Pedagogical Paradigms in Open and Distance Education | Handbook of Open, Distance, and Digital Education

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This is a chapter by me and Terry Anderson for Springer’s new Handbook of Open, Distance, and Digital Education that updates and refines our popular (1658 citations, and still rising, for the original paper alone) but now long-in-the-tooth ‘three generations’ model of distance learning pedagogy. We have changed the labels for the pedagogical families this time round to ones that I think are more coherent, divided according to their epistemological underpinnings: the objectivist, the subjectivist, and the complexivist. and we have added some speculations about whether further paradigms might have started to emerge in the 11 years since our original paper was published. Our main conclusion, though, is that no single pedagogical paradigm will dominate in the foreseeable future: that we are in an era of great pedagogical diversity, and that this diversity will only increase as time goes by.

The three major paradigms

Objectivist: previously known as ‘behaviourist/cognitivist’, what characterizes objectivist pedagogies is that they are both defined by assumptions of an objective external reality, and driven by (usually teacher-defined) objectives. It’s a paradigm of teaching, where teachers are typically sages on the stage using methods intended to achieve effective learning of defined facts and skills. Examples include behaviourism, learning styles theories, brain-based approaches, multiple intelligence models, media theories, and similar approaches where the focus is on efficient transmission and replication of received knowledge.

Subjectivist: formerly known as ‘social constructivist’, subjectivist pedagogies are concerned with – well – subjects: they are concerned with the personal and social co-construction of knowledge, recognizing its situated and always unique nature, saying little about methods but a lot about meaning-making. It’s a paradigm of learning, where teachers are typically guides on the side, supporting individuals and groups to learn in complex, situated contexts. Examples include constructivist, social constructivist, constructionist, and similar families of theory where the emphasis is as much on the learners’ growth and development in a human society as it is on what is being learned.

Complexivist: originally described as ‘connectivist’ (which was confusing and inaccurate), complexivist pedagogies acknowledge and exploit the complex nature of our massively distributed cognition, including its richly recursive self-organizing and emergent properties, its reification through shared tools and artefacts, and its many social layers. It’s a paradigm of knowledge, where teachers are fellow learners, co-travellers and role models, and knowledge exists not just in individual minds but in our minds’ extensions, in both other people and what we collectively create. Examples include connectivism, rhizomatic learning, distributed cognition, cognitive apprenticeship, networks of practice, and similar theories (including my own co-participation model, as it happens). We borrow the term ‘complexivist’ from Davis and Sumara, whose 2006 book on the subject is well worth reading, albeit grounded mainly in in-person learning.

No one paradigm dominates: all typically play a role at some point of a learning journey, all build upon and assemble ideas that are contained in the others (theories are technologies too), and all have been around as ways of learning for as long as humans have existed.

Emerging paradigms

Beyond these broad families, we speculate on whether any new pedagogical paradigms are emerging or have emerged within the 12 years since we first developed these ideas. We come up with the following possible candidates:

Theory-free: this is a digitally native paradigm that typically employs variations of AI technologies to extract patterns from large amounts of data on how people learn, and that provides support accordingly. This is the realm of adaptive hypermedia, learning analytics, and data mining. While the vast majority of such methods are very firmly in the objectivist tradition (the models are trained or designed by identifying what leads to ‘successful’ achievement of outcomes) a few look beyond defined learning products into social engagement or other measures of the learning process, or seek open-ended patterns in emergent collective behaviours. We see the former as a dystopic trend, but find promise in the latter, notwithstanding the risks of filter bubbles and systemic bias.

Hologogic: this is a nascent paradigm that treats learning as a process of enculturation. It’s about how we come to find our places in our many overlapping cultures, where belonging to and adopting the values and norms of the sets to which we belong (be it our colleagues, our ancestors, our subject-matter peers, or whatever) is the primary focus. There are few theories that apply to this paradigm, as yet, but it is visible in many online and in-person communities, and is/has been of particular significance in collectivist cultures where the learning of one is meaningless unless it is also the learning of all (sometimes including the ancestors). We see this as a potentially healthy trend that takes us beyond the individualist assumptions underpinning much of the field, though there are risks of divisions and echo chambers that pit one culture against others. We borrow the term from Cumbie and Wolverton.

