Tyranny of time – why learning often wastes time...

Our learning world, at all levels, in schools, HE and the workplace, including offline and online learning, suffers from one obsession that leads to massive waste and low productivity – an obsession with time. timetabling habits into the online world.

The metrics almost universally cost ‘teaching and learning’ like sausages…. by the pound/kilo - face time, contact time, fixed length courses, and hour of learner time in online learning. All are metrics that work against efficient delivery. The tyranny time is the disease that disables the learning world and by altering how we see 'learning time, a lot of time, money and wasted effort by teachers and learners could be saved.

Higher Education

The one hour lecture, that pedagogic staple in HE, is an hour long simply because the Sumerians had a base-60 number system - hence the ‘hour’. It bears no relation to the psychology of attention or efficient pedagogy. It is quite simply the slavish adherence to a fossilised method of delivery that is easy for faculty to timetable. Even then, attendance is often appalling (40% don't turn up even at Harvard), and often not recorded, rendering even rudimentary attempts at measurement meaningless. University terms still adhere to a mixture of old professional timetables (primarily the Law profession), religious festivals and an 18^th century agricultural calendar, with long holidays, that are periods of forgetting. Fixed three and four year length degree courses with only one start date per year, take no account of actual needs. Oh, and lets build and market ‘Masters’ Degrees to that we can add yet another year. Nowhere is the tyranny of time more crude and obvious than in Higher Education.

Schools

Similarly in schools, that mimic Universities, as they must be kept in sych. This is another form of tyranny as schools are now their feeders, despite the fact that the majority of young people do not take that route. The ‘period’ in schools mimics the ‘lecture’ where millions of young people pack up, stand up and shuffle through crowded corridors to another identical room where they have to unpack, sit down and settle again. This waste of time is immense. Imagine running a company where all employees have to rise on the hour and move somewhere else? Can't teacher's walk? And again the tyranny of an ancient calendar, where unhealthy doses of forgetting punctuate the year, determine the rhythm of learning, which should be steady... not full on, nothing, full on, nothing…..

Workplace

An obsession with padded out ‘courses’ from compliance to whatever fad arises (Emotional Intelligence, NLP. Mindfulness and so on) means days of wasted time doing courses that have little or no effect on performance. Get people to travel from all over, then batch people through, in dull rooms with round tables, bowls of mints, coloured pens and some half-baked attempt at collaboration, where you throw out a vague question, discuss at the table, feedback on flipchart paper, which gets pinned on the wall, then the promise that the results will be sent to you – they never are. These courses are always delivered by the half-day, full day, or worse, days on end and when it comes to impact the adherence to a ridiculous mode of evaluation (Kirkpatrick) means very little is meaningfully measured.

Online learning

Just as bad is online learning, bought and sold by the ‘learner hour’, mimicking the University and school model. Rather then focus on value and the idea that this really can save time, it encourages vendors to over-deliver so that they can charge more. The net result is overdesigned content, with oodles of meaningless, illustrative graphics, thinly punctuated by multiple-choice questions, and maybe some Pavlovian gamification (so that a premium price can be paid). Even MOOCs were foolishly deigned to match University semesters, with a drip feed of content over up to 10 weeks – and they wonder why people fell to the wayside?

What to do?

So the tyranny of time comes in many guises, the lecture, period, semester, term, course, clickthrough online learning and degree. Some make it worse by recommending lifelong learning, in the form of going back to college – life as one long course. No thanks. Life is far too short for that nonsense. By and large all of these take too long as they suffer from the following flaws:

1. Fixed form of delivery

Most ‘teaching and learning’ is shaped by pre-existing, fixed modes of delivery, the lecture, period, term, module, course and so on. This ‘ass before elbow’ mode of delivery should be shaped by the type of learning, needs of learners and resources, not mode of delivery. The solution is to imagine that the learning experience doesn’t exist, take it back to a blank slate, now re-design. Match modes of delivery to the typology of learning, learning needs and resources. Look to make everything shorter and more efficient for the learner. Some call this Blended Learning - that doesn’t mean a bit of online bolted on to a bit of classroom, let’s call that Velcro Learning, and don’t confuse Blended ‘Learning’ with Blended ‘Teaching’, where you simply slice and dice a bit of your old and new delivery methods and call it a ‘Blend’. Escape the tyranny of time and focus on value.

