Is China really the educational powerhouse that the PISA rankings suggest? (tl;dr: not even close)

Administered by the OECD, PISA is basically a set of tests, adapted to each country, that attempt to measure educational performance across a range of skills in order to rank educational systems around the world. The rankings really matter to many countries, and help to determine educational policies across the planet, being especially impactful when countries don’t do well. Often, a low PISA score triggers educational reform (not always ending well), but sometimes countries just stop playing the game. India, for instance, dropped out a decade ago after coming second from the bottom, complaining of lack of adaptation to the Indian context (which is totally fair – India is incredibly diverse, so one measure absolutely does not fit all) though it will be back again next year. There are many reasons to dislike PISA, but the one I want to highlight here is Goodhart’s Law that, when a measure becomes a target, it ceases to be a good measure.

This article – a report on an interview with Andreas Schleicher, OECD Director of Education and Skills (a very smart fellow) – provides some useful food for thought. Though it focuses on China as a case in point, the interview is not so much about China’s ‘success’ as it is about PISA and its limitations in general. Among Schleicher’s more interesting insights is the fact that China’s test results came solely from its four most highly developed and economically successful provinces. These are very unrepresentative of the whole. In fact, China replaced Guangdong in its submission this time round because it was blamed for poorer performance last time, suggesting that the Chinese government’s involvement with PISA is far more concerned with appearing effective on the International stage – on presenting a facade – than on actually improving learning. PISA is a test for countries, and some are quite happy to cheat on the test.

In fact, the biggest contributing factor to test results is, of course and as always, economic. Schleicher notes that, worldwide, the top 10% socioeconomically advantaged students have for at least 10 years consistently outperformed the 10% most disadvantaged students in reading by 141 score points, which equates to approximately three year’s worth of schooling. It is not news that by far the most productive way to improve the effectiveness of educational systems would be to diminish wealth inequalities. It is, though, worth noting that schools play a relatively small role in Chinese education, especially among more prosperous families, with vast amounts of (paid, private) tuition occurring outside schools. Similar extracurricular tuition patterns occur in several of the other highest ranking PISA countries, such as South Korea, Singapore, Japan, Hong Kong, and Taiwan. It is significant that, in these countries, test scores are extremely important in almost every way – economically, culturally, socially, and more – so there is a lot of teaching focused on test results at the expense of almost everything else.

It is also notable – and almost certainly a direct consequence of tests’ importance – that over 80% of Chinese students admit to cheating, which might be more than a minor contributor to the good results. In fairness, cheating rates for the US and Canada are also not too far short of that, correctly implying a serious endemic malaise with our educational systems worldwide (Goodhart’s Law, again), so this is just a relatively slight difference of degree, not of kind. Given the large amount of time spent learning outside school, the high levels of cheating, and the cherry-picking of top performing provinces, the implications are that, far from having a world-leading education system, teaching in China is actually really awful, on average. Among the things that can be gleaned from PISA results are that China performs very badly on productivity (points per hour of learning), and ranks 8th from bottom on life satisfaction for students. It is essentially a failure, by any reasonable measure. The PISA ranking is not quite a fiction but it is close. At least in the case of the high overall placing of China, it certainly fails to correctly measure the effectiveness of the educational system, if results are taken at face value.

