Some meandering thoughts on ‘good’ and ‘bad’ learning

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There has been an interesting brief discussion on Twitter recently that has hinged around whether and how people are ‘good’ at learning. As Kelly Matthews observes, though, Twitter is not the right place to go into any depth on this, so here is a (still quite brief) summary of my perspective on it, with a view to continuing the conversation.

Humans are nearly all pretty good at learning because that’s pretty much the defining characteristic of our species. We are driven by an insatiable drive to learn at from the moment of our birth (at least). Also, though I’m keeping an open mind about octopuses and crows, we seem to be better at it than at least most other animals. Our big advantage is that we have technologies, from language to the Internet, to share and extend our learning, so we can learn more, individually and collectively, than any other species. It is difficult or impossible to fully separate individual learning from collective learning because our cognition extends into and is intimately a part of the cognition of others, living and dead.

However, though we learn nearly all that we know, directly or indirectly, from and with other people, what we learn may not be helpful, may not be as effectively learned as it should, and may not much resemble what those whose job is to teach us intend. What we learn in schools and universities might include a dislike of a subject, how to conceal our chat from our teacher, how to meet the teacher’s goals without actually learning anything, how to cheat, and so on. Equally, we may learn falsehoods, half-truths, and unproductive ways of doing stuff from the vast collective teacher that surrounds us as well as from those designated as teachers.

For instance, among the many unintended lessons that schools and colleges too often teach is the worst one of all: that (despite our obvious innate love of it) learning is an unpleasant activity, so extrinsic motivation is needed for it to occur. This results from the inherent problem that, in traditional education, everyone is supposed to learn the same stuff in the same place at the same time. Students must therefore:

  1. submit to the authority of the teacher and the institutional rules, and
  2. be made to engage in some activities that are insufficiently challenging, and some that are too challenging.

This undermines two of the three essential requirements for intrinsic motivation, support for autonomy and competence (Ryan & Deci, 2017).  Pedagogical methods are solutions to problems, and the amotivation inherently caused by the system of teaching is (arguably) the biggest problem that they must solve. Thus, what passes as good teaching is largely to do with solving the problems caused by the system of teaching itself. Good teachers enthuse, are responsive, and use approaches such as active learning, problem or inquiry-based learning, ungrading, etc, largely to restore agency and flexibility in a dominative and inflexible system. Unfortunately, such methods rely on the technique and passion of talented, motivated teachers with enough time and attention to spend on supporting their students. Less good and/or time-poor teachers may not achieve great results this way. In fact, as we measure such things, on average, such pedagogies are less effective than harder, dominative approaches like direct instruction (Hattie, 2013) because, by definition, most teachers are average or below average. So, instead of helping students to find their own motivation, many teachers and/or their institutions typically apply extrinsic motivation, such as grades, mandatory attendance, classroom rules, etc to do the job of motivating their students for them. These do work, in the sense of achieving compliance and, on the whole, they do lead to students getting a normal bell-curve of grades that is somewhat better than those using more liberative approaches. However, the cost is huge. The biggest cost is that extrinsic motivation reliably undermines intrinsic motivation and, often, kills it for good (Kohn, 1999). Students are thus taught to dislike or, at best, feel indifferent to learning, and so they learn to be satisficing, ineffective learners, doing what they might otherwise do for the love of it for the credentials and, too often, forgetting what they learned the moment that goal is achieved. But that’s not the only problem.

When we learn from others – not just those labelled as teachers but the vast teaching gestalt of all the people around us and before us who create(d) stuff, communicate(d), share(d), and contribute(d) to what and how we learn – we typically learn, as Paul (2020) puts it, not just the grist (the stuff we remember) but the mill (the ways of thinking, being, and learning that underpin them). When the mill is inherently harmful to motivation, it will not serve us well in our future learning.

Furthermore, in good ways and bad, this is a ratchet at every scale. The more we learn, individually and collectively, the more new stuff we are able to learn. New learning creates new adjacent possible empty niches (Kauffman, 2019) for us to learn more, and to apply that learning to learn still more, to connect stuff (including other stuff we have learned) in new and often unique ways. This is, in principle, very good. However, if what and how we learn is unhelpful, incorrect, inefficient, or counter-productive, the ratchet takes us further away from stuff we have bypassed along the way. The adjacent possibles that might have been available with better guidance remain out of our reach and, sometimes, even harder to get to than if the ratchet hadn’t lifted us high enough in the first place. Not knowing enough is a problem but, if there are gaps, then they can be filled. If we have taken a wrong turn, then we often have to unlearn some or all of what we have learned before we can start filling those gaps. It’s difficult to unlearn a way of learning. Indeed, it is difficult to unlearn anything we have learned. Often, it is more difficult than learning it in the first place.