2. Sheep dip

Most teaching is a one-off event. It is ridiculous not to record lectures, even if you think it’s a poor form of pedagogy (which I do). Denying learners a second and third bite of the cherry is ridiculous – they may be ill, miss points, not understand at first pass, have trouble note taking, have the language of teaching as a second language. Above all the psychology of learning shows that repeated access for reinforcement and retrieval through revision is necessary for efficient learning. There is a strong argument for doing the same in schools. I’ve seen this work magnificently in an Italian school, yet few have ever thought about doing it.

3. Forgetting

Let’s not forget that single, fixed timetabled events ignore a well known principle in learning – that the brain forgets almost everything it’s taught. Ebbinghaus showed us this in 1885 and the learning world has studiously ignored the principle that learners need, not repetition but retrieval and deliberate practice. Learning needs to be repeatedly accessible, say through recorded lectures right through to spaced practice techniques such as top and tailing, note taking, repeated testing, up to algorithmically determined, personalised deliberate practice. Deliberate, effortful, spaced-practice frees learners from the tyranny of single event, sheep-dip learning.

4. Batching

Courses tend to batch learners who have to go through the linear course at the same pace. In any group you will have a distribution curve, where you only hit those in the middle. There will be tails of learners who find the experience too slow or too fast. Personalised delivery, now possible through adaptive, online learning, allows you to deliver learning to an individual, informed by their progress and aggregated data from all who took the course before. This results in increased attainment and lower dropout.

5. Less is more

In designing learning experiences, the ‘Garbage-In Garbage-Out’ rule is not taken seriously enough. I’ve seen far too many long compliance documents and over-engineered courses throw far too much detail at learners. Lecturers pad out lectures to fit their ‘hour’. Course designers fill out a timetable with unnecessary content and activities. The net result is actually lower learning, retention and recall. Cognitive overload results in less, not more, being retained. Research from large data sets has shown that video in learning tends to fall of a cliff at around 6 minutes. The consequence being that video should be that length or shorter.

The psychology of learning screams ‘less is more’ at us. Cut down documents until they bleed then cut them down again, so that the content is learning ready. There are few courses I’ve seen that can’t have up to 25-30% cut out – all the padding. There is no doubt that lecturers pad out to the hour, the same with classroom teachers and organisational trainers. Rather than plan to fill the time, like an empty vessel that needs to be topped up, look at making the learning experience as short as possible. Think about what learners ‘must’ learn, not generally what they ‘could’ learn. Of all the techniques to free learners from the tyranny of time this one is by far the most productive. This is precisely what we've been doing with WildFire - using AI to cut down on content creation time and learner time with crisp, open-input, online learning.

6. Failure to chunk

Chunking is a pretty basic pie of learning theory – that our working memory is limited and that throwing overlong learning experiences at the learner is counter productive. It happens all the time. We teach people to write essays by repeatedly getting them to ‘write essays’ rather than breaking that task down into its constituent parts. Whole word teaching was an almost perfect example of this approach to teaching that resulted in catastrophic failure in reading in UK schools. Learning experiences have to have focus.

7. Digital by default

Rethinking learning around, not existing modes of delivery and fixed timetables, but more flexible methods of delivery that suit the type of learning, learners and resources is badly needed. More often than not this means more 365/24/7 availability by being online. Being digital by default, wherever is practical, turns time-tabled learning experiences into anytime learning. Asynchronous often makes more sense than synchronous, even of its recorded lectures and resources. Switch away from a dependence on courses to an on-demand model.

Conclusion

In practice, as you get older and become a more self-sufficient learner, you realise that freedom from the tyranny of time is the real trick to learning. You literally ‘learn’ how to learn by being measured, having focus, rehearsal, retrieval – by avoiding the waste of time that are courses and degrees. That’s lifelong learning. Life is short, it's made even shorter by wasting so much time learning and not living.

Learning Technology - attempt at defining Tech-OLOGY

It is the ‘learning’ affordances of technologies that create civilisation - writing, printing, computers, internet, AI. All other technologies emerge from that underlying locomotive functions of reproduction and scale.