There appear to be two distinct patterns among those countries that consistently achieve high PISA results, that appear to divide along broadly cultural lines. The first group includes the likes of China, South Korea, Japan, and Taiwan (all quite notable examples of what Hofsteder describes as collectivist cultures), with high levels of out-of-school tuition, a strong educational emphasis on test scores, and great personal penalties for failure. These countries seem to achieve their high ranking by a very strong focus on passing the tests, with high penalties for failure and great significance for success. As a consequence, their educational systems cannot be seen as standalone causes but, rather, as creators of problems that have to be overcome by other means (most notably in the form of extra-curricular assistance that funds a booming personal tuition economy).  Standard bearers for the other main pattern are Finland and Estonia, as well as Switzerland, and Canada (though the latter two devolve educational responsibility to canton/province, so they are less consistently successful in the rankings). In Hofstede’s terms, these are more individualist societies. In this group, test scores (slightly) tend to be seen as a measure of only one of several consequences of teaching, rather than being the primary motivation for doing it. I am certainly culturally biased, but I cannot help but think this is a better way of going about the process: education is for society, much more than for the individual, and certainly not for economic gain, so it must be understood across many dimensions of value. Whether they agree with me or not, I am almost certain that most educators everywhere would like to think that education is about much more than achieving good test scores. It is only a matter of degree, though. Education in all countries I am aware of relies on extrinsic motivation, and there are large pockets of excellence in the first group and large pockets of awfulness in the second. Averages are a stupid way to evaluate a whole country’s educational system, and they conceal great diversity. The boundaries are also blurred. Estonia, for instance, that is singled out in the article as a success story due to its rapid rise through the rankings, actually also makes extensive use of extra tuition in the form of ‘long day groups’ that take place in schools after curricular instruction. Estonia is no worse than most other countries in this regard, and in some ways superior because such long day groups take the place of at least some of the homework that is widely required in many countries, despite a singular lack of evidence that (on average) it has more than a tiny effect on learning. At least Estonia’s approach involves a modicum of good education theory and evidence to support it.

Overall, I think the main thing that is revealed by the PISA process is that average test scores are, for the most part, an extremely poor means of comparing education systems. Given that it is useful for a government to know how their policies are working, there does need to be some way for them to observe how schools are doing, but it would seem more sensible to rely on trained inspectors reviewing schools, their teaching, the work of children, etc, than on test scores. At the very least they should be considering signs of happiness, motivation, community, and social achievement at least as much as academic achievement. However, Goodhart’s Law would cause its usual harm if such things became the dominant measures of success, and more than the lightest of inspections would normally cause more harm than good. I experienced something not too far removed from this (in the form of OFSTED inspections) in the UK as a parent and school governor back in the 1990s. The results were not pretty. For about a year leading up to them teachers’ workloads were massively strained by the need to report on everything, students suffered, resentments piled up, everyone suffered. Though OFSTED reports did sometimes lead to improvements in particularly bad schools, the effects on the vast majority of schools (and especially on teachers) were disastrous, often radically disrupting work, increasing stress levels beyond reasonable bounds, and leading to more than a few resignations and early retirements from the best, most dedicated teachers who could barely cope with the workloads at the best of times. They were forced to become bureaucrats, which is a role to which teachers tend to be very poorly suited. It was (and, I believe, may still be) beyond stupid, despite best intentions.

What is really needed is something more collegial, that is focused on improvement rather than judgment, that celebrates and builds on success rather than amplifying failure, where everyone involved in the process benefits and no one suffers. The whole point (as far as I understand it) is to improve what we do, not to blame those who fail. Appreciative Inquiry is a good start. Simple things like peer observation (with no penalties, no judgments, just formative commentary) can be more than adequate for the most part at a local level, and are beneficial to both observer and observed. Maybe – if someone thinks it necessary – inspectors (volunteers, perhaps, from the teaching profession) could look at samples of student work from further afield with a similarly positive, formative attitude. It might not provide numbers to compare but, if there were enough of a culture of sharing across the whole sector, and if inspectors came from across the geographical and cultural spectrum, it ought to be good enough to improve practice, and to spread good ideas around, so the intent would be achieved. Governments could receive reports on what actually matters – that things are getting better – rather than on what does not (that things are bad, according to some unreliable measurement that compares nothing of any real value to educators, students, or society). Teaching is a deeply soft technology that cannot be reductively simplified to a relationship of entailment. It can, though, as a lived, creative, social process, be improved. This should be the goal of all teachers, and of all those who can influence the process, including governments. PISA only achieves such results in a tiny minority of extreme cases. For the most part, it actively militates against them because it substitutes education – in all its rich complexity – for test scores. These are not even a passable proxy. They are a gross distortion, an abhomination that can trivially be turned to evil, self-serving purposes without in any way improving learning. Schleicher fully understands this. I wish that the people who his organization serves did too.

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Excellent news: Twitter Makes A Bet On Protocols Over Platforms.

