Some time today my email address and all its aliases at the University of Brighton will suddenly cease to exist, vacuumed away by an automated script that doesn’t care.
It has been 30 years since I sent my first ever SMTP email from that address, from a Vax terminal, carefully ending it with a single dot on its own line to signal the end of the message. Among the (yes) millions of emails (for years, well over 100 every day) that have since been sent to and from the account have been announcements of the births and deaths of many loved ones, job offers, notifications of awards, letters to and from long lost friends, and a metric tonne of spam and bacn. Among those messages were expressions of love, sorrow, pleasure, anger, and joy. It has been the tenuous thread connecting me with those I love when all others have failed. It has helped me make new friends and keep old ones. It has taught me, and I have taught with it. It has given me delight, angst, inspiration, frustration, fear, and exaltation. It has, in the past, been so much a part of my identity that my students used to refer to me as jon-dot-dron. I’ve been through eight physical addresses and at least as many phone numbers in the time I’ve had the account. It has been my prosthetic memory and my filing system. Its archives contain (or contained) records of the history of half my life. Some of those emails are what made that history. There are/were messages in it from more than a few loved ones who have since died, or with whom I’ve lost contact. It followed me through many jobs and roles at the University of Brighton – student, IT manager, lecturer, honorary fellow, and more.
But the Centre for Learning and Teaching to which my final role was attached is no more, and so my email account must now die with it.
I can think of no other digital entity associated with me that has lasted as long as that email address apart from, perhaps, the user account with which it was associated (which is also disappearing today). The nearest thing to it was my ‘Ship of Theseus’ PC that existed for over 20 years, from the 1980s to the 2010s, every single part of which had been replaced multiple times, and which (like the Ship of Theseus itself) had spawned a few offspring along the way that were made from its discarded parts. I was a little sad to let go of that, too, but its surviving contents lived on in something better, so it was no great loss. This is a bit different.
Pragmatically, it is pointless for me to retain my Brighton email account. With just a handful of exceptions a year, the only emails ever sent to it nowadays are spam or bacn, I hardly ever send emails from it, and it takes effort to maintain the thing. But I will miss it. The comfortable fiction that we are just what goes on in our brains and bodies has seldom seemed less believable. Our minds extend into those around us, the artefacts we create, the artefacts we use, the people we cherish. Those emails contained a bit of me, and a bit of all those who sent them. It was where our minds met. I think this should be recognized with more than a shrug. And so I write this both to celebrate the existence and to mourn the passing of a little bit of me.
Nobody learns anything online or at a distance. Nothing at all. You are always learning it where you are now. All learning is in-person learning, and it all takes place within a physical environment, part of which (only a part) may include whatever technologies you might be using to talk with people, read, watch, listen, and so on.
But there’s a distance component to all in-person education, too. People who learn with teachers in a physical space are almost always also interacting with other participants in the teaching role at a distance, usually in time and space – authors, classroom designers, editors, illustrators, timetablers, curriculum designers, and so on. And, for ‘in-person’ institutional learners, most of the learning itself also usually occurs at a distance, outside the classroom. This is most tangible in the form of assignments and homework but, if teaching works, sense-making connections always occur after the lesson is over, and continue to do so long after (sometimes decades after) the teaching event, almost never in the same place that the lesson originally occurred. So all learning is distance learning, in the sense of occurring somewhere and somewhen other than where and/or when teaching occurred.
That doesn’t mean that there are no consistent differences between the experiences of what we describe as online and in-person learners: very far from it. Some of those differences are inherent in the medium, whether online or in-person. But the big differences that actually make a difference are not in learning: they are in teaching.
There are (or should be) huge differences between distance/online teaching and in-person teaching. The most important differences are not technological, as such, nor do they lie in the physical distance between learners and teachers. Michael Moore very usefully talks of distance in terms of structure and dialogue to describe the transactional distance that matters more but, as I observed in my first book, from a system dynamics perspective, transactional distance is mainly a measure of the locus of control, not structure or dialogue as such. There are other differences that matter, but control is the big one.
Control in in-person teaching
Pedagogies are solutions to problems, and the physical context is rife with problems, most notably that it makes it far more likely that teachers will control much of the process. There are a great many reasons for this, most of which have nothing at all to do with pedagogical intent: it’s mainly physics, economics, and biology, and the consequences that follow. Though many teachers try to avoid it, doing so is a seriously upstream struggle. It causes immense problems, primarily because of the great harm it does to intrinsic motivation. Learners lack autonomy and are often over-challenged or under-challenged (thus undermining the two central foundations of intrinsic motivation) because, by default, everyone is forced to follow the same pace and method, determined by the teacher. Good in-person pedagogies compensate for these inherent weaknesses, by allowing (emphasis on allowing) learners to personalize their own learning, by engaging in dialogue, by building communities, by helping learners to find their own motivation, and so on.
