DOWNSIDE RISKS.

I get that people are concerned, especially during Covid and it is that uncertainty that’s driving the speculation and volatility fuels this speculation. But spare me the duplicity of doing good - it’s just plain bad. You always hear about winnings, never losses. What’s happened is that the whales, VCs, hedge-funds and billionaires have stepped in. It’s the 1% folks. The people who control it are the people with lots of it.

Jackson Palmer, founder of Dogecoin says crypto has “evolved to incorporate many of the same institutions tied to the existing centralized financial system they supposedly set out to replace. All the while shoving cash and profits back up the funnel towards the rich, not the bankless & the poor. Crypto avoids audits, regulation, taxation, all the protections that are they to protect citizens”. It sucks capital in like a black hole, indeed it has to, to sustain its existence, but without contributing to real economic productivity.

That’s not to mention several other bad actors; tax evaders, money launderers, sanction busters, ransomware gangs, kidnappers and scammers. Forget your password - hard luck. Get scammed - hard luck.

Then there's the fatal objection. Right in the middle of one of a serious, global energy crisis, where Lebanon quite simply went dark and where fuel poverty will hit hundreds of millions, cryptocurrencies are doubling their energy requirements, to the equivalent energy use of Poland. Talk about swimming against the tide. It’s not just the cost of mining, the cost per transaction but the waste. The problem is systemic, it is in the model of verification, in the maths. It is quite simply energy intensive. It’s also an emissions disaster as its primary energy source is fossil fuels. When China banned Bitcoin mining and trading, the miners fled to other countries.

Why Khazikstan? Low financial regulation, only 6% renewables and tons of dirty coal. Why Mongolia? Low regulation and tons of dirty coal. Why TEXAS? Cheap electricity. Why is it cheap? An independent grid, deregulated, old infrastructure, low investment, so bad that they had severe outages in February of this year - it is estimated that up to 700 people may have died, 4.5 m homes and businesses had no power.

Why did China do what they did? Climate change targets. It came on the back of huge internal Chinese energy outages, where factories were shut down. China has a target of being carbon neutral by 2060 and see crypto being regulated and banned through climate change blowback alone. Oh, and the chips for mining are almost all made in Taiwan.

No hears you when you scream with the pain of your hacked losses or lost password in cryptoland. No one comes to your rescue in an unregulated suprastate environment.

My fear is that crypto is ‘doomed to succeed’ to take us to dark, ugly places we can’t get back from. I said at the start I had gone from zealot to sceptic. I will keep an open mind but I am convinced that cryptocurrencies are purely speculative, not a viable set of currencies, destabilising, increasing inequalities, energy intensive and therefore on an unsustainable path, both politically and in terms of climate change.


Since when did Christmas become the celebration of successful supply-chains?

Since when did Christmas become the celebration of successful supply-chains?
We believe, like children, that there really is a Santa Claus. Santa has become the just-in-time delivery point at the end of a global network. In truth it is just-in-time manufacturing, with no resilience or just-in-case. The Reindeer are shiploads of containers on polluting ships that radiate out from ports to shops and Amazon centres, via low paid lorry and van drivers. Santa is a shitty piece of logistics software.
We have fallen into buying endless amounts of consumerist crap from China and as that economy stagnates, we blame everyone but ourselves... so when Santa goes ‘Ho Ho Ho’ he’s laughing at our downright stupidity. Turns out we’re the turkeys voting for our own Christmas extinction, going out in a blaze of neon lights next to our personal mountain of landfill.
In my lifetime I’ve seen Christmas explode into a heap of glittery crap. Houses lit up like Las Vegas Casinos. Christmas trees, often plastic, laden with more baubles per branch than leaves. Chocolates that come, not in boxes but enormous buckets. People really want all their Christmases to come all at once, in the form of a skipload of junk for every man, woman and child.
When Jesus was born there was no room at the Inn, no doubt because workers in hospitality were in short supply, the Three Kings brought single natural presents, not cartloads of tawdry rubbish, so let’s get back to dreaming, not of a White, but Green Christmas.

Sunday, October 03, 2021

Roediger and Karpicke - Retrieval practice and effortful learning

Henry L. Roediger (Washington University in St. Louis) and Jeffrey D. Karpicke (Purdue University) have been at the forefront of the research on retrieval practice. For centuries memories were seen as objects to be retrieved but neutral for learning. Few saw that act of retrieval as a learning experience in itself, something that produced learning. They can be said to have put retrieval practice, as a learning strategy, on the map by confirming the efficacy of free recall over rereading, stimulating research in the area.

Testing Effect (Retrieval Practice Effect)

In their Testing-enhanced learning (2006) paper they showed that repeated tests substantially increased retention relative to learners who simply restudied the prose material. Restudying had a better short-term effect but retrieval practice, 2 days and 1 week later showed a significant difference. Roediger et al. (2011) then did a study on text material covering Egypt, Mesopotamia, India and China, in the real context of real classes in a real school, a Middle School in Columbia, Illinois. Retrieval tests, only a few minutes long, produced a full grade-level increase on the material that had been subject to retrieval.