Well this is good news! Of course, the road to Hell is paved with good intentions and there is much that could go wrong in between plan and execution, but it seems that Twitter is recommitting itself to openness, standards, and the use of protocols for a federated social Web (see also and for the announcements by Twitter’s founders). It is a bit worrying that Twitter wants to help invent a new protocol when there are plenty of established ones that already exist (ActivityPub, OpenSocial, FOAF, XMPP, OStatus, OpenID, OAuth, PubSubHubbub, Zot, Diaspora, etc, etc). Also, there is already a pretty serviceable Twitter competitor in the form of Mastodon, that does most of what they seem to want to do. However, the fact that they are thinking about protocols rather than platforms at all is very heartening. The world needs much much more of this.

Twitter, as it evolved in its first couple of years, was brilliant. What made it great was that it could act as a highly efficient social bookmarking system *plus* commentary *plus* folksonomy, *plus* instant messaging, *plus* social networking, all through one incredibly simple, flexible, open field.  It was, in part, a descendant of social bookmarking systems that people like me developed in the 90s, but there were no predetermined fields for URLs (you could have more than one, or none at all); there were no predetermined categories; the tags (#hashtags) were trivially easy to include, without separate fields (this is what makes it highly supportive of social sets, in which the topic matters more than the person); and it had the lowest threshold social networking (especially through @mentions), again without the need for separate fields. It was a single small text box that did everything, and that could be used to share more or less anything with more or less anyone but, thanks to its size,  was primarily used to connect to other things. Part of what made this so cool is that #hashtags and @mentions were not designed into Twitter at the start, but emerged memetically from practice: the system evolved (at first) through a collective design process. Twitter’s implementation of such things in software ingeniously used automation to make the overall system even softer and more flexible than it was before. It was generous in what it shared, too, so a flourishing ecosystem grew around it, at least for the first few years. You could use pretty much any Twitter data to which you had access in any way you liked. It was a very simple, very powerful component, a tool rather than an environment or platform. In retrospect I wish we had used Twitter as a model when developing the Landing, rather than the kitchen sink approach that we settled for.

Twitter is widely viewed as a competitor to Facebook – increasingly even by the company itself – though it was (and still is, to an extent) a very different animal. Facebook has tried to emulate all of Twitter’s features as a subset of its own horrible evil mess, but completely misses the point. The strength of Twitter is that it (still) does one simple thing very well: it is primarily a hub that makes the rest of the Web more connected, rather than (like Facebook) sucking everything into it. However, that one simple thing is as soft and open to countless, unprestatable uses as an elastic band, a screwdriver, or good old fashioned email.  Jack Dorsey’s announcement of the new move itself is a classic example of this, creating a long-form announcement from short tweets. Beyond simply connecting stuff, people have used it to write novels, coordinate social protests, conduct personal conversations, influence elections, and thousands of other things. It is a very soft, very human-driven tool.

For a few years it was very open, and it seemed to be getting more so, but it lost its way after that and became much more the self-contained platform we see today, pulling a lot of features into its core, closing off many ways of connecting with and using it, and increasingly hardening things that should have stayed soft, notably in its algorithmic placing and sorting of tweets. Though its old character limit was frustrating at times, it was actually a very good idea to set such severe boundaries because it ensured that Twitter remained as a connecting hub, rather than a self-contained site. The new higher character limit is still somewhat constraining, but it makes longer-form conversations increasingly possible – especially when combined with the easy upload of video, files, images, etc – thus drawing people to stay more at the hub, rather than to visit the things that it connects. It has become more and more a social media platform, increasingly isolated, increasingly its own bubble, increasingly driven by the popularity contests and narcissism amplifiers that seldom end well. Twitter’s announcement, I hope, marks a reversal of this pattern. I hope (though don’t expect) that they get the Mastodon gang on board. I will watch with great interest, whatever happens.

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E-Learn 2019 presentation – X-literacies: beyond digital literacy

Here are  my slides from E-Learn 2019, in New Orleans. The presentation was about the nature of technologies and their roles in communities (groups, networks, sets, whatever), their highly situated nature, and their deep intertwingling with culture. In general it is an argument that literacies (as opposed to skills, knowledge, etc) might most productively and usefully be seen as the hard techniques needed to operate the technologies that are required for any given culture. As well as clarifying the term and using it in the same manner as the original term “literacy”, this implies there may be an indefinitely large range of literacies because we are all members of an indefinitely large number of overlapping cultures. All sorts of possibilities and issues emerge from this perspective.