Control in online teaching
Without significant coercion, the learner is always far more autonomous in almost any online or distance teaching context. Students don’t need to follow the teacher’s plan because they are not bound to a scheduled classroom, with all the problems of being heard, being present, and working in lock-step together that arise from it. Unfortunately, far too many online teachers assume that they have the same level of control as their in-person counterparts and, usually, it becomes a partly self-fulfilling assumption through coercive methods like frequent grading, draconian scheduling, and tests. They consequently often make use of very similar pedagogies to those of their in-person counterparts, struggling to find simulacra or workarounds for the affordances of physical spaces that are no longer available, and vainly believing that the learner is going to follow the path that they have determined for them. An unfortunate unintentional consequence of in-person teaching is thus too readily accepted as teaching’s central motif.
To make matters more difficult, educational institutions impose other stupid ideas that are side-effects of teaching in physical classrooms like fixed-length (or multiples of fixed lengths) courses, deadlines, and failure (what the heck?). I think this picture helps to illustrate my feelings about this:
Dealing with this kind of problem may require some big changes at an institutional level because teachers too rarely have much choice as to how long their courses might be, or whether students should receive grades for them, or how they are scheduled, and so on.
Outside of arbitrary institutional constraints, online courses do not have to be a particular length, because more complex scheduling is possible (and easily automated) and, if they are self-paced, there’s no good reason for them to have any schedule at all, nor for them to end on a particular date, as long as they can be funded. Credentialing and learning are two completely different processes that (thanks to the motivational impacts) are in many ways mutually exclusive. They must therefore be decoupled, as much as possible. It makes no sense to talk definitively about failure when you are learning: learning is either accomplished or not accomplished yet, and failure is an integral part of the process of accomplishment (ask any gamer). And, though they might not always get a credential on the first try, students never need to irrevocably fail to get them: they can just keep going until they succeed, or until they lose interest, much as we do for driving tests.
Distributed in-person teaching
Such issues highlight the fact that it is not just the designated teacher who teaches. Obviously, the main teacher in any learning transaction is the learner, sometimes followed by the designated teacher or writer of a textbook, but the rules, structures, processes and methods that define the educational context also teach. So do other students, especially in an in-person context thanks to the fact that they are all forced to be in one place at one time. In an in-person context, from the simple fact of having to turn up at a particular place and time to the structures of courses, assessments, classroom spaces, cafes, and schedules, the institutional context controls the learning process in profound ways.
Again, for teachers, good pedagogies have to compensate for the problems that such things cause, as well as to take advantage of the positive affordances the physical context provides. There are many of those. A great deal of learning can be assumed to occur in journeys to and from classrooms, in canteens, in common rooms, in libraries, and in other shared spaces, for example. Combined with the fact that a great deal of the organization is done by others, and that institutional credentials motivate (not in a good way), institutions (not just teachers) themselves teach through their physical, temporal, and organizational form. Combined with the many other teachers involved in the process (the learners themselves, textbook authors, illustrators, designers, etc) this means that in-person teachers don’t actually have to teach very well in order for their students to succeed. The systems mean that students are drowning in a sea of teachers.
Distributed online teaching
The online teaching context is, in principle though not so much in practice, more malleable, diffuse, and affording of learner control, but it almost always lacks much in the way of controllable infrastructure that learners can safely be assumed to inhabit, so teaching generally needs to be pretty good because, without care, that might be all there is. However, there are ways to help provide a bit more of the structure that also teaches. Some people try to create simulations of the in-person infrastructure, such as learning cafes, less formal social spaces (such as Athabasca Landing), etc but, though they can help a bit, they seldom work very well. Partly, this is because of the too common focus on explicit outcomes and grading found in most institutional teaching together with failure by students and teachers to recognize the critical role of in-between spaces in learning. Mainly, though, it’s because it’s not justthere: students aren’t going to pass it on their way to somewhere else or be there for other reasons (like a need for rest or refreshment). They have to intentionally visit, typically with a purpose in mind but, as the main value of it is its purposelessness, that’s not often going to happen. It would be better to embed such spaces in the intentional teaching space, to allow informal interaction everywhere, but too few teaching systems (notably none of the mainstream LMSs) support that.
It can help a little to make the need for such engagement more explicit in the teaching process: to tell students it is a good idea to engage beyond the course. It doesn’t have to be virtual, or planned, or catered for by the institution or teacher. We could just suggest that learners talk about what they’ve learned with someone they know, or that they should visit a place where people do talk about such things, or share via social media. But we can and should provide social spaces where they can interact with one another beyond the course, too.
Another way is to acknowledge the physical and virtual context of the learner, and to design flexible learning experiences that allow them to apply what they are learning to where they are, or to make use of what is around them (virtually and physically) to support the learning process. This is a pedagogical solution that, for some subjects, fits very well. For instance, I can rely on nearly all of my students working or studying in a context that can be used for analyzing and building information systems. It’s harder in the case of subjects that are much more abstract, or where engaging directly with the subject might be dangerous or prohibitively expensive (e.g. nuclear physics or medicine).