What distinguishes us as a species is tools and technology. More accurately, what distinguished the many species that we evolved from and co-evolved alongside us is technology. Other species such as birds and primates, do use tools, but the first of our genus Homo habilis (handy man) through to Homo sapiens (knowing man) are simply the most successful of these competing species. We had better tools and technology, aided by language and subsequent technologies, such as writing that gave us commanding advantages.

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

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

Learning technology

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

  Learning technology:

1.     has cultural & economic impact

2.     is a multiplier

3.     extends cognition

4.     replaces teaching with learning

5.      scales

6.      enables new pedagogies

7.      draws from consumer tech

8.      melds hardware & software

9.      can be both good and bad

10.  gets declassified

Learning technology has cultural impact

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

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

Learning technology is a multiplier

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

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

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

Learning technology extends cognition

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

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

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

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

Learning technology replaces teaching with learning

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

Learning technology scales

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

Learning technology is enables new pedagogies

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

Learning technologies draw from consumer technologies

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

Learning technology melds hardware and software

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

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

Learning technology can be both good and bad 

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

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

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

Learning technology gets declassified

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

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

Stage 1 Prehistory

Stage 2 Writing

Stage 3 Printing

Stage 4 Broadcast media

Stage 5 Computing

Stage 6 Internet

Stage 7 AI and data

Bloom (1913-1999) - Mastery learning. Taxonomy of learning… not a hierarchy…

Benjamin Bloom’s is best known for his ‘taxonomy’ of learning, in Taxonomy of educational objectives: The classification of educational goals: Handbook I, cognitive domain (1956)but it has not stood the test of time as well as other aspects of his work around time to competence and personalised learning. Bloom claimed that his ‘taxonomy’ book was one of the most cited and least read books in education. The taxonomy was created to validate assessment items and learning objectives. It was designed to be used as an analytic tool to create balance in courses, balanced objectives and assessments. It was a regulating tool. Instead it was turned into a partial and misleading pyramid.

Bloom’s taxonomy

Bloom is known globally for his hugely influential classification of learning behaviours and provided concrete measures for identifying different levels of learning. In the 1950s there was a movement to identify a taxonomy of learning, as examinations were being used nationally in education. Bloom chaired the committee and they saw the top level of a taxonomy as three overlapping domains:

Cognitive domain (knowledge-based)

In the original version of the taxonomy, the cognitive domain is broken into the following six levels of objectives; Knowledge, Comprehension, Application, Analysis, Synthesis and Application.

Psychomotor domain (action-based)

Skills in the psychomotor domain describe the ability to physically manipulate a tool or instrument like a hand or a hammer. Psychomotor objectives usually focus on change and/or development in behavior and/or skills.

Affective domain (emotion-based)

Skills in the affective domain describe the way people react emotionally and their ability to feel other living things' pain or joy. Affective objectives typically target the awareness and growth in attitudes, emotion, and feelings.

Taxonomy gone wrong

The taxonomy was devised to assist teachers to classify educational goals and plan and evaluate learning experiences. Unfortunately, he only published the first book on the Cognitive domain, co-authored with David Krathwohl, in 1956. It was another eight years until the second book on the Affective Domain was published. This led to an unnatural, over-emphasis on the cognitive side, captured meme-like by a coloured pyramid, that was never in Bloom’s work. His pupil, Anderson (2001) tried to correct these misconceptions, turning the nouns into verbs but the mythical Bloom endures.

Critique

In the 2001 revised edition of Bloom's taxonomy, written by Lori Anderson decades after the original publication (he had never read it), updated the taxonomy based on a more sophisticated understanding of cognitive psychology. The levels are slightly different and he abandoned the pyramid for a rectangle:

 

• Remember

• Understand

• Apply

• Analyze

• Evaluate

• Create (rather than Synthesise)

Note that there is no sense of higher and lower here, as they are often represented in diagrams. There is no hierarchy here. Unfortunately, they are still both misrepresented by coloured pyramids, that are over-hierarchical and devalue and diminish the role of knowledge in learning, placed at the bottom of the pile. Learning is neither a hierarchy of separate entities nor a linear process. It is a gross oversimplification.

It has been argued that Bloom’s taxonomy has done a lot of damage to teaching and learning. Learners from poorer backgrounds may have suffered badly from this devaluation of knowledge, as it is a necessary condition and the foundation for learning. That is not to say that all learning is remembering. Analysis and generated work are also important but this is not a linear process of climbing a pyramid, it is about an integrated approach. In reality, learning is non-linear and messier than many taxonomies and instructional theories suggest. It uses many of these activities in a more elaborate and networked fashion. The problem may very well be, say teaching the grammar and language of a language or coding before ever getting learners to actually practice dialogue or actually synthesize and code with a goal.