Abstract: Dozens, if not hundreds, of literacies have been identified by academic researchers, from digital- to musical- to health- to network- literacy, as well as combinatorial terms like new-, multi-, 21st Century-, and media-literacy. Proponents seek ways to support the acquisition of such literacies but, if they are to be successful, we must first agree what we mean by ‘literacy’. Unfortunately, the term is used in many inconsistent and incompatible ways, from simple lists of skills to broad characteristics or tendencies that are either ubiquitous or meaninglessly vague. I argue that ‘literacy’ is most usefully thought of as the set of learned techniques needed to participate in the technologies of a given culture. Through use and application of a culture’s techniques, increasing literacy also leads to increasing knowledge of the associated facts and adoption of the values that come with that culture. Literacy is thus contextually situated, mutates over time as a culture and its technologies evolve, and participates in that co-evolution. As well as subsuming and eliminating much of the confusion caused by the proliferation of x-literacies, this opens the door to more accurately recognizing the literacies that we wish to use, promote and teach for any given individual or group.


Social Media Has Not Destroyed a Generation   – Scientific American

Well this is not a surprise. It turns out that social media and cellphone use have little to no effect on the mental well-being of teenagers. And, having just hung out with more than 10,000 young people in Vancouver, I’d say that they seem to be doing pretty well,

(if the video does not display, visit

Unfortunately, these wonderful young people are not to be confused with the very many utter creeps, idiots, paid lackeys of oil companies, bizarrely de-evolved evolution-deniers (not to mention climate-change deniers), and haters of all things decent who felt compelled to contribute to the live chat displayed alongside the YouTube video linked to above, as well as to far too many of the subsequent comments. This is what raw, unfiltered sets (the largely anonymous, non-networked social form that dominates on YouTube and many other social media) look like. The insane, the evil, and the stupid (often a mix of all three) have voices at least as loud as those who have something reasonable or human to say, and they have a platform where at least a few other people with ugly, broken souls will help them to feel validated, so they feel even more compelled to say the stupid, ugly, evil things they say. How dare they? Perhaps some of them are also children but, from many of the comments, I’d say that most have reached voting age. It’s not the kids that we need to worry about, apart from that they may be being brought up by such vile excuses for humanity, and that they have to learn to make sense of the stuff swamp of social media systems that enable such voices to be loudly heard.

When I hear Greta Thunberg talk it consistently brings tears to my eyes and sends shivers down my spine. She is astonishingly wonderful and deeply, deeply inspiring. She is brave, she is brilliant, she is right. She is not proposing anything apart from that politicians take action now on an unequivocal, plain to see, planet-wide threat, that is caused by problems that we know how to solve, and that demands political action. Yes, that will disrupt the lives of people that have profited from our collective madness – that is to say, most of us (but it is a hell of a lot less disruption than the alternative, at least for those not due to die any time soon). Yes, it is really difficult to make it happen. Yes, it means we will all have to change some of our ways, but that is no bad thing: our lives, and those of our children, and those of most of the living things on our planet, will be better as a result. And no, it is not her job to propose solutions, and she very deliberately does not try to do so, though she lives her life according to her convictions and does what she sees as necessary as an individual fighting the climate crisis. When she talks she simply states – with immense, infectious, intense passion – what is wrong, and demands that those who can fix it should do so. I am deeply humbled by this amazing teenager. We should all be.

Do buy the cheap, slim volume of her speeches, No One Is Too Small to Make a Difference. It is an inspiring book, and the proceeds will all go to charity.

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Technology, technique, and teaching

These are the slides from my recent talk with students studying the philosophy of education at Pace University.

This is a mashup of various talks I have given in recent years, with a little new stuff drawn from my in-progress book. It starts with a discussion of the nature of technology, and the distinction between hard and soft technologies that sees relative hardness as the amount of pre-orchestration in a technology (be it a machine or a legal system or whatever). I observe that pedagogical methods (‘pedagogies’ for short) are soft technologies to those who are applying them, if not to those on the receiving end. It is implied (though I forgot to explicitly mention) that hard technologies are always more structurally significant than soft ones: they frame what is possible.