Really, though, the big problem is one of perspective. It’s that we see our virtual institutions as analogues of our physical institutions, not as something really very different. Even quite enlightened edtech folk talk of students bringing their own devices, or bringing their own networks to the learning space. That’s laudable, in a way, but it’s completely the wrong way round. Instead, online and distance students bring their own institutions (plural), or bring their own courses into their own spaces. The need to go to an institution is a side-effect of the physics that co-determines how traditional teaching occurs. Students shouldn’t need to go to an online institution; institutions should come to them. That is, in fact, the reality of learning through online means, but almost everything we do works on the assumption that it is the other way round: that they visit us.
We (the teachers) are not, cannot be, and should not try to be the sole arbiters of how our distance/online students learn. Unless they want it, we should not even be managers or leaders of it. Instead, we should think of ourselves as parts of their support networks, available to provide help and direction as and when it is needed. If they want to delegate some of the control of the process to us then that’s great, because it keeps us employed and we’re often pretty good at it because it’s our job, but we should not take it unbidden.
We really need to let go of the notion that learning only takes place when and where our teaching happens, and that we are the sole directors of it. We need to acknowledge everything that learners bring with them, in prior learning, in digital and physical systems, in networks, and in pedagogical tools. But it’s not about bringing stuff to us: it’s about bringing it to their own learning. Above all, we need to recognize that online students do not come to institutional environments, but that they bring those institutions into their own environments. From that simple shift in perspective, myriad improvements follow.
The other day a small group of students and I had a really interesting experimental classroom session in Gather. The article linked here describes a much bigger-scale and intentional approach.
If you’re not familiar with Gather, its a web-based real-time social environment. Its deceptively simple (to the point of silliness) 8-bit interface provides a 2D top-down view of a virtual space that very closely resembles that of a 1980s video game – in fact, it’s even simpler than the seminal multi-player Habitat, that came out in 1985, inasmuch as it is only top-down. You could think of it as much simpler and flatter but vaguely in a similar vein to Minecraft or Habbo, but it’s easier to create new spaces (people have replicated whole buildings, islands, and villages, in 2D 8-bit form – there are even pubs and bars). Your cartoon-ish avatar can be moved around with really simple cursor-driven movements, though more complex interactions with objects require you to press the X key, and/or to make selections from menus or move things with your mouse. Spaces can be any size, you can create them and objects within them (including in the free version), and there are mapping tools to help you find people and places.
So far so not very interesting: been there and done that.
Immediately under the surface, however, is a full-fledged, very modern web-conferencing system with a wide range of options to share audio, webcams, documents, videos, images, whiteboards, screens, chat, calendars, and so on, which is (almost) infinitely extendable through embedding of any website. Objects left in the space can be persistent, so it’s not just about real-time meetings. You can send and leave messages, videos, voice recordings, and more. There’s a lot more to it that I’ve yet to explore, but I’ve not found anything I could do in almost any collaboration system that I could not do here. Functionally, it is not dissimilar to MS Teams, but there the similarity ends: this is way better in almost every way.
Though it looks like an ancient video game, the interface is actually extremely smart, because instead of interacting with a fixed, typically hierarchical, abstract set of documents and containers, it gives you an intuitive spatial view on everything, and the space is very easy to create, incredibly flexible, and visually well differentiated (not perfect for people with visual disabilities, but they are catered for). You can enter a private space with others if you wish, a bit like breakout rooms in conventional webmeeting systems except that it is easy for anyone to (literally) wander between them, to see who is inside (if enabled) and for the moderator of the space to be seen and heard by everyone, wherever they are. By default, outside a private space you can generally only hear and see someone if your avatar is near to theirs, so you could have hundreds of people in a space but only chat with those around you, much like a physical social gathering. As you move away the voice and the webcam video of those no longer proximal to you start to fade until they disappear altogether, while others you approach fade into view. Digital objects (e.g. files, presentations, videos, websites, etc) can be placed anywhere, in arbitrary but potentially meaningful spatial relationships with one another, and visitors can work on them or view them together.
The sense of social presence is very palpable in a way that far exceeds conventional webmeeting tools – it’s incredibly effective, without being intrusive, difficult, or demanding explicit interaction. No uncomfortable silences or artificial instrumental activities here, and you get to do things together, not just stare at one another’s faces or watch a document. In this space you could have a private office that people can ‘see’ you inside, but have to knock to come in and chat (without being heard by others). They can see if you are interacting with others (who can be anonymous shadows) and are therefore busy, or they can join in the conversation – they cannot overhear anything without you knowing they are there, much like in meatspace. You could ‘lock’ the room if you don’t want to be disturbed at all. You could leave your office to visit a common room, or classroom, or conference, or whatever. You could just stop by someone else’s office to chat, or they could leave messages and so on for you.
