Beyond learning outcomes

What we teach, what a student learns, what we assess This is a slide deck for a talk I’m giving today, at a faculty workshop, on the subject of learning outcomes.

I think that well-considered learning outcomes can be really helpful when planning and designing learning activities, especially where there is a need to assess learning. They can help keep a learning designer focused, and to remember to ensure that assessment activities actually make a positive contribution to learning. They can also be helpful to teachers while teaching, as a framework to keep them on track (if they wish to remain on track).  However, that’s about it. Learning outcomes are not useful when applied to bureaucratic ends, they are very poor descriptors of what learning actually happens, as a rule, and they are of very little (if any) use to students under most circumstances (there are exceptions – it’s a design issue, not a logical flaw).

The big point of my talk, though, is that we should be measuring what students have actually learned, not whether they have learned what we think we have taught, and that the purpose of everything we do should be to support learning, not to support bureaucracy.

I frame this in terms of the relationships between:

  • what we teach (what we actually teach, not just what we think we are teaching, including stuff like attitudes, beliefs, methods of teaching, etc),
  • what a student learns in the process (an individual student, not students as a whole), and
  • what we assess (formally and summatively, not necessarily as part of the learning process).

There are many things that we teach that any given student will not learn, albeit that (arguably) we wouldn’t be teaching at all if learning were not happening for someone. Most students get a small subset of that. There are also many things that we teach without intentionally teaching, not all of them good or useful.

There are also very many things that students learn that we do not teach, intentionally or otherwise. In fact, it is normal for us to mandate this as part of a learning design: any mildly creative or problem-solving/inquiry-oriented activity will lead to different learning outcomes for every learner. Even in the most horribly regimented teaching contexts, students are the ones that connect everything together, and that’s always going to include a lot more than what their teachers teach.

Similarly, there are lots of things that we assess that we do not teach, even with great constructive alignment. For example, the students’ ability to string a sentence together tends to be not just a prerequisite but something that is actively graded in typical assessments.

My main points are that, though it is good to have a teaching plan (albeit that it should be flexible,  reponsive to student needs, and should accommodate serendipity)learning :

  • students should be participants in planning outcomes and
  • we should assess what students actually learn, not what we think we are teaching.

From a learning perspective, there’s less than no point in summatively judging what learners have not learned. However, that’s exactly what most institutions actually do. Assessment should be about how learners have positively changed, not whether they have met our demands.

This also implies that students should be participants in the planning and use of learning outcomes: they should be able to personalize their learning, and we should recognize their needs and interests. I use andragogy to frame this, because it is relatively uncontroversial, is easily understood, and doesn’t require people to change everything in their world view to become better teachers, but I could have equally used quite a large number of other models. Connectivism, Communities of Practice, and most constructivist theories, for instance, force us to similar conclusions.

I suggest that appreciative inquiry may be useful as an approach to assessment, inasmuch as the research methodology is purpose-built to bring about positive change, and its focus on success rather than failure makes sense in a learning context.

I also suggest the use of outcome mapping (and its close cousin, outcome harvesting) as a means of capturing unplanned as well as planned outcomes. I like these methods because they only look at changes, and then try to find out what led to those changes. Again, it’s about evaluation rather than judgment.

Smart learning environments, and not so smart learning environments: a systems view | Smart Learning Environments | Full Text

This is a new article from me about smartness in learning environments. The originally submitted title was ‘stupid learning environments’ but the reviewers rightly felt that this didn’t accurately reflect the main points of the article. It’s worth dwelling for a second on why I chose it, though. I created the original title in homage to Cipolla, whose definition in ‘The Basic Laws of Human Stupidity” resonates through the paper:

“A stupid person is a person who causes losses to another person or to a group of persons while himself deriving no gain and even possibly incurring losses.”

In the paper I describe how traditional educational systems can be (and, without much effort, usually are) not just a bit unintelligent but, in Cipolla’s sense of the word, positively stupid, because they can (and by default do) actively militate against effective learning in a number of important ways. It’s not the first paper in which I have mentioned this curious fact, nor the first one in which I have suggested ways to overcome the problem but, in this paper, it is really just intended as an illustrative example of how learning environments can result in unwanted behaviours, and not the main point of the piece.