All technologies are assemblies, and (in education), the pedagogies applied by learners are always the most important parts of those assemblies. However, in traditional in-person classrooms, learners are (by default) highly controlled due to the nature of physics – the need to get a bunch of people together in one place at one time, scarcity of resources,  the limits of human voice and hearing, etc – and the consequent power relationships and organizational constraints that occur.  The classroom thus becomes the environment that frames the entire experience, which is very different from what are inaccurately described as online learning environments (which are just parts of a learner’s environment).

Because of physical constraints, the traditional classroom context is inherently very bad for intrinsic motivation. It leads to learners who don’t necessarily want to be there, having to do things they don’t necessarily want to do, often being either bored or confused. By far the most common solution to that problem is to apply externally regulated extrinsic motivation, such as grades, punishments for non-attendance, rules of classroom behaviour, and so on. This just makes matters much worse, and makes the reward (or the avoidance of punishment) the purpose of learning. Intelligent responses to this situation include cheating, short-term memorization strategies, satisficing, and agreeing with the teacher. It’s really bad for learning. Such issues are not at all surprising: all technologies create as well as solve problems, so we need to create counter technologies to deal with them. Thus, what we normally recognize as good pedagogy is, for the most part, a set of solutions to the problems created by the constraints of in-person teaching, to bring back the love of learning that is destroyed by the basic set-up. A lot of good teaching is therefore to do with supporting at least better, more internally regulated forms of extrinsic motivation.

Because pedagogies are soft technologies, skill is needed to use them well. Harder pedagogies, such as Direct Instruction, that are more prescriptive of method tend (on average) to work better than softer pedagogies such as problem-based learning, because most teachers tend towards being pretty average: that’s implicit in the term, after all. Lack of skill can be compensated for through the application of a standard set of methods that only need to be done correctly in order to work. Because such methods can also work for good teachers as well as the merely average or bad, their average effectiveness is, of course, high. Softer pedagogical methods such as active learning, problem-based learning, inquiry-based learning, and so on rely heavily on passionate, dedicated, skilled, time-rich teachers and so, on average, tend to be less successful. However, when done well, they outstrip more prescriptive methods by a large margin, and lead to richer, more expansive outcomes that go far beyond those specified in a syllabus or test. Softer technologies, by definition, allow for greater creativity, flexibility, adaptability, and so on than harder technologies but are therefore difficult to implement. There is no such thing as a purely hard or purely soft technology, though, and all exist on a spectrum,. Because all pedagogies are relatively soft technologies, even those that are quite prescriptive, almost any pedagogical method can work if it is done well: clunky, ugly, weak pedagogies used by a fantastic teacher can lead to great, persistent, enthusiastic learning. As Hattie observes, almost everything works – at least, that’s true of most things that are reported on in educational research studies :-). But (and this is the central message of my book, the consequences of which are profound) it ain’t what you do, it’s the way that you do it, that’s what gets results.

Problems can occur, though, when we use the same methods that work in person in a different context for which they were not designed. Online learning is by far the most dominant mode of learning (for those with an Internet connection – some big social, political, economic, and equity issues here) on the planet. Google, YouTube, Wikipedia, Reddit, StackExchange, Quora, etc, etc, etc, not to mention email, social networking sites, and so on, are central to how most of us in the online world learn anything nowadays. The weird thing about online education (in the institutional sense) is that online learning is far less obviously dominant, and tends to be viewed in a far less favourable light when offered as an option. Given the choice, and without other constraints, most students would rather learn in-person than online. At least in part, this is due to the fact that those of us working in formal online education continue to apply pedagogies and organizational methods that solved problems in in-person classrooms, especially with regard to teacher control: the rewards and punishments of grades, fixed length courses, strictly controlled pathways, and so on are solutions to problems that do not exist or that exist in very different forms for online learners, whose learning environment is never entirely controlled by a teacher.