And, of course, you could use if for teaching, which is exactly what this linked article describes. It provides a really good in-depth description of how the author is using Gather to manage a very large introductory computing class, that goes into plenty of detail about how Gather works and what you can do there. The uses involve nothing more than plain vanilla options that take a few minutes to configure – a lot more is possible – but it’s easy to see how incredibly effectively it marries the digital environment and our evolved ability to navigate physical spaces, without trying to exactly mimic the real world beyond what is absolutely necessary to get around.
This seems like a vastly superior approach to communication than that of nearly all shared-reality VR, that mostly just replicates all the constraints and annoyances of the physical world or, when it doesn’t, feels jarring and wrong, not to mention almost always involving a steep learning curve and requiring a mighty machine to run it well (or, worse, separating you from your actual physical world with annoying goggles and headsets). Such a waste of computing power for no good reason. It’s not that shared-reality VR doesn’t have some compelling use cases – it does. It’s just deeply hopeless as a general-purpose social environment.
Though not quite as infinitely flexible as Minecraft or an old-fashioned MOO (that it resembles, albeit highly evolved from there) – at least in what I’ve seen so far – it’s much easier to get started and much easier to get around, plus it’s a fully featured synchronous web conferencing system. There’s copious and comprehensive help at https://support.gather.town/help. I contacted the company for an educational discount and thereby got involved with their tech support team (because I found a bug/feature that wouldn’t let me pay, not that it was needed for this small number of students), and I found them very responsive, friendly, and personally interested.
Gather is also vastly superior to the abstract, alienating, function-driven approaches of most ‘grid of faces’ webmeeting software like Teams, Zoom, or Webex, albeit that it shares with them the annoying need to visit a separate virtual space (a website), rather than integrating that space in the rest of your own environment. However, the only significant exception to that failing that I’m aware of is the very excellently designed Around, though even that has to become more of an isolated space (albeit with a cute campfire to sit around) if you are meeting many people, and it is nothing like as flexible or powerful as Gather – it’s just a meeting system.
Back in the early 2000s I tried to build a much simpler toy system along quite similar lines, called Dwellings. I used a metaphor of streets and buildings (my inspiration was Jane Jacobs’s ‘The Death and Life of Great American Cities’ – I tried to enable support for the kinds of things driving successful city areas), as well as a bunch of stigmergic cues to help with social navigation and some ideas drawn from MOOs. These were pre-HTML5 days and, though AJAX had recently been invented, I’d not discovered it, so it really didn’t work at all well: I had to invent some really bad and ugly ways to do synchronous stuff. I only got as far as providing clunky text chat, the interface was dire, it only supported sharing of web sites (and graffiti about them) and it was a truly awfully designed and implemented system that ground to a halt under the strain of more than about half a dozen simultaneous users. If you really want to suffer, a version from about 15 years ago is actually still online though I guess I should get round to removing it at some point as it couldn’t be much flakier. There were a few papers about it (e.g. this one, sadly paywalled by AACE but available via most university library accounts). Gather is orders of magnitude better, far more fully thought through and, above all, it actually works, really well, with a very full range of modern, effective features. I don’t like that it’s a cloud-only service that starts to get expensive for more than a few dozen people, I don’t like that it’s not open source, and I am not sure that some of my more staid colleagues would take it seriously: it really does look a lot like an old-fashioned game. But it is a really cool place to collaborate, cooperate, and socialize, in a fabulously retro but very modern way.
Originally posted at: https://landing.athabascau.ca/bookmarks/view/10868769/gather-is-a-remarkable-retro-but-modern-collaboration-cooperation-and-socialization-system-i-really-like-it
This is very cool – a library of articles and journals that have been censored in various regions, built inside Minecraft, that thereby evades censorship (for now). It lends a whole different meaning to ‘serious games’.
Originally posted at: https://landing.athabascau.ca/bookmarks/view/10846432/the-uncensored-library-%E2%80%93-reporters-without-borders
It has taken me over 14 years, with numerous setbacks along the way (some bizarre, some mundane), but, as of today, I am a Canadian citizen. I cried most of the way through the (Zoom) ceremony, and completely choked up singing the anthem.
I love Canada. I love that Canadian culture is guilty deep to its very heart (sorry), that caring for your neighbour is fundamental to our (yes, our!) identity, that line-ups last forever because everyone in front of you is having a fine and leisurely conversation with the person serving them, even in the biggest cities. I love waiting to cross a road on the corner of an empty street where a single truck heads nervously towards you half a kilometre away, but we all know the rules and it just works better that way. I love hockey, and the fact that the only riot I have ever seen here was when the Canucks (just, at the last possible moment) lost the Stanley Cup Final, but that half the city was up before work the next morning cleaning up the mess. I love the vast, vast land. I don’t think I’ll ever understand Tim Horton’s (really? Is that pale brown water actually coffee and what kind of doughnut doesn’t go bad for over a year?) but I love that it is so deeply embroiled with what it means to be Canadian that the awfulness of the coffee and doughnuts doesn’t matter. I love that there’s a hairdresser on every corner but that everyone’s haircut looks like it was done by their kids. I love the fact that diversity is a cause for celebration and delight, not division. I love plaid. I love that Canadians will describe themselves as German, or Scottish, or Polish, or pretty much anything (though almost never English) other than Canadian, even though the last person in their family to actually live elsewhere died a century ago. I love that I live in a city where over half the population was not born here. I love poutine, and mac n cheese, and beaver tails. I love that, wandering past my home in the very heart of a huge city are skunks, raccoons and coyotes, while seals, the occasional whale, beavers, and otters swim by, and giant bald eagles circle constantly overhead, eternally plagued by crows and seagulls trying to chase them from the sky. I love that everyone knows at least one person called Gord. I love that Canada is not America, and that’s part of the definition. I love that a gang of teenagers on a street corner will invariably wish you well and help you out rather than abuse you. I like maple syrup. I love maple leaves. I even like the anthem, though the words could do with far fewer gods and (in the French version) way less swords.