The main point of the paper is that typical definitions of smart learning environments in existing literature, that talk only of digital tools embedded in or overlaid on an environment, make little sense because smartness in an environment is not a consequence of smartness in its components, but of how they work together to support learning. An individual brain cell is not smart, but systems comprised of lots of them, connected in the right ways, can be. Equally, an individual professor might (occasionally) be very smart but, without a lot of coordination and/or connection, a collection of them is no smarter than a collection of cats. The point is that smartness in an environment is a systems issue that, generally speaking, has little to do with the pieces of digital technology we embed in it (a distributed model) or that we overlay on top (a centralized model). Most importantly, perhaps, a model of a smart learning environment that ignores the most intelligent and dynamic parts of it (the learners), or that only looks at a tiny fraction of the environment, makes no sense whatsoever. The paper is thus an attempt to shift the focus away from digital tools and towards the roles that they and other smart things (like students and professors and cats) can play in the broader learning environment. To do that it meanders a bit around a bunch of related issues, integrating a number of ideas I have written about before such as orchestral perspectives on soft and hard technologies, the gestalt nature of teaching, and the value of connectivist patterns of thinking, leading to a few suggested strategies for building smart learning environments (not just smart tools), and a conclusion that the smartest learning environments are “inhabited spaces that provide the richest opportunities for people to connect, engage, support, and challenge one another to learn”.

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Laziness Does Not Exist

Sloth (public domain from Flickr Commons)This is a refreshing article from E Price, a social psychologist, who makes an obvious and self-evident point that is far too often forgotten: that there are always underlying reasons for what we perceive as laziness. This quote sums it up:

“People do not choose to fail or disappoint. No one wants to feel incapable, apathetic, or ineffective. If you look at a person’s action (or inaction) and see only laziness, you are missing key details. There is always an explanation. There are always barriers. Just because you can’t see them, or don’t view them as legitimate, doesn’t mean they’re not there. Look harder.”

I suspect that we don’t address the issue as much as we should because people with problems (i.e. all of us, in one way or another) usually make our lives more difficult. In fact, that’s pretty much what we mean by ‘lazy’ – if inaction has no harmful effects, then it is just relaxation. It seems to me, therefore, that ‘laziness’ characterizes a harmful effect, whether on self or others, rather than being a psychological characteristic of a person. Laziness is not a state of mind: it is a harmful effect of any number of different states of mind.

If someone is not doing what is expected of them, whether in work, study, or play, it normally makes our own lives more difficult. In the workplace this is usually pretty obvious: if someone is not working as much as they should, everyone else has to work more in order to compensate. It might not always be so clear cut, though. For instance, a lazy student might sometimes reduce our workload as teachers because we don’t have to mark work that is not submitted, and we don’t have to engage with a student that fails to show up. To be fair, it is almost as common that laziness means we have to engage in lengthy and traumatic plagiarism proceedings, because we make the stakes so high and the motivation so extrinsic that a fair number of students take shortcuts to the mark, rather than face the traumas of learning in the ways we insist they should learn. But, whether or not it reduces our workload, it still affects us deeply because, if a student is failing, we have failed. The fact that they are the ones that receive the ‘F’ is a consequence of a stupid power relationship that institutionally absolves us of virtually all responsibility for our own failure, but the fact remains that a failing student is also a failed student, and no one likes to fail. If we were truly great teachers, none of our students would ever fail, so a student that fails is a clear sign that we are not truly great. Maybe it’s because we are too lazy.


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Open Education Resources, Massive Open Online Courses, and Online Platforms for Distance and Flexible Learning

Ironically published in a closed and massively over-priced Handbook of IT in Primary and Secondary Education, here’s a chapter from me and Gerald Ardito on open and distance learning in the context of teaching children (paywall). I don’t know very much about primary and secondary education per se, but Gerald knows a lot, and we share a lot of attitudes, interests, and practices relating to education in general, so it was fun authoring this with him.

In the chapter we characterize openness as freedom from constraint – the more there are constraints, the less open it is, on whatever dimension of openness you choose to consider. The insight that pleases me most in this chapter is that, as applied in adult education, openness has traditionally been about making it easier to get in, whereas in child education the problem lies in making it easier to opt out, whether of a specific school or of the curriculum requirements imposed on it. In the chapter we use this as a foundation to explore dimensions of openness, kinds of openness, and ways of escaping the pedagogical constraints of traditional teaching systems.  