That said, it’s complex, and entangled. For instance, if you are learning the violin then there are essentially two main ways to angle the wrist of the hand that fingers the notes, and the easiest, most natural way (for beginners) is to bend your hand backwards from the wrist, especially if you don’t hold the violin with your chin, because it supports the neck more easily and, in first position, your fingers quickly learn to hit the right bit of the fingerboard, relative to your hand. Unfortunately, this is a very bad idea if you want a good vibrato, precision, delicacy, or the ability to move further up the fingerboard: the easiest way to do that kind of thing is to to keep your wrist straight or slightly angled in from the wrist, and to support the violin with your chin. It’s more difficult at first, but it takes you further. Once the ‘wrong’ way has been learned, it is usually much more difficult to unlearn than if you were starting from scratch the ‘right’ way. Habits harden. Complexity emerges, though, because many folk violin styles make a positive virtue of holding the violin the ‘wrong’ way, and it contributes materially to the rollicking rhythmic styles that tend to characterize folk fiddle playing around the world. In other words, ‘bad’ learning can lead to good – even sublime – results. There is similarly plenty of space for idiosyncratic technique in many of the most significant things we do, from writing to playing hockey to programming a computer and, of course, to learning itself. The differences in how we do such things are where creativity, originality, and personal style emerge, and you don’t necessarily need objectively great technique (hard technique) to do something amazing. It ain’t what you do, it’s the way that you do it, that’s what gets results. To be fair, it might be a different matter if you were a doctor who had learned the wrong names for the bones of the body or an accountant who didn’t know how to add up numbers. Some hard skills have to be done right: they are foundations for softer skills. This is true of just about every skill, to a greater or lesser extent, from writing letters and spelling to building a nuclear reactor and, indeed, to teaching.

There’s much more to be said on this subject and my forthcoming book includes a lot more about it! I hope this is enough to start a conversation or two, though.

References

Hattie, J. (2013). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. Taylor & Francis.

Kauffman, S. A. (2019). A World Beyond Physics: The Emergence and Evolution of Life. Oxford University Press.

Kohn, A. (1999). Punished by rewards: The trouble with gold stars, incentive plans, A’s, praise, and other bribes (Kindle). Mariner Books.

Paul, A. M. (2021). The Extended Mind: The Power of Thinking Outside the Brain. HarperCollins.

Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Publications.

 

Slides from my ICEEL 22 Keynote, November 20, 2022

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ICEEL 22 keynote

Here are the slides (11.2MB PDF) from my opening keynote yesterday at the 6th International Conference on Education and E-Learning, held online, hosted this year in Japan. In it I discussed a few of the ideas and consequences of them from my forthcoming book, How Education Works: Teaching, Technology, and Technique.

Title: It ain’t what you do, it’s the way that you do it, that’s what gets results

Abstract: In an educational system, no teacher ever teaches alone. Students teach themselves and, more often than not, teach one another. Textbook authors and illustrators, designers of open educational resources, creators of curricula, and so on play obvious teaching roles. However, beyond those obvious teachers there are always many others, from legislators to software architects, from professional bodies to furniture manufacturers . All of these teachers matter, not just in what they do but in how they do it: the techniques matter at least as much as the tools and methods.  The resulting complex collective teacher is deeply situated and, for any given learner, inherently unpredictable in its effects. In this talk I will provide a theoretical model to explain how these many teachers may work together or in opposition, how educational systems evolve, and the nature of learning technologies. Along the way I will use the model to explain why there is and can be no significant difference between outcomes for online and in-person teaching, why teaching to perceived learning styles research is doomed to fail, why small group tutoring will always (on average) be better than classroom teaching, and why quantitative research methods have little value in educational research.

Learning, Technology, and Technique | Canadian Journal of Learning and Technology

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This is my latest paper, Learning, Technology, and Technique, in the current issue of the Canadian Journal of Learning and Technology (Vol. 48 No. 1, 2022).

Essentially, because this was what I was invited to do, the paper shrinks down over 10,000-words from my article Educational technology: what it is and how it works (itself a very condensed summary of my forthcoming book, due out Spring 2023) to under 4,000 words that, I hope, more succinctly capture most of the main points of the earlier paper. I’ve learned quite a bit from the many responses to the earlier paper I received, and from the many conversations that ensued – thank you, all who generously shared their thoughts – so it is not quite the same as the original. I hope this one is better. In particular, I think/hope that this paper is much clearer about the nature and importance of technique than the older paper, and about the distinction between soft and hard technologies, both of which seemed to be the most misunderstood aspects of the original. There is, of course, less detail in the arguments and a few aspects of the theory (notably relating to distributed cognition) are more focused on pragmatic examples, but most are still there, or implied. It is also a fully open paper, not just available for online reading, so please freely download it, and share it as you will.

Here’s the abstract:

To be human is to be a user, a creator, a participant, and a co-participant in a richly entangled tapestry of technologies – from computers to pedagogical methods – that make us who we are as much as our genes. The uses we make of technologies are themselves, nearly always, also technologies, techniques we add to the entangled mix to create new assemblies. The technology of greatest interest is thus not any of the technologies that form that assembly, but the assembly itself. Designated teachers are never alone in creating the assembly that teaches. The technology of learning almost always involves the co-participation of countless others, notably learners themselves but also the creators of systems, artifacts, tools, and environments with and in which it occurs. Using these foundations, this paper presents a framework for understanding the technological nature of learning and teaching, through which it is possible to explain and predict a wide range of phenomena, from the value of one-to-one tutorials, to the inadequacy of learning style theories as a basis for teaching, and to see education not as a machine made of methods, tools, and systems but as a complex, creative, emergent collective unfolding that both makes us, and is made of us.

Originally posted at: https://landing.athabascau.ca/bookmarks/view/14622408/my-latest-paper-learning-technology-and-technique-now-online-in-the-canadian-journal-of-learning-and-technology

The limits and limitations of business requirements

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Athabasca University’s Digital Governance Committee recently got into a heated debate about whether and why we should support Zoom. It was a classic IT manageability vs user freedom debate and, as is often the way in such things, the suggested resolution was to strike up a working group/sub-committee of stakeholders to identify business requirements that the IT department could use to find an acceptable solution. This approach is eminently sensible, politically expedient, tried-and-tested, and profoundly inadequate.

horse-carAs Henry Ford (probably never) said, “if I’d asked people what they wanted they would have said ‘a better horse'”.