I could do without every second vehicle being a poorly driven truck or an SUV, the deep and unresolvable guilt at the horrific way indigenous people have been treated and continue to suffer, the mega-scale rape of the land that persists to this day, the many nonsensical practices and cultural quirks caught like diseases from south of the border, the fact that any prepared foodstuff contains more salt than food, and a few other things. But abhorring such things is quite Canadian, too.
I do miss the good-natured cruelty and friendly belligerence of old Blighty, the blithe disregard of rules, the bitingly dark humour, and cask beer in nearly every pub that won’t plaster you to the floor after a single cold, fizzy, strong yet peculiarly flavourless pint (and it’s an actual pint, where ‘pint’ means exactly the same thing literally everywhere). And, though a proper, salt-of-the-earth Canadian pub is a truly wonderful thing, I miss those English pubs – real pubs that smell of history and tobacco smoke (despite that smokers now smoke outside), where no one cares whether you are still working on your food or expects a tip for asking it. I miss the word ‘fuck’ used as a punctuation mark in every sentence, and ‘cunt’ used as a term of endearment. I miss the layer upon endless layer of the past that oozes out of every tiny cranny, and fills every little nook with tired ghosts that cling to the living. I miss the fact that people are bound together by mutual gloom or shared hatred of everyone else, but that there’s something chummy in it, a sort of kindness, a recognition of shared adversity that runs deep. And I miss the NHS.
But, on balance, I’d really much rather be here, and I am very proud indeed to be a citizen of the wonderful, apologetic, law-abiding, kindly mosaic that is Canada. It’s good to be Canadian, eh?
This Scientific American article tells the tale of one of the genesis stories of complexity science, this one from 1952, describing what, until relatively recently, was known as the Fermi-Pasta-Ulam (FPU) problem (or ‘paradox’, though it is not in fact a paradox). It is now more commonly known as the Fermi-Pasta-Ulam-Tsingdou (FPUT) problem, in recognition of the fact that it was only discovered thanks to the extraordinary work of Mary Tsingou, who wrote the programs that revealed what, to Fermi, Pasta, and Ulam, was a very unexpected result.
The team was attempting to simulate what happens to energy as it moves around atoms connected by chemical bonds. This is a classic non-linear problem that cannot be observed directly, and that cannot be solved by conventional reductive means (notwithstanding recent work that reveals statistical patterns in complex systems like urban travel patterns). It has to be implemented as a simulation in order to see what happens. Fermi, Pasta, and Ulam thought that, with enough iterations, it would reveal itself to be ergodic: that, given long enough, every state of a given energy of the system would be visited an equal number of times. Instead, thanks to Mary Tsingou’s work, they found that it was non-ergodic. Weird stuff happened, that could not be predicted. It was chaotic.
The discovery was, in fact, accidental. Initial results had shown the expected regularities then, one day, they left the program running for longer than usual and, instead of the recurring periodic patterns seen initially, it suddenly went haywire. It wasn’t a bug in the code. It was a phase transition, perhaps the first unequivocal demonstration of deterministic chaos. Though Fermi died and the paper was not actually published until nearly a decade later, it is hard to understate the importance of this ‘accidental’ discovery that deterministic systems are not necessarily ergodic. As Stuart Kauffman puts it, ‘non-ergodicity gives us history‘. Weather is non-ergodic. Evolution is non-ergodic. Learning is non-ergodic. We are non-ergodic. The universe is non-ergodic. Though there are other strands to the story that predate this work, more than anything else this marks the birth of a whole new kind of science – the science of complexity – that seeks to deal with the 90% or more of phenomena that matter to us, and that reductive science cannot begin to handle.
Here’s a bit of Tsingou’s work on the program, written for the MANIAC computer:
It was not until 2008 that Tsingou’s contribution was fully recognized. In the original paper she was thanked in a footnote but not acknowledged as a co-author. It is possible that, had it been published right away she might have received proper credit. However, it is at least as possible that she might not. The reasons for this are a mix of endemic sexism, and (relatedly) the low esteem accorded to computation at the time.