The first solid research on the Testing effect was by Abbot (1909), then Gates (1917), who tested children aged 8-16 on short biographies. Some simply re-read the material several times, others were told to look up and silently recite what they had read. The latter, who actively retrieved knowledge, showed better recall. Spitzer (1939) made over 3000 11-12 year olds read 600 word articles then tested students at periods over 2 months. The greater the gap between testing and the original exposure or test, the greater the forgetting. The tests themselves seemed to halt forgetting. 

Tulving (1967) took this further with lists of 36 words, with repeated testing and retrieval. The retrieval led to as much learning as the original act of studying. This shifted the focus away from testing as just assessment to testing as retrieval, as an act of learning in itself and Karpicke and Roedegir’s work in 2006 and 2009. McDaniel (2011) did a further study on science subjects, with 16 year olds, on genetics, evolution and anatomy. Students who used retrieval quizzes scored 92% (A-) compared to 79% for those who did not. More than this, the effect of retrieval lasted longer, when the students were tested eight months later. 

Karpicke and Blunt (2011) also showed that retrieval practice is superior to concept or mind-mapping. Spaced, retrieval practice is even better (Karpicke & Bauernschmidt, 2011). It has been shown to be effective at all levels in education; elementary, middle-school, Universities and in adult medical education.

The work by Kornell (2009) also shows that even unsuccessful testing is better. Retrieval testing gives you better internal feedback and works even when you get few or no correct answers. Testing, even before you have access to the material, as a learning experience, also helps learning. Once again, Huestler and Metcalfe (2012) asked learners what worked best and they were largely wrong.

Illusions of competence

In their 2006 research, Karpicke and Roediger used rereading as the control, as that is what most learners do, see Karpicke, Butler and Roediger (2009), and in doing so uncovered a fascinating supplementary finding. In a survey of 117 students they asked them to list their study strategies, then also choose from a list of set strategies. The majority chose rereading as a strategy with relatively few using self-testing or free recall. They christened this the ‘illusion of competence’. Just as Bjork had done in asking students about practice techniques, they found that students think they will do better by repeated study and not free recall practice, yet the evidence shows the students were wrong. This lack of metacognitive awareness severely limits the ability of learners to learn.

Make It Stick

Make It Stick (2014) by Brown, Roediger and McDaniel takes a wider view. It is the result of over ten years of focused research on 'Applying Cognitive Psychology to Enhance Educational Practice'. It is practical and gives plenty of advice on both how to teach and how to learn, the point being that knowing how to learn is a necessary condition for good teaching.

Researchers like Bjork, Karpicke, Rodeiger and McDaniel claim that most good learning theory is counterintuitive. Most students are misled by teachers and institutions into the wrong strategies for studying; reading, highlighting, underlining and rereading. This feels productive but the evidence suggests it is a largely ineffective strategy for learning. It turns out that we are very poor judges of our own learning. The optimal strategies for learning are in the 'doing' and some of that doing is counterintuitive. We think we are mastering something but this is an illusion of mastery. It is easy to think you’re learning when the going is easy – re-reading, underlining and repetition but it doesn’t work. To learn effectively, you must make the going harder. They also explain why the research is not about rote learning, the charge that is usually levelled against them.

The real force behind successful learning is effortful learning. By effort they mostly mean retrieval practice. Practically, they recommend regular, low-stakes testing for teachers and learners, not ‘teaching to the test’ as summative assessment but regular formative exercises, where recall is stimulated and encouraged. Test little and often – that is what makes effortful learning stick.This is not testing as assessment, it is testing to learn. Interesting research is also presented for the idea that having a go at retrieval, even when you make mistakes and errors, is better than simply getting the exposition. 

They also recommend spaced practice, especially spaced retrieval practice and interleaving and delayed feedback.

Criticism

It is not that retrieval practice doesn;t work only that it only works for limited types of learning, such as factual recall, and that the effect fades, even disappears for more complex material. Many of the trials are on verbal information, word-pairs and so on. An associated problem is the difficulty in designing retrieval practice and transferring it to the classroom or online environment. It is ebay to design low-level practice.

Influence

Their work has gathered a great deal of attention, especially in schools and stimulated other research on different audiences with different types of material and in different contexts. Movements such as ResearchED have promoted the research and its spread in recent books on teaching practice, and online, has been significant.

Bibliography

Brown, P.C., 2014. Make it stick. Harvard University Press.

Abbott, E. E. (1909). On the analysis of the factors of recall in the learning process. Psychological Monographs, 11, 159–177.

Gates, A. I. (1917). Recitation as a factor in memorizing. Archives of Psychology, No. 40, 1-104. 

Spitzer, H. F. (1939). Studies in retention. Journal of Educational Psychology, 30, 641-656. 

Tulving, E. (1967). The effects of presentation and recall of material in free-recall learning. Journal of Verbal Learning and Verbal Behavior, 6, 175􏰀184.

Huelser, B.J. and Metcalfe, J., 2012. Making related errors facilitates learning, but learners do not know it. Memory & cognition, 40(4), pp.514-527.