A design approach that starts by gathering business requirements situates the problem in terms of the current solution, which is comprised of layers of solutions to problems caused by other solutions. For simple ‘hygiene’ tech that serves a hard, well-defined business function – leave reporting, accounting, etc – as long as you do properly capture the requirements and don’t gloss over things that matter, that’s normally fine, because you’re just building cogs to make the existing machine work more smoothly. However, for very soft social technologies like meetings, with potentially infinite ways of using them (by which I mean purposes, techniques, ways of assembling them with other technologies, and so on), no list of requirements could even begin to scratch at the surface. The thing about soft technologies – meetings, writing, pencils, pedagogies, programmable computers, chisels, wheels, technologies of fire, groups, poetry, etc – is that they don’t so much solve problems as they create opportunities. They create adjacent possible empty niches. In other words, they are defined by the gaps they leave, much more than the gaps they fill. What happens as a result of them is fundamentally non-deducible. 

Solving different problems, creating different possibles

Meetings are assemblies of vast ranges of technologies and other phenomena, and they serve a vast number of purposes. Meetings are not just one technology but a container for an indefinitely large number of them. They are, though, by and large, solutions to in-person problems, many of which are constrained by physics, physiology, psychology, and other factors that do not apply or that apply differently online. Most webmeeting systems are attempts to replicate the same solutions or (more often) to replicate other webmeeting systems that have already done so, but they are doomed to be pale shadows of the original because there are countless things they cannot replicate, or can only replicate poorly. Among the phenomena that are the default in in-person meetings are, for example:

  • the immense salience brought about by travelling to a location, especially when it involves significant effort (lost in webmeetings);
  • the fact that it forces attention for a sustained period   (most webmeeting software and ways of using it makes inattention much easier);
  • the social bonding that we have evolved to feel in the presence of others (not well catered for in webmeeting software);
  • the focus and meaning that comes from the ‘eventness’ of the occasion (diluted in webmeetings);
  • the ability to directly work together on an issue or artefact (limited in some ways in webmeetings, though potential exists for collaborative construction of digital artefacts);
  • the inability to invisibly escape (easy in most webmeetings);
  • the microexpressions, postures, movements, smells, etc that support communication (largely lost in webmeetings);
  • the social bonding value of sharing food and drink (lost in webmeetings);
  • the blurred boundaries of entering and leaving, the potential to leave together (usually lost in webmeetings);
  • the bonding that occurs in having a shared physical experience, including adversities such as a room that is too hot, roadworks outside, wasps in the room, etc, as well as good things like the smell of good coffee or luxurious chairs (not remotely possible in webmeetings, apart from when the tech fails – but then the meeting fails too);
  • the support for nuances of verbal interaction – knowing when it’s OK to interrupt, being able to sigh, talk at once, etc, not to mention having immediate awareness of who is speaking (webmeetings mostly suck at this);
  • the ability to cluster with others – to sit next to people you know (or don’t know), for instance (rarely an option in most webmeetings, and nothing like as salient or rich in potential as its in-person counterpart even when allowed);
  • the salience of being in a space, with all the values, history, power relationships, and so on that it embodies, from who sits where to which room is chosen (hardly a shadow of this in most webmeetings);
  • the ability to stand up and walk around together (a motion-sickness-inducing experience in webmeetings);
  • the problems and benefits of both over-crowding and excessive sparsity (very different in webmeetings);
  • the means to seamlessly integrate and employ other technologies, including every digital technology as well as paper, dance, desks, chairs, whiteboards, pins, clothing, coffee, doors, etc, etc, etc. (webmeetings offer a tiny fraction of this);
  • and so on.

A few of these might be replicated in current or future webmeeting software, though usually only in caricature. Most simply cannot be replicated at all, even if we could meet as virtual personas in Star Trek’s holodecks. Of course there are also many things that we should be grateful are not replicated in online meetings: conspicuous body odour, badly designed meeting rooms, schedule conflicts, and so on, as well as the unwanted consequences of most of the phenomena above. These, too, are phenomena that the technologies of meetings are designed around.  In-person meetings are incredibly highly-evolved technologies, making use of technological and non-technological phenomena in immensely subtle ways, as well as having layers of counter-technology a kilometre deep, from social mores and manners to Roberts’ rules, from meeting tables to pens and note-taking strategies. Much of the time we don’t even notice that there are any technologies involved at all (as Danny Hillis quipped, ‘technology’ is anything invented after you were born).

Webmeetings, though, also have distinctive phenomena that can be exploited, such as:

  • the ease of entering and leaving (so breaks are easier to take, they don’t need to last a long time, people can dip in and out, etc);
  • the automation of scheduling and note-taking;
  • the means to record all that occurs;
  • the means to directly share digital tools;
  • the fact that people occupy different spaces (often with tools at their disposal that would be unavailable in a shared meeting space);
  • the captions for the hard of hearing;
  • the integrated backchannels of text chat.

These are different kinds of problem space with different adjacent possibles as well as different constraints. It therefore makes no sense to blindly attempt to replicate in-person meetings when the problems and opportunities are so different. We don’t (or shouldn’t) teach online in the same way we teach in the classroom, so why should we try to use meetings in the same way? For that matter, why have meetings at all?