One thing that is important to observe, and that is implicit in our chapter, is that this simple characterization hides a wealth of complexity, nuance, and fuzziness. Most adult learners who are enrolled within an educational system have a great many constraints that prevent or discourage them from getting out of it, or at least out of the chunk into which they have enrolled, and most child learners have a great many freedoms, often including things we do mention in the chapter like homeschooling and (sometimes, though often dependent on income or religious persuasion) alternative schools of many varieties, but equally within the structure of traditional schooling itself. However, as a general pattern, it seems to me that any system that demands attendance, especially where even the alternative choices are themselves constrained in the extent to which they are allowed to depart from a fixed curriculum, cannot be accurately described as particularly open, any more than one that erects barriers to attendance or that unnecessarily limits how and what is learned within it. An open prison provides fewer barriers to leaving it than a traditional prison, and may allow greater freedoms within its boundaries, but it is still a prison.

Openness, however, is not so much about freedom as it is about control. There is often less than no point in removing barriers to choice if the learners do not know what to choose or why to choose it. A large part of the essence of being in control therefore lies in our ability to delegate choices to another. This is exactly how all powerful people are powerful: they are able to exercise influence over others who will do what they wish to be done to achieve what they wish to achieve.

I believe that a central and fundamental goal of education is empowerment of learners. Consequently, anything that disempowers learners is almost certainly a bad thing (exceptions apply only when the needs of one conflict with the need of others), and anything that eliminates barriers is a good thing. This is why there is a moral imperative for all educators to seek openness in all that they do, whether in terms of access, pedagogy, engagement, content, or whatever, and to eliminate barriers to learning whatever form they may take. Education empowers. Openness empowers education.

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Unintelligent machines

In 2012 there were roughly 100 million lines of code in an average car, a number that has been rapidly increasing for decades, and is no doubt significantly higher now. If you printed out 100 million lines of code, it would consume approximately 1.8 million pages of text, or a stack of paper approaching 200 metres in height. Assuming a text coverage of about 5%, if you were using (say) an HP inkjet printer which uses 35g of ink per thousand pages, it would take about 630kg of ink to print and you would make your way through over 50,000 ink cartridges (which, at about $CAD40 a piece, would set you back a couple of million dollars). On a 20ppm printer, it would take over 600 days of continuous printing, not allowing for time between cartridge changes, paper refills, etc, nor the fact that the printer would need to be replaced every day or two as it reached the end of its useful life.  To be fair, much of that would be duplicate code, well-tested libraries, and standard functions, lots of it is involved in stuff like entertainment systems, USB readers, and other non-critical systems and, of those 100 million lines, ‘only’ around 10 million are actually involved in systems that make the vehicle do its thing.

But wow.

The industry average for bugs varies between 15-50 defects per thousand lines. Microsoft reckon they have that down to 0.5 per thousand which, as anyone who has ever used Microsoft software will no doubt agree, is still way too high. I think that it might result from a peculiarly rosy definition of ‘defect’, and it certainly doesn’t include code behaviours that are entirely intentional but horribly wrong. But let’s assume that they are being open and truthful about it and that this really is a realistic defect rate. In that case, in the 10 million lines of code that make the vehicle work, there will be roughly 5000 defects, a good number of which will definitely cause security holes, some of which might be positively dangerous in their own right. Most of those vehicles are wirelessly connected and updated over the air, and there has been a significant increase in in-vehicle networking over the years (Cisco are becoming big players here) so the opportunities for system-level bugs and vulnerabilities are growing all the time. Meanwhile, the human side of the Internet continues to explode, and so the opportunities and tools available to skript kiddies expand at an exponential rate.

The average car weighs around 1500kg and can easily travel at 140kph. Just saying.

I’m not particularly worried about intelligent machines becoming our robot overlords. We’ve really got a long way to go before we even know what such a thing is, let alone how to make one and, by the time we do get there, we’ll know how to augment ourselves so that we are at least a match for them. But unintelligent machines are another matter.

XKCD on voting software




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You Can Learn Everything Online Except for the Things You Can't

cookies (public domain, Wired magazine article from Rhett Allain that is big on metaphor (courses are the chocolate chips, the cookie is the on-campus experience) but very small on critical thinking. What it does highlight, though, is the failure of imagination lurking in much online and in-person learning discussion and literature, and I give credit to Allain for recognizing the obvious elephant in the room: that education is about learning to be, not about learning to do/learning stuff. As he puts it, “the whole cookie is about becoming more mature as a human. It’s about leveling up in the human race”. I couldn’t agree more. What we explicitly teach and what students actually learn are utterly different things, and our own little contributions are at best catalysts, at worst minor diversions. To simply compare the chocolate chips is a variant on the McNamara Fallacy, and well done to Allain for pointing this out in a mainstream publication. Where I profoundly disagree is the bizarre notion that colleges somehow bake better cookies, or that cookies are the only (or even the best) medium in which to embed chocolate chips.