The relationship between these two factors runs deep. Historically, the word ‘computer’ originally referred to a job title. As scientists in the 19th Century amassed vast amounts of data that needed processing, there was far too much for an individual to handle. They figured out that tasks could be broken up into smaller pieces and farmed out in parallel to humans who could do the necessary rote arithmetic. Because women were much cheaper to hire, and computing was seen as a relatively unskilled (albeit very gruelling and cognitively demanding) role, computing therefore became a predominantly female occupation. From the 19th Century onwards into the mid 20th Century, all-women teams worked on astronomical data, artillery trajectories, and similar tasks, often performing extremely complex mathematical calculations requiring great precision and endurance, always for far less pay than they deserved or that a man would receive. Computers were victims of systematic gender discrimination from the very beginning.
The FPUT problem, however, is one that doesn’t lend itself to chunking and parallel computation: the output of one iteration of the computation is needed before you can calculate the next. Farming it out to human computers simply wouldn’t work. For work of this kind, you have to have a machine or it would take decades to come up with a solution.
In the first decade or so after digital computers were invented significant mathematical skill was needed to operate them. Because of their existing exploitation as human computers, there was, luckily enough, a large workforce of women with advanced math skills whose manual work was being obsoleted at the same time, so women played a significant role in the dawn of the industry. Mary Tsingou was not alone in making great contributions to the field.
By the 1970s that had changed a lot, not in a good way, but numbers slowly grew again until around the mid-1980s (a terrible decade in so many ways) when things abruptly changed for the worse.
Whether this was due to armies of parents buying PCs for their (male) children thanks to aggressive marketing to that sector, or highly selective media coverage, or the increasing recognition of the value of computing skills in the job market reinforcing traditional gender disparities, or something else entirely (it is in fact complex, with vast self-reinforcing feedback loops all the way down the line), the end result was a massive fall in women in the field. Today, less than 17% of students of computer science are women, while the representation of women in most other scientific and technical fields has grown considerably.
There’s a weirder problem at work here, though, because (roughly – this is an educated guess) less than 1% of computer science graduates ever wind up doing any computer science, unless they choose a career in academia (in which case the figure rises to very low single figures), and very few of them ever do more mathematics than an average greengrocer. What we teach in universities has wildly diverged from the skills that are actually needed in most computing occupations at an even sharper rate than the decline of women in the trade. We continue to teach it in ways that would have made sense in the 1950s, when it could not be done without a deep understanding of mathematics and the science behind digital computation, even though neither of these skills has much if any use at all for more than a minute fraction of our students when they get out into the real world. Sure, we have broadened our curriculum to include many other aspects of the field, but we don’t let students study them unless they also learn the (largely unnecessary in most occupations) science and math (a subject that suffers even lower rates of non-male participation than computing). Thinking of modern computing as a branch of mathematics is a bit like treating poetry as a branch of linguistics or grammar, and thinking of modern computing as a science is a bit like treating painting as a branch of chemistry. It’s not so much that women have left computing but that computing – as a taught subject – has left women.
Computing professionals are creative problem solvers, designers, architects, managers, musicians, writers, networkers, business people, artists, social organizers, builders, makers, teachers, or dreamers. The main thing that they share in common is that they work with computers. Some of them are programmers. A few (mostly those involved in designing machines and compilers) do real computer science. A few more do math, though rarely at more than middle school level, unless they are working on the cutting edge of a few areas like graphics, AI, or data science (in which case the libraries etc that would render it unnecessary have not yet been invented). The vast majority of computing professionals are using the outputs of this small elite’s work, not reinventing it. It it not surprising that there is enormous diversity in the field of computing because computers are universal machines, universal media, and universal environments, so they encompass the bulk of human endeavour. That’s what makes them so much fun. If you are a computing professional you can work with anyone, and you can get involved in anything that involves computers, which is to say almost everything. And they are quite interesting in and of themselves, partly because they straddle so many boundaries, and ideas and tools from one area can spark ideas and spawn tools in another.
If you consider the uses of computer applications in many fields, from architecture or design to medicine or media to art or music, there is a far more equal gender distribution. Computing is embedded almost everywhere, and it mostly demands very different skills in each of its uses. There are some consistent gaps that computing students could fill or, better, that computing profs could teach in the context they are used. Better use could be made of computers across the board with just a little programming or other technical skills. Unfortunately, those who create, maintain, and manage computers and their applications tend to mainly come out of computer science programs (at least in North America and some other parts of the world) so many are ill prepared for participating in all that richness, and computing profs tend to stick with teaching in computer science programs so the rest of the world has to figure out things they could help with for themselves.
I think it is about time that we relegated computer science to a minor (not unimportant) stream and got back into the real world – the one with women in it. There’s still a pressing need to bring more women into that minor stream: we need inspirations like Mary Tsingou, we could do worse than preferentially hiring more non-male professors, and we desperately need to shift the discriminatory culture surrounding (especially) mathematics but, if we can at least teach in a way that better represents the richness and diversity of the computing profession itself, it would be a good start.