Dealing with the hard stuff

Some constraints are quite easy to specify. If a matter under discussion needs to be kept private, say, that limits the range of options, albeit that, for such a soft technology as a meeting, privacy needs may vary considerably, and what works for one context may fail abysmally for another. Similarly for security, accessibility, learnability, compatibility, interoperability, cost, reliability, maintainability, longevity, and other basic hygiene concerns. There are normally hard constraints defining a baseline, but it is a fuzzy baseline that can be moved in different contexts for different people and different uses. No one wants unreliable, insecure, expensive, incompatible, unusable, buggy, privacy abusing software but most of us nonetheless use Microsoft products.

It is also not completely unreasonable to look for specific known business requirements that need to be met. However, there are enormous risks of duplicating solutions to non-existent problems. It is essential, therefore, to try to find ways of understanding the problems themselves, as much as possible in isolation from existing solutions. It would be a bad requirement to simply specify that people should be able to see and hear one another in real-time, for example: that is a technological solution based on the phenomena that in-person meetings use, not a requirement. It is certainly a very useful phenomenon that might be exploited in any number of ways (we know that because our ancestors have done it since before humans walked the planet) but it tells us little about why the phenomenon matters, or what it is about it that matters.

It would be better, perhaps, to ask people what is wrong with in-person meetings. It still situates the requirements in the current problem space, but it looks more closely at the source rather than the copy. It makes it easier to ask what purposes being able to see and hear one another during in-person meetings serve, what phenomena it provides, on what phenomena (including those provided by other technologies) it depends, and what depends on it. From that we may uncover the business requirements that seeing and hearing other people actually meet. However, it is incredibly tricky to ask such questions in the abstract: the problem space is vast, complex, diverse, and deeply bound up in what we are familiar with, not what is possible.

It might help to make the familiar unfamiliar, for instance, by holding in-person meetings wearing blindfolds, or silently, or to attempt to conduct a meeting using only sticky notes (approaches I have used in my own teaching about communication technologies, as it happens). This kind of exercise forcibly creates a new problem space so that people can wonder about what is lost, what is gained, reasons for doing things, and so on. If you do enough of that, you might start to uncover what matters, and (perhaps) some of the reasons we have meetings in the first place.

Exploring the adjacent possible

Perhaps most importantly, though, soft technologies are not just solutions to problems. Soft technologies are, first and foremost, creators of opportunities, the vast majority of which we will never begin to imagine. Soft technology design is therefore, and must be, a partnership between the person and the technology: it’s not just about creating a tool for a task but about having a conversation with that tool, asking what it can do for us and wondering where it might lead us. What’s interesting about the ubiquitous backchannel feature of webmeetings, for instance, is that it did not find its way into the software as a result of a needs assessment or analysis of business requirements. It was, instead, an early (and deeply imperfect) attempt at replicating what could be replicated of synchronous meetings before multimedia communication became possible. When designing early web conferencing systems, no one said ‘we need a way of typing so that others can see it’. They looked at what could be done and said ‘hey, we can use that’. The functionality persisted and has become nearly ubiquitous because it’s easy to implement and obviously useful. It’s an exaptation, though, not the product of a pre-planned intentional design process. It’s a side-effect of something else we did – a poor solution to an existing problem – that created new phenomena we could co-opt for other purposes. New adjacent possible empty niches emerged from it.

One way to explore such niches would be to give people the chance to play with a wide range of existing ways of addressing the same problem space. A lot of people have turned their attention to these issues, so it makes sense to mine the creativity of the crowd. There are systems like Discord or MatterMost, that represent a different category of hybrid asynchronous/synchronous tool, for instance, blurring the temporal boundaries. There are spatial metaphor systems with isometric interfaces like Spatial, or Ovice, which can allow more intuitive clustering, perhaps contributing to a greater sense of the presence of others, while enabling novel approaches to (say) voting, and so on. There are immersive systems that more literally replicate spaces, like Mozilla Hubs or OpenSim. I hold out little hope for those, but they do have some non-literal features – especially in ways they allow impossible spaces to be created – that are quite interesting. There are instant messengers like Telegram or Signal, that offer ambient awareness as well as conventional meeting support (MS Teams, reflecting its Skype origins, has that too). There are games and game-like environments like Gather or Minecraft, that create new kinds of world as well as providing real-time conferencing features. And there are much smarter webmeeting systems like Around (that largely solves almost all audio problems, that – crucially – can make the meeting a part of a user’s environment rather than a separate space for gathering, that rethinks text chat as a transient, person-focused act rather than a separate text-stream, that makes working together on a digital artefact a richly engaging process, that automatically sends a record to participants, and more).  And there’s a wealth of research-based systems that we have built over the past few decades, including many of my own, that do things differently, or that use different metaphors. Computer-supported collaborative argumentation tools, for instance, or systems that leverage social navigation (I particularly love Viégas’s and Donath’s ChatCircles from the late 1990s, for instance), and so on. They all make new problems, and all have flaws of one kind or another, but thinking about how and why they are different helps to focus on what we are trying to do in the first place.