Allain’s confusion is shared by a great many professional educators and educational researchers so, assuming he is not a professional researcher in the field, his ignorance is forgivable. If we are being persnickety, there is no such thing as either online or in-person learning: learning is something that is done by people (individually and collectively) and it resides in both people and the environments/objects they co-create and in which they live. It is not done online or in-person. It is done in the connections we make, in our heads and between one another. 

It is fair to observe that there are huge differences between online and on-campus learning. There is no doubt that removing people from the rest of the human race, and shoving a bunch of them who share an interest in learning together in one concentrated space does result in some interesting and useful side effects, and it does lead to a distinctive set of benefits. When done well (admittedly rarely) it gives people time to dream, time to explore, time to do nothing much apart from reflect, to discover, to connect, and to talk, to grow. For kids who have lived dependent lives in schools and their homes this can be a useful transition phase. So, yes, there are things learned in physical colleges that are not the same as things learned in other places. But that’s a trite truism. There are things learned in pubs, on planes, while swimming, in fields, etc, etc, etc that are distinctive too.

There is equally no doubt that those that don’t go to college can and do get at least the same diversity and richness in their learning experience: it’s just a different set of things that result from the complex interactions and engagements with where they happen to be and who they happen to know. Being less removed from the rest of life and the community has its own benefits, situating learning in different contexts, enabling richer connections between all aspects of human life. The online folk have (innately) much more control of their learning experience and, on the whole, therefore need to work harder to make the most of the environments they are in – it doesn’t come in a neat, self-contained, packaged box. But to suggest that it is any the less rich and meaningful is to do online learners a deep disservice. My own institution, Athabasca University, doesn’t have online learners. We just have learners, who live somewhere, in communities and in regions, among people and places that matter to them. We provide another (online) place to dwell but, unlike a traditional campus-based institution, it’s not an either/or alternative: our online place coexists with and extends into myriad other physical places, that reach back into it and enrich it as much as we reach out and enrich them. At least, that’s how it works when we do it right.

Analogies and metaphors can be useful jumping-off points for understanding things, and I’m OK with the cookie idea because it emphasizes the intimate relationship between teaching and learning. A more useful analogy, though, might be to compare and contrast online vs in-person learning with the experiences of those who watch movies on a home theatre via Netflix, YouTube, Amazon Prime, Mubi, etc vs those who watch movies at the cinema. There’s a great deal to be said for the cinema – the shared experience, the feeling of belonging to a crowd and, of course, the big benefits of being able to hang out with fellow movie-goers before and after the movie. There’s also the critical value of the rituals, and the simple power of the event. I love going to movie theatres. On the other hand, if you have a decent enough rig at home (technologies matter) there’s also a lot to be said for the control (stop when you need a break, rewind to catch things you missed or want to see again, adjust the volume to your needs, eat the food you want, drink what you wish, etc), the vast choice (tens of thousands of movies rather than a handful), the flexibility (when you want, with whom you want, at a pace to suit you), the focus (no coughing, chatting, phone-using idiots around you, etc), the diversity and range of social connectedness (from looking up reviews on IMDB to chatting about it on social media or with others in the room), and the comfort of watching movies at home.

Can one replace the other? Not really. Is one better than the other? It depends. I’m glad I don’t have to make a final binary choice in the matter, and I think that’s how we should think about online and in-person teaching. I don’t mean that a single institution should offer alternative online and in-person routes: that’s way too limiting, like only getting movies from one organization. I mean that education can and should be a distributed experience, chosen by the learners (with guidance if they wish), not tied to one place and one method of learning. Just as I can watch YouTube, Netflix, Mubi, Crave, Amazon Prime, Apple, or whatever, as well as go to any one of several movie theatres nearby (not to mention open-air movie events etc), so should I be able to choose my ways to learn.