Bricolagogic: this is a free-for-all paradigm, a kind of meta-pedagogy in which any pedagogical method, model, or theory may be used, chosen for pragmatic or personal reasons, but in which the primary focus of learning is in choosing how (in any given context) we should learn. Concepts of charting and wayfinding play a strong role here. This resembles what we originally identified as an emerging ‘holistic’ model, but we now see it not as a simple mish-mash of pedagogical paradigms but rather as a pedagogic paradigm in its own right.

Another emerging paradigm?

I have recently been involved in a lengthy Twitter thread, started by Tim Fawns on the topic of his recent paper on entangled pedagogy, which presents a view very similar indeed to my own (e.g. here and here), albeit expressed rather differently (and more eloquently). There are others in the same thread who express similar views. I suggested in this thread that we might be witnessing the birth of a new ‘entanglist’ paradigm that draws very heavily on complexivism (and that could certainly be seen as part of the same family) but that views the problem from a rather different perspective. It is still very much about complexity, emergence, extended minds, recursion, and networks, and it negates none of that, but it draws its boundaries around the networked nodes at a higher level than theories like Connectivism, yet with more precision than those focused on human learning interactions such as networks of practice or rhizomatic learning. Notably, it leaves room for design (and designed objects), for meaning, and for passion as part of the deeply entangled complex system of learning in which we all participate, willingly or not. It’s not specifically a pedagogical model – it’s broader than that – though it does imply many things about how we should and should not teach, and about how we should understand pedagogies as part of a massively distributed system in which designated teachers account for only a fraction of the learning and teaching process. The title of my book on the subject (that has been under review for 16 months – grrr) sums this up quite well, I think: “How Education Works”. The book has now (as of a few days ago) received a very positive response from reviewers and is due to be discussed by the editorial committee at the end of this month, so I’m hoping that it may be published in the not-too-distant future. Watch this space!

Here’s the chapter abstract:

Building on earlier work that identified historical paradigm shifts in open and distance learning, this chapter is concerned with analyzing the three broad pedagogical paradigms – objectivist, subjectivist, and complexivist – that have characterized learning and teaching in the field over the past half century. It goes on to discuss new paradigms that are starting to emerge, most notably in “theory-free” models enabled by developments in artificial intelligence and analytics, hologogic methods that recognize the many cultures to which we belong, and a “bricolagogic,” theory-agnostic paradigm that reflects the field’s growing maturity and depth.

Reference

Dron J., Anderson T. (2022) Pedagogical Paradigms in Open and Distance Education. In: Zawacki-Richter O., Jung I. (eds) Handbook of Open, Distance and Digital Education. Springer, Singapore. https://doi.org/10.1007/978-981-19-0351-9_9-1

English version of my 2021 paper, “Technology, technique, and culture in educational systems: breaking the iron triangle”

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Technology, technique, and culture in educational systems: breaking the iron triangle

This is the (near enough final) English version of my journal paper, translated into Chinese by Junhong Xiao and published last year (with a CC licence) in Distance Education in China. (Reference: Dron, Jon (2021).  Technology, technique, and culture in educational systems: breaking the iron triangle (translated by Junhong Xiao). Distance Education in China, 1, 37-49. DOI:10.13541/j.cnki.chinade.2021.01.005).

The underlying theory is the same as that in my paper Educational technology: what it is and how it works (Reference: Dron, J. Educational technology: what it is and how it works. AI & Soc 37, 155–166 (2022). https://doi.org/10.1007/s00146-021-01195-z direct link for reading, link to downloadable preprint) but this one focuses more on what it means for ways we go about distance learning. It’s essentially about ways to solve problems that we created for ourselves by solving problems in the context of in-person learning that we inappropriately transferred to a distance context.