Perhaps the best of all ways to explore those adjacent possible empty niches is to make them: not to engineer it according to a specification, but to tinker and play. I’ve written about this before (e.g. here and, paywalled, here, summarized by Stefanie Panke here). Tinkering as a research methodology is a process of exploration not of what exists but of what does not. It’s a journey into the adjacent possible, with each new creation or modification creating new adjacent possibles, a step by step means of reaching into and mapping the unknown. We don’t all have the capacity (in skills, time, or patience) to create software from scratch, but we can assemble what we already have. We can, for instance, try to add plugins to existing systems: it is seldom necessary to write your own WordPress plugin, for example, because tens of thousands of people have already done so. Or we can make use of frameworks to construct new systems: the Elgg system underpinning the Landing, for example, does require some expertise to build new components, but a lot can be achieved by assembling and/or modifying what others have built. Or, if standards are followed, we can assemble services as needed: there are standards like xcon, XMPP, Jabber, IRC, and so on that make this possible. And we don’t need to create software or hardware at all in order to dream. Hand-drawn mockups can create new possibilities to explore. Small steps into the unknown are better than no steps at all.

Stop looking for solutions

Webmeetings that attempt to replicate their in-person inspirations are unlikely to ever afford the flexibility of in-person meetings, because they have fewer phenomena to orchestrate and we are never going to be as adept at using them. The gaps they leave for us to fill are smaller, and our capacity to fill those gaps is less well-developed. However, digital systems can provide a great many new and different phenomena that, with creativity and inspiration, may meet our needs much better. Without the constraints of physical spaces we can invent a new physics of the digital. As long as we treat the problem as one of replicating meetings then it makes little difference what we choose: Zoom, Teams, Webex, Connect, BBB, Jitsi, whatever – the feature set may vary, there may be differences in reliability, security, cost, etc but any of them will do the job. The problem is that it is the wrong job. We already pay for and use at least three major systems for synchronous meetings at AU, as well as a bunch of minor ones, and that is nothing like enough. Those that begin to depart from the replication model – Around being my current favourite – are a step in the right direction, while those that double down on it (notably most immersive environments) are probably a step in the wrong direction. It is not about going forward or backward, though: it is about going sideways.

It is not too tricky to experiment in this particular field. For most digital systems we create our decisions normally haunt us for years or decades, because we become locked in to them with our data. Synchronous technologies can, with provisos, be swapped around and changed at will. Sure, there can be issues with recording and transcripts, there can be a training burden, contracts can be expensive and hard to escape, and tech support may be a little more costly but, for the most part, if we don’t like something then we can drop it and try something else. 

I don’t have a solution to choosing or making the right piece of software for AU’s needs, because there isn’t one. There are countless possible solutions, none of which will suit everyone, many of which will provide parts that might be useful to most people, and all of which will have parts or aspects that won’t. But I do know that the way to approach the problem is not to have meetings to determine business requirements. The solution is to find ways of discovering the adjacent possible, to seek inspiration, to look sideways and forwards instead of backwards. We don’t need simple problem-solving for this kind of situation (or rather, it is quite inadequate on its own): we need to find ways to dream, ways to wonder, ways to engage in the act of creation, ways to play.

 

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!

Mediaeval Teaching in the Digital Age (slides from my keynote at Oxford Brookes University, May 26, 2021)

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 front slide, mediaeval teaching

These are the slides from my keynote today at the Oxford Brookes “Theorizing the Virtual” School of Education Research Conference. As theorizing the virtual is pretty much my thing, I was keen to be a part of this! It was an ungodly hour of the day for me (2am kickoff) but it was worth staying up for. It was a great bunch of attendees who really got into the spirit of the thing and kept me wide awake. I wish I could hang around for the rest of it but, on the bright side, at least I’m up at the right time to see the Super Flower Blood Moon (though it’s looking cloudy, darn it).  In this talk I dwelt on a few of the notable differences between online and in-person teaching. This is the abstract…

Pedagogical methods (ways of teaching) are solutions to problems of helping people to learn, in a context filled with economic, physical, temporal, legal, moral, social, political, technological, and organizational constraints. In mediaeval times books were rare and unaffordable, and experts’ time was precious and limited, so lectures were a pragmatic solution, but they in turn created more problems. Counter-technologies such as classes, classrooms, behavioural rules and norms, courses, terms, curricula, timetables and assignment deadlines were were devised to solve those problems, then methods of teaching (pedagogies) were in turn invented to solve problems these counter-technologies caused, notably including:
· people who might not want (or be able) to be there at that time,
· people who were bored and
· people who were confused.
Better pedagogies supported learner needs for autonomy and competence, or helped learners find relevance to their own goals, values, and interests. They exploited physical closeness for support, role-modelling, inspiration, belongingness and so on. However, increasingly many relied on extrinsic motivators, like classroom discipline, grades and credentials to coerce students to learn. Extrinsic motivation achieves compliance, but it makes the reward or avoidance of the punishment the goal, persistently and often permanently crowding out intrinsic motivation. Intelligent students respond with instrumental approaches, satisficing, or cheating. Learning seldom persists; love of the subject is subdued; learners learn to learn in ineffective ways. More layers of counter-technologies are needed to limit the damage, and so it goes on.
Online, the constraints are very different, and its native forms are the motivational inverse of in-person learning. An online teacher cannot control every moment of a learner’s time, and learners can use the freedoms they gain to take the time they need, when they need it, to learn and to reflect, without the constraints of scheduled classroom hours and deadlines. However, more effort is usually needed to support their needs for relatedness. Unfortunately, many online teachers try (or are required) to re-establish the control they had in the classroom through grading or the promise of credentials, recreating the mediaeval problems that would otherwise not exist, using tools like learning management systems that were designed (poorly) to replicate in-person teaching functions. These are solutions to the problems caused by counter-technologies, not to problems of learning.
There are better ways, and that’s what this session is about.

front slide, mediaeval teaching

Educational technology: what it is and how it works | AI & Society

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https://rdcu.be/ch1tl

This is a link to my latest paper in the journal AI & Society. You can read it in a web browser from there, but it is not directly downloadable. A preprint of the submitted version (some small differences and uncorrected errors here and there, notably in citations) can be downloaded from https://auspace.athabascau.ca/handle/2149/3653. The published version should be downloadable for free by Researchgate members.