Disclaimer: this is not a perfect metaphor by any means. Perhaps it would be fairer to compare watching a live play with watching streaming TV, and it certainly doesn’t begin to capture the significant differences in engagement, interaction, activity, and creativity involved in the educational processes compared with ‘passive’ watching of entertainment. But it’s still better than chocolate chip cookies.

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Scholarly publishing is broken. Here’s how to fix it

An article for Aeon by Jon Tennant on the heinous state of affairs that gives unscrupulous publishers profit margins that put Apple to shame while hiding publicly funded research from the public that pays for it. It is a shamefully broken system that stands in the way of human progress. It has to change.

The ground this (open access) article goes over is much the same as the ground many of us have been tilling for many years, but it’s well expressed, and good to see it aired in a non-academic (though intellectually vigorous) journal like Aeon. It winds up with a set of six recommendations for things that all academics can do to improve our lot, which all make sense to me:

  1. Sign, and commit to, the Declaration on Research Assessment, and demand fairer evaluation criteria independent of journal brands. This will reduce dependencies on commercial journals and their negative impact on research.
  2. Demand openness. Even in research fields such as global health, 60 per cent of researchers do not archive their research so it is publicly available, even when it is completely free and within journal policies to do so. We should demand accountability for openness to liberate this life-saving knowledge.
  3. Know your rights. Researchers can use the Scholarly Publishing and Academic Rights Coalition (SPARC) Author Addendum to retain rights to their research, instead of blindly giving it away to publishers. Regain control.
  4. Support libraries. Current library subscription contracts are protected from public view by ‘non-disclosure clauses’ that act to prevent any price transparency in a profoundly anti-competitive practice that creates market dysfunction. We should support libraries in renegotiating such contracts, and in some cases even provide support in cancelling them, so that they can reinvest funds in more sustainable publishing ventures.
  5. Help to build something better. On average, academics currently spend around $5,000 for each published article – to get a PDF and some extra sides. A range of different studies and working examples exist that show the true cost of publishing an article can be as low as $100 using cost-efficient funding schemes, community buy-in, and technologies that go a step further than PDF generation. We can do better.
  6. Use your imagination. What would you want the scholarly communication system to look like? What are all the wonderful features you would include? What can you do to help turn a vision into reality?


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Mindfulness Meditation Impairs Task Motivation but Not Performance

Sadly published behind a paywall (but, happily, also available at SciHub) this is a fascinating sequence of studies from Hafenbrack & Voh that, firstly, appears to demonstrate that mindfulness (meditative practice) actively reduces motivation to perform a wide range of cognitively taxing or repetitive tasks, then shows that (despite this, and contrary to what might be expected) the loss of motivation has little or no effect on performance. The studies seem well-designed and well integrated, involving a very wide range of participants across continents, a wide variety of activities, and lots of good meta-analysis to pull them together. I’ll talk about why there are none-the-less very good reasons to be cautious in wholeheartedly accepting the results later on but, even with my provisos, the fact that such an effect can be seen at all is really interesting. Hafenbrack & Voh hypothesize (and provide evidence) that, because mindfulness tends to result in improvements in many other areas of cognition and performance, the overall effect is more or less neutral on actual task performance. The researchers partly explain this by citing other studies showing meditation-mediated improvements in empathy, reading comprehension, resilience to unpleasant images, resistance to distraction, negotiation effectiveness, and improved health indicators, though they only attempt to find out about reduced levels of distraction in their own experiments. They conclude that the effects of mindfulness on performance are complex and nuanced, and that employers and organizers of meditation/mindfulness sessions should therefore look carefully into their timing in the context of the working day.

What I find especially interesting about this study are the suggested reasons that mindfulness might impair motivation, which provided the initial justification for the research:

  1. mindfulness tends to focus on valuing the ‘now’ rather than dwelling on the future.
  2. mindfulness aims to reduce arousal (though, interestingly, many forms of it used in the Western mainstream actually seem to stoke the ego).

I’m not totally convinced by (1), inasmuch as it seems to me that the researchers believe that motivation is about desiring (or wishing to avoid) a future state, which is only partly true, notably in the case of simple extrinsic motivation (especially when externally regulated, as in these studies). It is far less likely to be true in the case of intrinsic motivation. Indeed, high levels of intrinsic motivation tend to be very focused on the ‘now’ and, in many cases, can result in a state of flow that can be very closely akin to mindfulness. For me, for instance, playing music can (sometimes) be a highly meditative pursuit with very little future focus. The same can (sometimes) be true when I get into the flow of most things, from writing to sailing to playing with my grandson. It can even be true for at least a couple of the tasks the researchers used to test their theory, when actively chosen by people as fun things to do rather than given to them as part of a research study.