McDaniel, M. A., Agarwal, P. K., Huelser, B. J., McDermott, K. B., & Roediger, H. L. (2011). Test-enhanced learning in a middle school science classroom: The effects of quiz frequency and placement. Journal of Educational Psychology, 103, 399-414

Karpicke, J.D., & Bauernschmidt, A. 2011. Spaced retrieval: Absolute spacing enhances learning regardless of relative spacing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(5), 1250-1257. 

Karpicke, J.D. and Blunt, J.R., 2011. Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331(6018), pp.772-775.


Friday, October 01, 2021

Mill - Utilitarianism, associationism and women’s rights

John Stuart Mill saw education as a means to the end of achieving happiness for the individual and happiness as a whole. Hot-housed as a child, and educated by his Scottish father the philosopher John Mill and Jeremy Bentham, his Godfather, he was kept apart from other children, reading Greek and Latin at age 8. As a teenager he suffered from depression, which he in part saw arising from the intensity and isolation of his education. He felt as though his purely rational education had not allowed him to develop feelings such as sympathy and appreciation of the real world. Finding Wordsworth helped him overcome this tendency to immediately rationalise and analyse the world.

He was one of the most significant intellectual figures in England in the mid-nineteenth century, as a philosopher, politician and economist. He also played a significant role in the advancement of women’s rights.

Empiricism and associationism

As an empiricist, he saw sensory experience as the raw data from which all else arises, even logic and mathematics. This meant he saw the mind as a tabla rasa, ready to be filled with sensations that lead to all manifestations of consciousness and thought. It is the scientific approach making inductive inferences from experience that should be used to build a view of education.

His associationist psychology meant the association of small pieces of data, sense data or feelings, to form our view of the world. This came from Locke, Hume and Hartley and forms the basis of his empiricism and belief in the strength of the scientific method.

Utilitarianism

From his Godfather, Jeremy Bentham, he saw Utilitarianism (1863), expressed in the formula ‘the greatest happiness for the greatest number of people’ as an empirical theory based on the observation that this is what all people actually desire - happiness. This is not to say that one should pursue one’s own happiness at the expense of others,as the greater good is a sure source of happiness for the individual. Although he did believe that some forms of happiness were higher than others and , unlike Bentham, saw feelings as important guides in moral, aesthetic and other judgements.

Utility is intimately connected with liberty and in On Liberty (1859) he is keen to press the idea that one cannot infringe upon the rights of others to pursue their happiness, unless their actions cause ‘harm’. State and social control were to be resisted. As they infringe upon the development of the individual. This debate around freedom of expression is still relevant today, along with the ‘harm principle’ and influenced his views on education.

Education

Education was the means to attain true happiness, not in the simple sense of hedonistic pleasures but the higher forms of happiness. He refused to believe that most learners were innately incapable of being fully educated. In his Autobiography, he was also critical of the idea that one should only teach what learners enjoy, as this appeals to a primitive view of the lower pleasures of ‘fun’ and prevents access to the higher pleasures and happiness of subtler, elevated subjects. This hinders rather than helps learning as it prevents the learner from reaching their fullest potential and happiness. Above all education should teach children to become autonomous being and and to think for themselves.

Education should have a strong moral purpose, to overcome the selfish pursuit of pleasures at the expense of others. Moral education must encourage the capability of appreciating that the happiness of others, the greater and common good, leads also to the happiness of the individual within that society and culture. The taking on of public duties and active participation in society and democracy was important.

In On Liberty (1859) he proposes compulsory, universal education for every citizen, including women, all the way up to University entrance. Although he was critical of the idea that such education should be provided by the state, as that could result in compulsory coercion and control, which was counter to his views on freedom and liberty. One notable example of his aversion to education coercing learners, was his view that religion, as a subject of opinions, should not be taught in schools.

Women’s rights

In The Subjection of Women (1869), he calls upon his utilitarian and libertarian principles to defend the emancipation of women from the social pressures to conform to what men think. Women are forced to lead less happy lives because they are not free to pursue their own happiness, almost in a state of slavery. Here, he also called for the abolition factual  slavery.

He makes the case for absolute equality, especially in the freedom giving process of education that would give women, as citizens, freedom and independence. 

Influence

Mill’s influence has been immense in politics, notably his ideas on freedom of expression and liberty. He is still read and quoted at length on these issues to this day and these issues in education, especially in the campus culture clashes, are still with us. His influence on education is not via his purely empiricist views but his appeal for compulsory, universal education was realised, at least in the developed world, along with the inclusion of women, especially in Higher Education. Mill played a key role in the latter.

His focus on happiness also influenced the recent rise of positive psychology, through Seligman and others, although much of that debate seems to ignore the deep and sophisticated interest taken on that topic in the 19th century.

Bibliography

Mill, J.S. and Stillinger, J., 1873. Autobiography.

Mill, J.S., 2018. (1869) The subjection of women. Routledge.

Mill, J.S. and Bentham, J., 1987. (1863) Utilitarianism and other essays. Penguin UK.

Mill, J.S., 1989. (1859)  'On Liberty' and Other Writings. Cambridge University Press.