This is a long paper (about 10,000 words), that summarizes some of the central elements of the theoretical model of learning, teaching and technology developed in my recently submitted book (still awaiting review) and that gives a few examples of its application. For instance, it explains:

  • why, on average researchers find no significant difference between learning with and without tech.
  • why learning styles theories are a) inherently unprovable, b) not important even if they were, and c) a really bad idea in any case.
  • why bad teaching sometimes works (and, conversely, why good teaching sometimes fails)
  • why replication studies cannot be done for most educational interventions (and, for the small subset that are susceptible to reductive study, all you can prove is that your technology works as intended, not whether it does anything useful).

Abstract

This theoretical paper elucidates the nature of educational technology and, in the process, sheds light on a number of phenomena in educational systems, from the no-significant-difference phenomenon to the singular lack of replication in studies of educational technologies.  Its central thesis is that we are not just users of technologies but coparticipants in them. Our participant roles may range from pressing power switches to designing digital learning systems to performing calculations in our heads. Some technologies may demand our participation only in order to enact fixed, predesigned orchestrations correctly. Other technologies leave gaps that we can or must fill with novel orchestrations, that we may perform more or less well. Most are a mix of the two, and the mix varies according to context, participant, and use. This participative orchestration is highly distributed: in educational systems, coparticipants include the learner, the teacher, and many others, from textbook authors to LMS programmers, as well as the tools and methods they use and create.  From this perspective,  all learners and teachers are educational technologists. The technologies of education are seen to be deeply, fundamentally, and irreducibly human, complex, situated and social in their constitution, their form, and their purpose, and as ungeneralizable in their effects as the choice of paintbrush is to the production of great art.

Originally posted at: https://landing.athabascau.ca/bookmarks/view/8692242/my-latest-paper-educational-technology-what-it-is-and-how-it-works

Are experienced online teachers best-placed to help in-person teachers cope with suddenly having to teach online? Maybe not.

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lecturingI recently downloaded What Teacher Educators Should Have Learned From 2020. This is an open edited book, freely downloadable from the AACE site, for teachers of teachers whose lives were disrupted by the sudden move to emergency remote teaching over the past year or so.  I’ve only skimmed the contents and read a couple of the chapters, but my first impressions are positive. Edited by Richard Ferdig and Kristine Pytash, It springs from the very active and engaged AACE SITE community, which is a good indicator of expertise and experience. It seems well organized into three main sections:

  1.         Social and Emotional Learning for Teacher Education.
  2.         Online Teaching and Learning for Teacher Education.
  3.         eXtended Reality (XR) for Teacher Education

I like the up-front emphasis on social and emotional aspects, addressing things like belongingness, compassion, and community, mainly from theoretical/model-oriented perspectives, and the other sections seem wisely chosen to meet practitioner needs. The chapters adopt a standardized structure:

  • Introduction. 
  • What We Know. 
  • Lessons Learned for Research. 
  • Lessons Learned for Practice. 
  • What You Should Read. 
  • References

Again, this seems pretty sensible, maintaining a good focus on actionable knowledge and practical steps to be taken. It’s not quite a textbook, but it’s a useful teach-yourself resource with good coverage. I look forward to dipping into it a bit more deeply. I expect to find some good ideas, good practices, and good theoretical models to support my teaching and my understanding of the issues. And I’m really pleased that it is being released as an open publication: well done, AACE, for making this openly available.

But I do wonder a little about who else will read this.

Comfort zones and uncomfortable zones

The other day I was chatting with a neighbour who teaches a traditional hard science subject at one of the local universities, who was venting about the problems of teaching via Zoom. He knew that I had a bit of interest and experience in this area, so he asked whether I had any advice. I started to suggest some ways of rethinking it as a pedagogical opportunity, but he was not impressed. Even something as low-threshold and straightforward as flipping the classroom or focusing on what students do rather than what he has to tell them was a step too far. He patiently explained that he has classes with hundreds of students and fixed topics that they need to learn, and he really didn’t see it as desirable or even possible to depart from his well-tried lecture format. At least it would be too much work and he didn’t have the time for it. I did try to push back on that a bit and I may have mentioned the overwhelming body of research that suggests this might not be a wise move, but he was pretty clear and firm about this.  What he actually wanted was for someone to make (or tell him how to make) the digital technology as easy and as comfortably familiar as the lecture theatre, and that would somehow make the students as engaged as he perceived them to normally be in his lectures, without notably changing how he taught. The problem was the darn technology, not the teaching. I bit my tongue at this point. I eventually came up with a platitude or two about trying to find different ways to make learning visible, about explicitly showing that he cares, about taking time to listen, about modelling the behaviour he wanted to see, about using the chat to good advantage, and about how motivation differs online and off, but I don’t think it helped. I suspect that the only things that really resonated with him were suggestions about how to get the most out of a webcam and a recommendation to get a better microphone.