That mindfulness may reduce arousal, and so in turn reduce motivation, is more believable though, again, it depends very much upon context whether that affects task performance positively or negatively. Sticking with a music theme, some pieces require intense concentration, physical effort, and mental agility, especially when learning a technically demanding new piece so, though it is usually bad to be tense when attempting such things, excessive relaxation might not be too great either. However, other kinds of music require you only to be at one with the sound and the instrument, and being in a relaxed mental state is really good for that. It is not a coincidence that many religious rituals involve music-making – especially that involving repetitive rhythmic sounds, chants, and drones – because it can lift you to exactly that detached, calm, yet spiritually heightened state of mindfulness. I find that the most fun and rewarding musical activities tend to be those which combine both modes at once – things like counterpoint or blues, in which the patterns are relatively easy to learn but remain infinitely rich in their expression. This hints that the real world of motivation, and other mental states, is way more complex than experiments like this suggest. I use music as a fairly unequivocal example, but similar diversity lies even in mundane bureaucratic form-filling, and certainly in complex creative behaviours like teaching or research.

Methodological concerns

One central problem with both hypotheses on reasons for reduced motivation, and with the researchers’ discussion and conclusions, is that they mistakenly assume motivation to be one thing – a very behaviourist orientation that looks at simple effects and ignores their complex causes – when, in reality, it is many things, often all at once, and the kind and strength of motivation varies enormously from one context to the next, often on a minute-by-minute basis, typically changing as a direct result of performance on a given task as well as other extrinsic factors. This study almost completely conceals such diversity.

Another problem is that the seemingly innocuous term ‘participants’ subtly and all too easily shifts from its actual meaning (the averaged behaviours of a particular group of people) to ‘all people’ in the description of the resultsm,the discussion, and the conclusion. It’s like saying ‘ripe bananas are yellow’ because (on average) if you examine any given square centimetre of a ripe banana in a batch, the chances are that it will mostly be yellow. This is despite the fact that virtually no bananas are wholly yellow, some are mainly red, a lot are partly green, and many are mainly black or brown. It bothers me that the consequent leap from ‘on average, people tend to be less motivated to perform researcher-imposed tasks after meditation’ to ‘meditation impairs task motivation’ is huge and unwarranted, especially in the absence of a truly plausible (or at least generalizable) model of why this might be so. In fairness, this is exactly the same form of flawed inductive thinking used in the vast majority of experimental studies in education, sociology, psychology, and related disciplines the world over. Knowing average tendencies can be extremely useful in all sorts of ways but to slip from ‘on average, X’ to ‘X’ as this and countless other studies do, is dangerous and counter-productive, especially when combined with a slip from ‘is’ to ‘ought’,  when suggesting ways the research can be applied.  This kind of experimental study is equally bad at discovering reasons for those averages because (unlike less fuzzy pseudo sciences) the range of possible inputs and outputs is vast, and highly interconnected: there’s irreversible complexity in the whole thing. Such studies can be at least partly saved by including rich qualitative information and analysis, but there’s none of that here. Smedlund offers a far subtler and more thorough critique of this kind of psychological experiment that I highly recommend anyone engaged in such studies should read.

Another way of interpreting the results

I like this paper and, for all my concerns, have found much that is thought-provoking within it. However, the simplistic implied behaviourist model of motivation and the lack of qualitative information that would help to better interpret the results does raise more questions than it answers. It also strikes me that, rather than drawing conclusions about ways to change the behaviour of people in organizations, it would make far more sense and have far more lasting value to look at ways to change the tasks expected of them so that they are (ideally) better aligned with intrinsic motivation, or (where that is difficult or impossible) are less externally regulated. Assuming at least a glimmer of truth in these findings (and there is more than a glimmer) I would hypothesize that, under such circumstances, mindfulness would be highly beneficial. Like so many things relating to human activity, it ain’t what you do it’s the way (and the where, and the when, and the why) that you do it that matters most.

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The ultimate insomnia cure: new GDPR legislation soothingly read by Peter Jefferson

The BBC’s Shipping Forecast is one of the great binding traditions of British culture that has been many a Brit’s lullaby since time immemorial (ie. long before I was born). Though I never once paid attention to its content in all the decades I heard it, eleven years after leaving the country I could still probably recite the majority of the 31 sea areas surrounding the British Isles from memory. 