Originally posted at: https://landing.athabascau.ca/bookmarks/view/10624709/some-thoughts-for-ada-lovelace-day
With a possible audience of thousands, and without a clue they were there because the Zoom output was streamed to a different site (weird), I talked very fast about my experience of higher education for about 20 minutes at the THE UK Student Festival yesterday. The talk was recorded and will be used again for the THE Canada Student Festival later in the month. It’s a huge event – over 8000 enrolled (though not all attending every session) – with quite a lot of other keynotes and a great many other talks, panels, and discussions, aimed at helping students starting out in higher education. The audience was very different from those I normally talk to, and the (very sensible) strict 20-minute format gave me a lot less leeway than the usual hour allowed, so I found it interestingly challenging. These are the slides I used.
The brief I was given was not to preach, but to share my experience of higher education, as a student and as an educator. My personal agenda was to talk about why and how online learning is worth doing (especially at AU), so I tried (a bit clunkily) to aim my story in that direction. I failed to remember to mention some key things, I spent too long on others, and I suspect that the most memorable message that came through was, for in-person students living on campus, to get a kettle (it’s a great way to make lots of new friends fast) but, hopefully, my bigger message got through to some.
The essential point of my wild ramble was not that kettles are the solution to success in higher education, but that students and the rest of us should take ownership of our own education: it should be done by us, not to us. We should learn the way we want to learn, and we should learn what we want to learn; we should seek adventure and challenge rather than easy pickings; and we should hang out with interesting people and/or those we care about, because that’s how most learning happens, as well as being a large part of what makes it meaningful. I noted that we should focus on learning and should to try to ignore grades as much as possible, because grades destroy the love of doing something simply because we enjoy it. Essentially, my advice was about finding the things that intrinsically motivate us and reducing the effects of things that demotivate us. My own educational journey, and (I think) that of most committed educators, has largely followed that path: that’s how we thrived in a system not conducive to intrinsic motivation, and it’s the path we try to encourage our own students to take. I observed that it is much easier to own your own education when it is done online, at least if it is done in ways that take advantage of the medium, and not through a pale simulacrum of in-person teaching, because the teacher cannot be in control, the level of challenge is much more controllable, and there are way more people (online and in your own environment) who can support you.
The conference theme was ‘challenges of the digital’ so I thought it might be fun to reverse the problem, and to think instead about the challenges of in-person education. In this presentation I imagined a world in which in-person teaching had never been invented, and presented a case for doing so. In fairness, it was not a very good case! But I did have fun using some of the more exotic voice changing features of my Voicelive Play vocal processor (which I normally use for performing music), presenting some of the arguments against my suggestions in different voices using a much better mic than my usual (pretty good) Blue Yeti. I might not use the special effects again that often, but I was quite impressed with the difference the better microphone made.
My central points (mostly implicit until the end) were:
That the biggest challenge of the digital is all the baggage that we have inherited from in-person teaching, and our continuing need to interoperate with in-person institutions.
That pedagogies are neither universal nor neutral. They are solutions to problems of learning in a particular context, in assembly with countless constraints and possibilities provided by that context: people, tools, structures, methods, systems, and so on.
That solutions to learning in a physical context – at least in the one-to-many model of traditional education systems – inevitably lead to a very strong power imbalance between teacher and learner, where the teacher is in control of every moment that the teaching event occurs. This has many repercussions, not least of which being that needs for autonomy and competence support are very poorly addressed (though relatedness comes for free), so it is really bad for intrinsic motivation.
Thus, the pedagogies of physical spaces have to compensate for the loss of control and achievable challenge that they naturally entail.
That the most common approach – and, again, an almost inevitable (i.e. the shortest path) follow-on from teaching a lot of people at once – involves rewards and punishments, that massively impair or destroy intrinsic motivation to learn and, in most cases, actively militate against effective learning.
That the affordances of teaching everyone the same thing at once lead fairly naturally to credentials for having learned it, often achieved in ‘efficient’ ways like proctored exams that are incredibly bad for learning, and that greatly reinforce the extrinsic motivation that is already highly problematic in the in-person modality. The credentials, not the learning, become the primary focus.
That support for autonomy and competence are naturally high in online learning, though support for relatedness is a mix of good and bad. There is no need for teachers being in control and, lacking most of the means of control available to in-person teachers, the only reliable way to regain it is through rewards and punishments which, as previously mentioned, are fatal to intrinsic motivation.
That the almost ubiquitous ways that distance educators inherit and use the pedagogies, methods, and structures of in-person learning – especially in the use of coercion through rewards and punishments (grades, credentials, etc) but also in schedules, fixed-length courses, inflexible learning outcomes, etc – are almost exactly the opposite of what its technologies can best support.