Within the context in which he usually teaches, he is probably a very good teacher. He’s a likeable person who clearly cares a lot about his students, he knows a lot about his subject, and he knows how to make it appealing within the situation that he normally works. His courses, as he described them, are very conventional, relying a lot on the structure given to them by the industry-driven curriculum and the university’s processes, norms, and structures, and he fills his role in all that admirably. I think he is pretty typical of the vast majority of teachers. They’re good at what they do, comfortable with how they do it, and they just want the technology to accommodate them continuing to do so without unnecessary obstacles.

Unfortunately, technology doesn’t work that way.

The main reason it doesn’t work is very simple: technologies (including pedagogies) affect one another in complex and recursive ways, so (with some trivial exceptions) you can’t change one element (especially a large element) and expect the rest to work as they did before.  It’s simple, intuitive, and obvious but unless you are already well immersed in both systems theories and educational theory, really taking it to heart and understanding how it must affect your practice demands a pretty big shift in weltanschauung, which is not the kind of thing I was keen to start while on my way to the store in the midst of a busy day.

To make matters worse, even if teachers do acknowledge the need to change, their assumption that things will eventually (maybe soon) return to normal means that they are – reasonably enough –  not willing and probably not able to invest a lot of time into it. A big part of the reason for this is that, thanks to the aforementioned interdependencies, they are probably running round like blue-arsed flies just trying to keep things together, and filling their time with fixing the things that inevitably break in the process. Systems thrive on this kind of self-healing feedback loop. I guess teachers figure that, if they can work out how to tread water until the pandemic has run its course, it will be OK in the end.

If only.

Why in-person education works

The hallmark technologies (mandatory lectures, assignments, grades, exams, etc, etc) of in-person teaching are worse than awful but, just as a talented musician can make beautiful noises with limited technical knowledge and sub-standard instruments, so there are countless teachers who use atrocious methods in dreadful contexts but who successfully lead their students to learn. As long as the technologies are soft and flexible enough to allow them to paper over the cracks of bad tools and methods with good technique, talent, and passion, it works well enough for enough people enough of the time and can (with enough talent and passion) even be inspiring.

It would not work at all, though, without the massive machinery that surrounds it.

An institution (including its systems, structures, and tools) is itself designed to teach, no matter how bad the teachers are within it. The opportunities for students to learn from and with others around them, including other students, professors, support staff, administrators, and so on; the supporting technologies, including rules, physical spaces, structures, furnishings, and tools; the common rooms, the hallways, the smokers’ areas (best classrooms ever), the lecture theatres, the bars and the coffee shops; the timetables that make students physically travel to a location together (and thus massively increase salience); the notices on the walls; the clubs and societies; the librarians, the libraries, the students reading and writing within those libraries, echoing and amplifying the culture of learning that pervades them; the student dorms and shared kitchens where even more learning happens; the parties; even the awful extrinsic motivation of grades, teacher power, and norms and rules of behaviour that emerged in the first place due to the profound motivational shortcomings of in-person teaching. All of this and more conspires to support a basic level of at least mediocre (but good enough) learning, whether or not teachers teach well. It’s a massively distributed technology enacted by many coparticipants, of which designated teachers are just a part, and in which students are the lead actors among a cast of thousands. Online, those thousands are often largely invisible. At best, their presence tends to be highly filtered, channeled, or muted.

Why in-person methods don’t transfer well online

When most of that massive complex machinery is suddenly removed, leaving nothing but a generic interface better suited to remote business meetings than learning or, much worse, some awful approximation of all the evil, hard, disempowering technologies of traditional teaching wrapped around Zoom, or nightmarishly inhuman online proctoring systems, much of the teaching (in the broadest sense) disappears with it. Teaching in an institution is not just what teachers do. It’s the work of a community; of all the structures the community creates and uses; of the written and unwritten rules; of the tacit knowledge imparted by engagement in a space made for learning; of the massive preparation of schooling and the intricate loops that connect it with the rest of society; of attitudes and cultures that are shaped and reinforced by all the rest.  It’s no wonder that teachers attempting to transfer small (but the most visible) parts of that technology online struggle with it. They need to fill the ever-widening gaps left when most of the comfortable support structures of in-person institutions that made it possible in the first place are either gone or mutated into something lean and hungry. It can be done, but it is really hard work.

More abstractly, a big part of the problem with this transfer-what-used-to-work-in-person approach is that it is a technology-first approach to the problem that focuses on one technology rather than the whole. The technology of choice in this case happens to be a set of pedagogical methods, but it is no different in principle than picking a digital tool and letting that decide how you will teach. Neither makes much sense. All the technologies in the assembly – including pedagogies, digital tools, regulations, designs, and structures – have to work together. No single technology has precedence, beyond the one that results from assembling the rest. To make matters worse, what-used-to-work-in-person pedagogies were situated solutions to the problems of teaching in physical classrooms, not universally applicable methods of teaching. Though there are some similarities here and there, the problems of teaching online are not at all the same as those of in-person teaching so of course the solutions are different. Simply transferring in-person pedagogies to an online context is much like using the paddles from a kayak to power a bicycle. You might move, but you won’t move far, you won’t move fast, you won’t move where you want to go, and it is quite likely to end in injury to yourself or others.

Such problems have, to a large extent, been adequately solved by teachers and institutions that work primarily online. Online institutions and organizations have infrastructure, processes, rules, tools, cultures, and norms that have evolved to work together, starting with the baseline assumption that little or none of the physical stuff will ever be available. Anything that didn’t work never made it to first base, or has not survived. Those that have been around a while might not be perfect, but they have ironed out most of the kinks and filled in most of the gaps. Most of my work, and that of my smarter peers, begins in this different context. In fact, in my case, it mainly involves savagely critiquing that context and figuring out ways to improve it, so it is yet another step removed from where in-person teachers are now.