Here’s the abstract:
This paper presents arguments for a different way of thinking about how distance education should be designed. The paper begins by explaining education as a technological process, in which we are not just users of technologies for learning but coparticipants in their instantiation and design, implying that education is a fundamentally distributed technology. However, technological and physical constraints have led to processes (including pedagogies) and path dependencies in In-person education that have tended to massively over-emphasize the designated teacher as the primary controller of the process. This has resulted in the development of many counter technologies to address the problems this causes, from classrooms to grades to timetables, most of which have unnecessarily been inherited by distance education. By examining the different strengths and weaknesses of distance education, the paper suggests an alternative model of distance education that is more personal, more situated in communities and cultures, and more appropriate to the needs of learners and society.

I started working on a revised version of this (with a snappier title) to submit to an English language journal last year but got waylaid. If anyone is interested in publishing this, I’m open to submitting it!

So mouse jigglers are a thing now

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https://www.amazon.ca/s?k=mouse+jiggle

A mouse jiggler is a mechanical device that literally jiggles your mouse, or a dongle that electronically mimics mouse movement. There are even a few real mouses with jiggling functions built in. Why? Though there are a few people who might use it to keep their computer awake (there are better ways), mainly it is because there are companies that track whether their employees are working based on whether they are moving their mouses frequently enough. This would be laughable were it not so goddam serious.

I hardly know where to begin with the many things that are wrong with monitoring your employees’ mouse movements to check that they are working. Anyone ever heard of respect? Anyone ever heard of trust or the importance of it? Anyone ever heard of autonomy or why it matters? Anyone ever read even a blog post about motivation (let alone any actual research)? Anyone ever heard of the McNamara Fallacy?  Anyone ever considered whether people are more productive when given autonomy than when forced to conform? Anyone ever looked at how people actually work, and what makes them productive? Anyone ever even thought about it? So I thoroughly applaud the many people who are buying these devices to fool their employers into thinking they are working when they are, quite rightly and inevitably, emphatically not doing so. The employers deserve everything they (don’t) get. There are devices from a few dollars up that will jiggle your mouse for you so, if your employer seriously thinks that your job is to move a mouse, get one now! Screw them and let them stew in their own vile festering juices. If the measure of your value can be diminished to whether you are sitting in front of a computer (even if you are a data entry clerk) then cheat all you can, because no one cares about you, or whether you can actually do your job.

It is possibly even more concerning that some people get them because, though they may not deliberately be monitored for ‘activity’,  they don’t want their status to be shown as ‘away’ in whatever real-time system they use (IMs, Slack, MS Teams, etc) in case anyone thinks they are slacking. It is sadder when, rather than submitting to unwarranted policing, people police themselves because of what they believe other people will think of them.

There are lessons to be learned from this for online ‘educators’ who think that they can automatically proctor online exams, or who think that log files and similar activity trackers based on automated collection of computer use can tell them anything useful about whether or how their students are learning. Making learning visible is not about measuring compliance, especially when the means to measure it is such a weak, irrelevant, and easily gamed proxy that assumes everyone is average. It’s about designing the learning experience so that students can share their learning – process and product – with you and with one another, voluntarily, as fellow human beings doing something marvellous, unique, and unquantifiable.

Originally posted at: https://landing.athabascau.ca/bookmarks/view/11154838/so-mouse-jigglers-are-a-thing-now

Requiem for an email address

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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. 

jon.dron@brighton.ac.uk/jd29@bton.ac.uk

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Nobody has ever learned anything at a distance, and no one ever goes to a distance institution

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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.

It is not surprising, therefore, that no significance difference is normally found between online and in-person learning outcomes because they are essentially the same thing.

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:

horse pulling a car

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 just there: 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.

Conclusion

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.

Gather is a remarkable retro but modern collaboration, cooperation, and socialization system: I really like it.

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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.

A group in Gather (not my students!)

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

The Uncensored Library – Reporters without borders

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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

I am, at last, Canadian, eh? 🇨🇦

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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?

Some thoughts for Ada Lovelace Day

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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:

Mary Tsingou's original algorithm design, drawn in freehand

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.

graph showing the huge drop in women in IT from the 1980s onwards

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