For as long as I can recall, the gently soothing voice of the Shipping Forecast was Peter Jefferson (apparently he retired after 40 years in 2009) who, in this magnificently somnolent rendering, immortalizes exerpts from the General Data Protection Regulation that has recently come into force in the EU. My eyelids start drooping about 30 seconds in.


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Tim Berners-Lee: we must regulate tech firms to prevent ‘weaponised’ web

TBL is rightfully indignant and concerned about the fact that “what was once a rich selection of blogs and websites has been compressed under the powerful weight of a few dominant platforms.” The Web, according to Berners-Lee, is at great risk of degenerating into a few big versions of Compuserve or AOL sucking up most of the bandwidth of the Internet, and most of the attention of its inhabitants. In an open letter, he outlines the dangers of putting so much power into hands that either see it as a burden, or who actively exploit it for evil.

I really really hate Facebook more than most, because it aggressively seeks to destroy all that is good about the Web, and it is ruthlessly efficient at doing so, regardless of the human costs. Yes, let’s kill that in any way that we can, because it is actually and actively evil, and shows no sign of getting any nicer. I am somewhat less concerned that Google gets 87% of all online searches (notwithstanding the very real dangers of a single set of algorithms shaping what we find), because most of Google’s goals are well aligned with those of the Web. The more openly people share and link, the better it gets, and the more money Google makes. It is very much in Google’s interest to support an open, highly distributed, highly connected Web, and the company is as keen as everyone else to avoid the dangers of falsehoods, bias, and the spread of hatred (which are among the very things that Facebook feeds upon), and, thanks to its strong market position and careful hiring practices, it is more capable of doing so than pretty much anyone else. Google rightly hates Facebook (and others of its ilk) not just because it is a competitor, but because it removes things from the open Web, probably spreads lies more easily than truths, and so reduces Google’s value.

I am somewhat bothered that the top 100 sites (according to WIkipedia, based on Alexa and SimilarWeb results) probably get far more traffic than the next few thousand put together, and that the long tail pretty much flattens to approximately zero after that. However, that’s an inevitable consequence of the design of the Web (it’s a scale-free network subject to power laws), and ‘approximately zero’ may actually translate to hundreds of thousands or even millions of people, so it’s not quite the skewed mess that it seems. It is, as TBL observes, very disturbing that big companies with big pockets purchase potential competitors and stifle innovation, and I agree that (like all monopolies) they should be regulated, but there’s no way they are ever going to get everything or everyone, at least without the help of politicians and evil legislation, because it’s a really long tail.

It is also very interesting that even the top 10 – according to just about all the systems that measure such things – includes the unequivocally admirable and open Wikipedia itself, and also Reddit which, though now straying from its fully open model, remains excellently social and open. In different ways, both give more than they take.

It is also worth noting that there are many different ways to calculate rank. (based on the Mozscape web index of 31 Billion domains and 165 Billion pages) has a very different view of things, for instance, in which Facebook doesn’t even make it to the domains listing, and is way below WordPress and several others in the popular pages list, which is a direct result of it being a closed and greedy system. Quantcast’s perspective is somewhat different again, albeit only focused on US sites which are a small but significant portion of the whole.

Most significantly, and to reiterate the point because it is worth making, the long tail is very long indeed. Regardless of the dangers of a handful of gigantic platforms casting their ugly shadows over the landscape, I am extremely heartened by the fact that, now, over 30% of all websites run on WordPress, which is both open source and very close to the distributed ideal that TBL espouses, allowing individuals and small communities to stake their claims, make a space, and link (profusely) with one another, without lock-in, central control, or inhibition of any kind. That 30% puts any one of the big monoliths, including Facebook, very far into the shade. And, though WordPress’s nearest competitor (Joomla, also open source) accounts for a ‘mere’ 3% of all websites, there are hundreds if not thousands of similar systems, not to mention a huge number of pages (50% of the total, according to W3Techs) that people still roll for themselves.

Yes, the greedy monoliths are extremely dangerous and should, where possible, be avoided, and it is certainly worth looking into ways of regulating their activities, nationally and internationally, as many governments are already doing and should continue to do so. We must ever be vigilant. But the Web continues to grow, and to diversify regardless of their pernicious influence because it is far bigger than all of them put together.

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