The final section of the presentation is concerned with what – in very broad terms – native distance pedagogies might look like. Distance pedagogies need to acknowledge the inherently greater freedoms of distance learners and the inherently distributed nature of distance learning. Truly learner-centric teaching does not seek to control, but to support, and to acknowledge the massively distributed nature of the activity, in which everyone (including emergent collective and networked forms arising from their interactions) is part of the gestalt teacher, and each learner is – from their perspective – the most important part of all of that. To emphasize that none of this is exactly new (apart from the massive scale of connection, which does matter a lot), I include a slide of Leonardo’s to-do list that describes much the same kinds of activity as those that are needed of modern learners and teachers.

For those seeking more detail, I list a few of what Terry Anderson and I described as ‘Connectivist-generation’ pedagogical models. These are far more applicable to native online learning than earlier pedagogical generations that were invented for an in-person context. In my book I am now describing this new, digitally native generation as ‘complexivist’ pedagogies, which I think is a more accurate and less confusing name. It also acknowledges that many theories and models in the family (such as John Seely Brown’s distributed cognitive apprenticeship) predate Connectivism itself. The term comes from Davis’s and Sumara’s 2006 book, ‘Complexity and Education‘, which is a great read that deserves more attention than it received when it was published.

Slides: Technology, technique and teaching

Causal understanding is not necessary for the improvement of culturally evolving technology (paywalled)

I’ve been struggling a bit with writing a chapter on how we should research technologies, especially soft technologies, in the light of their innate complexity, the difficulties of identifying relevant boundaries, their situated nature, the impossibility of identifying all possible uses for any soft technology (and the immense importance of the role of the user in their enactment), and the fact that they are far from fixed, amongst other things. This (regretably paywalled) paper helps support the theoretical model I am developing. Using an experimental method, it shows that technologies can be developed, and can gain in sophistication and complexity over multiple generations, without any of its designers having an accurate or complete understanding of how they work. It is particularly interesting when viewed through a lens of distributed/situated/extended cognition because of the role the technology itself plays in its evolution, and it accords very well with Kauffman’s notion of the adjacent possible and Arthur’s theory of technological evolution.

From the abstract…

“Here we show that a physical artefact becomes progressively optimized across generations of social learners in the absence of explicit causal understanding. Moreover, we find that the transmission of causal models across generations has no noticeable effect on the pace of cultural evolution. The reason is that participants do not spontaneously create multidimensional causal theories but, instead, mainly produce simplistic models related to a salient dimension. Finally, we show that the transmission of these inaccurate theories constrains learners’ exploration and has downstream effects on their understanding. These results indicate that complex technologies need not result from enhanced causal reasoning but, instead, can emerge from the accumulation of improvements made across generations.”

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My learning style

I am a visual, aural, read/write, kinaesthetic, introvert, extravert, sensing, intuitive, analytic, thinking, feeling, judging, perceiving, independent, dependent, collaborative, competitive, participant, avoidant, wholist, analytic, verbalizing, imaging, visualizing, deductive, synthetic, expansive, serialist, holist, field-dependent, field-independent, intrinsically motivated, extrinsically motivated, impulsive, reflexive, convergent, divergent, levelling, sharpening, concrete-sequential, concrete-random, abstract-sequential, abstract-random, assimilating, exploring, adaptive, innovative, reproductive, experiencing, thinking, doing, reflective, directed, self-directed, undirected, application-directed, meaning-directed, deep, surface, strategic, apathetic, elaborative, impulsive, concrete, independent, self-assertive, cerebral,  affective, type 1, type 2, type 3, global, scanning, focusing, physical, logical, social, solitary, musical-rhythmic, interpersonal, intrapersonal, spatial, body, active, common sense, dynamic, imaginative, quadrant 1, quadrant 2, quadrant 3, quadrant 4, theorizing, organizing, humanitarian, legislative, judicial, executive, tactile, pragmatic, versatile learner.

My birth sign is Aquarius, and I was born in the Year of the Rat.