Indeed, we have had dozens of taxonomies that sliced and diced learning in all sorts of ways. These include; L. Dee Fink’s Taxonomy of Significant Learning Outcomes that goes beyond cognitive processes and includes other aims of teaching: Foundational Knowledge, Application, Integration, Human Dimension, Caring and Learning How to Learn; Wiggins and McTighe backwards design model describes Six Facets of Understanding: Explain, Interpret, Apply, Have perspective, Empathize and Have self-knowledge; Davis and Arend provide yet another categorization that can help educators determine which teaching methods are best suited for which learning objectives: Acquiring knowledge, Building skills, Developing critical, creative, dialogical thinking, Cultivating problem solving and decision-making abilities, Exploring attitudes, feelings and perspectives, Practicing professional judgment and Self-discovery and personal growth.

But Bloom’s, and other taxonomies, don’t pick up on contemporary findings from cognitive science, such as retrieval and spaced practice or technical skills.

Mastery learning

Bloom’s other research led him to believe, in Human Characteristics and School Learning (1976), that learners could master knowledge and skills given enough time. It is not that learners are good or bad but fast and slow. The artificial constraint of time in timed periods of learning, timetables and fixed point final exams, as a destructive filter on most. The solution was to loosen up on time to democratise learning to suit the many not the few. Learning is a process not a timed event. Learning, free from the tyranny of time. allows learners to proceed at their own pace.

Bloom proposed three things could make mastery learning fulfil its potential:

1. Entry diagnosis and adaption (50%) - diagnose, predict and recommend

2. Address maturation (25%) - personalise and adapt

3. Instructional methods (25%) - match to different types of learning experiences and time

Personalised learning

His true legacy, which is now starting to be realised and implemented through the use of technology, is personalised learning. Google’s Peter Norvig famously said that if you only have to read one paper to support online learning, this is it - The 2 Sigma Problem, where he compared the lecture, formative feedback lecture and one-to-one tuition. Taking the straight lecture as the mean, he found an 84% increase in mastery above the mean for a formative approach to teaching and an astonishing 98% increase in mastery for one-to-one tuition. In other words, the increase in efficacy for one-to-one learning, because of the increase in on-task learning, is immense. This paper deserves to be read by anyone looking at improving the efficacy of learning as it shows hugely significant improvements by simply altering the way teachers interact with learners. Online learning, in the widest sense of the word, promises what Bloom called ‘one-to-one learning’, whether it’s through self-paced structured learning, scenario-based learning, simulations or increasingly adaptive and personalised learning. The advances and availability of AI has made this possible, as explained in AI for learning, Clark (2020).

Influence

Bloom was also the first to really establish a solid, working taxonomy of learning. Unfortunately it was truncated and excluded the psychomotor and affective components, was caricatured as a hierarchical pyramid, its subsequent improvements ignored, leading to an overemphasis on the cognitive and artificially hierarchical and sequential nature of learning. It was also used to reinforce the prejudices among the academically minded, those who see knowledge, the affective and psychomotor and vocational learning as playing a diminished role in funded learning. One could argue that it has also led to an over-emphasis on 21st C skills, which explicitly devalue the role of knowledge in learning.

His longer legacy is more likely to be, not his outdated, partial and misleading taxonomy but how work on personalised learning. Free from the tyranny of time, he thinks mastery learning will produce better results for the majority of learners.

This is now manifesting itself in personalised learning technology that uses aggregated and personal data to deliver the right thing to the right learners at the right time. Resequencing content, based on continuous assessment of their personal progress is the realisation of Bloom’s research and dream of a massively more efficient and optimised learning process.

Bibliography

Bloom, B. (1984). The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring, Educational Researcher, 13:6(4-16).

Bloom, B.S. (Ed.) (1956). Taxonomy of educational objectives: The classification of educational goals: Handbook I, cognitive domain. Longmans, Green.

Guskey, T. R. (2005).Benjamin S. Bloom: Portraits of an educator. Lanham, MD: Rowman & Littlefield Education.