Towards the end, acknowledging that it is difficult to change such complex and deeply entangled systems (much though it is to be desired) I presented some ways of reducing the challenges of the physical in online teaching, and regaining that lost intrinsic motivation, that I summarized thus:
Let go (you cannot and should not control learning unless asked to do so), but stay close;
Make learning (not just its products) visible (and, in the process, better understand your teaching);
Make learning shared (cooperation and, where possible, collaboration built in from the ground up);
Don’t ever coerce (especially not through grades);
Care (for learners, for learning, for the subject).
It’s a theme that I have spoken and written of many, many times, but (apart from the last few slides) the way I presented it this time was new for me. I had fun pretending to be different people, and the audience seemed to like it, in a challenging kind of a way. There were some great questions at the end, not all of which I had time to answer, though I’m happy to continue the conversation here, or via Twitter.
There has been a lot of negative reaction of late to virtual proctors of online exams. Perhaps students miss the cheery camaraderie of traditional proctored exams, sitting silently in a sweaty room with pen and paper, doing one of the highest stakes, highest stress tasks of their lives, with someone scrutinizing their every nervous tic whose adverse judgment may destroy their hopes and careers, for the benefit of an invisible examiner whose motives and wishes are unclear but whose approval they dearly seek. Lovely. Traditional. Reassuring. A ritual for us all to cherish. It’s enough to bring a tear to the eye.
But exams cost a huge amount of money to host and to invigilate. It is even worse when one of the outcomes might, for the student or the invigilator, be death or disability due to an inconvenient virus.
I have a better solution.
Instead of costly invigilators and invigilation centres, all we need to do is to send out small (returnable, postage-paid) robots to students’ homes. A little robot sitting on the student’s desk or kitchen table as they sit their written exam (on paper, of course – tradition matters), recording every blink, watching their fingers writing on the paper, with 360 degree panoramic camera and the ability to zoom in on anything suspicious or interesting. Perhaps it could include microphones, infrared and microwave sensors, and maybe sensors to monitor skin resistance, pulse, etc, in order to look for nefarious activities or to call the ambulance if the student seems to be having a heart attack or stroke due to the stress. It could be made to talk, too. Perhaps it could offer spoken advice on the process, and alerts about the time left at carefully selected intervals. Students could choose the voice. It would also allow students to sit exams wherever and whenever they please: we are all in favour of student choice. With a bit of ingenuity it could scan what the students have written or drawn, and send it back to an examiner. Or, with a bit more ingenuity and careful use of AI, it could mark the paper on the spot, saving yet more money. Everyone wins.
It would be important to be student-centric in its design. It could, for instance, be made to look like a cute little furry animal with googly eyes to put students more at ease. Maybe it could make soothing cooing noises like a tribble, or like a cat purring. Conversely, it could be made to scuttle ominously around the desk and to appear like a spider with venomous-looking fangs, making gentle hissing noises, to remind students of the much lamented presence of in-person invigilators. Indeed, maybe it could be made to look like a caricature of a professor. More advanced models could emit bad smells to replicate invigilator farts or secret smoking habits. It could be made small and mobile, so that students could take it with them if they needed a bathroom break, during which it might play soothing muzak to put the student at ease, while recording everything they do. It would have to be tough, waterproof, and sterilizable, in order to cope with the odd frustrated student throwing or dunking it.
Perhaps it could offer stern spoken warnings if anomalies or abuses are found, and maybe connect itself to a human invigilator (I hear that they are cheaper in developing nations) who could control it and watch more closely. Perhaps it could be equipped with non-lethal weaponry to punish inappropriate behaviour if the warnings fail, and/or register students on an offenders database. It could be built to self-destruct if tampered with.
Though this is clearly something every university, school, and college would want, and the long-term savings would be immense, such technologies don’t come cheap. Quite apart from the hardware and software development costs, there would be a need for oodles of bandwidth and storage of the masses of data the robot would generate.
I have a solution to that, too: commercial sponsorship.
We could partner with, say, Amazon, who would be keen to mine useful information about the students’ surroundings and needs identified using the robot’s many sensors. A worn curtain? Stubborn stains? A shirt revealing personal interests? Send them to Amazon! Maybe Alexa could provide the voice for interactions and offer shopping advice when students stop to sharpen their pencils (need a better pencil? We have that in stock and can deliver it today!). And, of course, AWS would provide much of the infrastructure needed to support it, at fair educational prices. I expect early adopters would be described as ‘partners’ and offered slightly better (though still profitable) deals.
And there might be other things that could be done with the content. Perhaps the written answers could be analyzed to identify potential Amazon staffers. Maybe students expressing extremist views could be reported to the appropriate government agency, or at least added to a watch-list for the institution’s own use.
Naysayers might worry about hackers breaking into it or subverting its transmissions, or the data being sent to a country with laughable privacy laws, or the robot breaking down at a critical moment, or errors in handwriting recognition, but I’m sure that could be dealt with, the same as we deal with every other privacy, security, and reliability issue in IT in education. No problem. No sir. We have lawyers.
The details still need to be ironed out here and there, but the opportunities are endless. What could possibly go wrong? I think we should take this seriously. Seriously.