It appears that 97% of American teachers actually believe in learning styles, by which I mean the belief that there are persistent traits describing how people learn that can be used to determine the best way to teach them. This is despite at least most, if not all, of the many scores of such theories existing somewhere between astrology and fairies in terms of evidence for their relevance or applicability in real life learning. Though there may be ever-shifting conditions under which we may at times prefer one or other of whatever learning styles the theory we like offers – this may be a source of the persisting appeal of the idea – there is no reliable evidence that this is in any way relevant to whether or not we will learn better or worse (whatever we think that means) when offered a learning experience that is tailored to that preference. It’s not by any means for want of trying – countless studies exist, and that’s not counting probably many more that never saw the light of day because they had only null results to report and so were not deemed worthy of publication – so the obvious conclusion to be drawn is that these theories are most likely false.

It wouldn’t be so worrying were it not that there is evidence that such beliefs are harmful to learners and, even if there were not, then the time, effort, and money put into trying to use them would be far better spent on things that actually might work.

In the extremely unlikely event that it were one day proven that an individual has a persistent style of learning that, when we teach to that style, consistently leads to improved learning (however we measure that), then it would be my duty as a teacher to try to teach them to learn in other ways, because here’s the thing: the real world in which we are and must be lifelong learners doesn’t come neatly packaged in ways that fit your learning style. We can all learn to learn in all the ways that I list above, and then some, and we can all become better and smarter by applying the right strategy at the right time. We therefore need to cultivate as many diverse learning strategies as we can, and learn when to use them. That’s just common sense which, as it happens and surprisingly enough, is itself a learning style, according to the 4MAT model.

Signals, boundaries, and change: how to evolve an information system, and how not to evolve it

primitive cell development

For most organizations there tend to be three main reasons to implement an information system:

  1.     to do things the organization couldn’t do before
  2.     to improve things the organization already does (e.g. to make them more efficient/cheaper/better quality/faster/more reliable/etc)
  3.     to meet essential demands (e.g. legislation, keep existing apps working, etc)

There are other reasons (political, aesthetic, reputational, moral, corruption/bribery/kickbacks, familiarity, etc) but I reckon those are the main ones that matter. They are all very good reasons.

Costs and debts

With each IT solution there will always be costs, both initial and ongoing. Because we are talking about technology, and all technologies evolve to greater complexity over time, the ongoing costs will inevitably escalate. It’s not optional. This is what is commonly described as the ‘technological debt’ but that is a horrible misnomer. It is not a debt, but the price we pay for the solutions we need. If we don’t do it, our IT systems decay and die, starved of their connections with the evolving business and global systems around them. It’s no more of a debt than the need to eat or receive medical care is a debt for living.

Thinking locally, not globally

When money needs to be saved in an organization, senior executives tend to look at the inevitably burgeoning cost of IT and see it as ripe for pruning. IT managers thus tend to be placed under extreme pressure to ‘save’ costs. IT managers might often be relieved about that because they are almost certainly struggling to maintain the customized apps already, unless they have carefully planned for those increased costs over years (few do). Sensibly (from their own local perspective, given what they have been charged with doing), they therefore tend to strip out customizations, then shift to baseline applications, and/or cloud-based services that offer financial savings or, at least, predictable costs, giving the illusion of control. Often, they wind up firing, repurposing, or not renewing contracts for development staff, support staff, and others with deep knowledge of the old tools and systems. This keeps the budget in check so they achieve the goals set for them.

Unfortunately, assuming that the organization continues to need to do what it has been doing up to that point, the unavoidable consequence is that things that computers used to do are now done by people in the workforce instead. When made to perform hard mechanical tasks that computers can and should do, people are invariably far more fallible, slow, inconsistent, and inefficient. Far more. They tend to be reluctant, too. To make things worse, these mundane repetitive tasks take time, and crowd out other, more important things that people need to do, such as the things they were hired for. People tend to get tired, angry, and frustrated when made to do mechanical things over which they have little agency, which reduces productivity much further than simply the time lost in doing them. To make matters even worse, there is inevitably going to be a significant learning curve, during which staff try to figure out how to do the work of machines. This tends to lead to inflated training budgets (usually involving training sessions that, as decades of research show, are rarely very effective and that have to be repeated), time to read documentation, and more time taken out of the working day. Creativity, ingenuity, innovation, problem-solving, and interaction with others all suffer. The organization as a whole consequently winds up losing many times more (usually by orders of magnitude) than they saved on IT costs, though the IT budget now looks healthy again so it is often deemed to be a success. This is like taking the