OK, maybe I could offer a little advice or, at least, a metaphor

Roughly 20 years ago I did share a similar context. Working in an in-person university, I had to lead a team of novice online teachers from geographically dispersed colleges to create and teach a blended program with 28 new online courses. We built the whole thing in 6 months from start to finish, including the formal evaluations and approvals process. I could share some generic lessons from what I discovered then, the main one being to put most of the effort into learning to teach online, not into designing course materials. Put dialogue and community first, not structure. For instance, make the first thing students see in the LMS the discussion, not your notes or slides, and use the discussion to share content and guide the process. However, I’d mostly feel like the driver of a Model T Ford trying to teach someone to drive a Tesla. Technologies have changed, I have changed, my memory is unreliable.

bicycleIn fact, I haven’t driven a car of any description in years. What I normally do now is, metaphorically, much closer to riding a bicycle, which I happen to do and enjoy a lot in real life too. A bike is a really smart, well-adapted, appropriate, versatile, maintainable, sustainable soft technology for getting around. The journey tends to be much more healthy and enjoyable, traffic jams don’t bother you, you can go all sorts of places cars cannot reach, and you can much more easily stop wherever you like along the way to explore what interests you. You can pretty much guarantee that you will arrive when and where you planned to arrive, give or take a few minutes. In the city, it’s often the fastest way to get around, once you factor in parking etc. It’s very liberating. It is true that more effort is needed to get from A to B, bad weather can be a pain, and it would not be the fastest or most comfortable way to reach the other side of the continent: sometimes, alternative forms of transport are definitely worth taking and I’m not against them when it’s appropriate to use them. And the bike I normally ride does have a little electric motor in one of the wheels that helps push me up hills (not much, but enough) but it doesn’t interfere with the joy (or most of the effort) of riding.  I have learned that low-threshold, adaptable, resilient systems are often much smarter in many ways than high-tech platforms because they are part-human. They can take on your own smartness and creativity in ways no amount of automation can match. This is true of online learning tools as much as it is true of bicycles. Blogs, wikis, email, discussion forums, and so on often beat the pants off learning management systems, commercial teaching platforms, learning analytics tools or AI chatbots for many advanced pedagogical methods because they can become what you want them to be, rather than what the designer thought you wanted, and they can go anywhere, without constraint. Of course, the flip side is that they take more effort, sometimes take more time, and (without enormous care) can make it harder for all concerned to do things that are automated and streamlined in more highly engineered tools, so they might not always be the best option in all circumstances, any more than a bike is the best way to get up a snowy mountain or to cross an ocean.

Why you shouldn’t listen to my advice

It’s sad but true that most of what I would really like to say on the subject of online learning won’t help teachers on the ground right now, and it is actually worse than the help their peers could give them because what I really want to tell them is to change everything and to see the world completely differently. That’s pretty threatening, especially in these already vulnerable times, and not much use if you have a class to teach tomorrow morning.

The AACE book is more grounded in where in-person teachers are now. The chapter “We Need to Help Teachers Withstand Public Criticism as They Learn to Teach Online”, for example, delves into the issues well, in accessible ways that derive from a clear understanding of the context.  However, the book cannot help but be an implicit (and, often, explicit) critique of how teachers currently teach: that’s implied in the title, and in the chapter structures.  If you’re already interested enough in the subject and willing enough to change how you teach that you are reading this book in the first place, then this is great. You are 90% of the way there already, and you are ready to learn those lessons. One of the positive sides of emergency remote teaching has been that it has encouraged some teachers to reflect on their teaching practices and purposes, in ways that will probably continue to be beneficial if and when they return to in-person teaching. They will enjoy this book, and they may be the intended audience. But they are not the ones that really need it.

I would quite like to see (though maybe not to read) a different kind of book containing advice from beginners. Maybe it would have a title something like ‘What I learned in 2020’ or ‘How I survived Zoom.’ Emergency remote teachers might be more inclined to listen to the people who didn’t know the ‘right’ ways of doing things when the crisis began, who really didn’t want to change, who maybe resented the imposition, but who found ways to work through it from where they were then, rather than where the experts think (or know) they should be aiming now. It would no doubt annoy me and other distance learning researchers because, from the perspective of recognized good practice, much of it would probably be terrible but, unlike what we have to offer, it would actually be useful. A few chapters in the AACE book are grounded in concrete experience of this nature, but even they wind up saying what should have happened, framing the solutions in the existing discourse of the distance learning discipline. Most chapters consist of advice from experts who already knew the answers before the pandemic started. It is telling that the word ‘should’ occurs a lot more frequently than it should. This is not a criticism of the authors or editors of the book: the book is clear from the start that it is going to be a critique of current practice and a practical guidebook to the territory, and most of the advice I’ve seen in it so far makes a lot of sense. It’s just not likely to affect many of the ones who have no wish to change not just their practices but their fundamental attitudes to teaching. Sadly, that’s also true of this post which, I think, is therefore more of an explanation of why I’ve been staring into the headlights for most of the pandemic, rather than a serious attempt to help those in need. I hope there’s some value in that because it feels weird to be a (slight, minor, still-learning) expert in the field with very strong opinions about how online learning should work, but to have nothing useful to say on the subject at the one time it ought to have the most impact.

Read the book:

Ferdig, R.E. & Pytash, K.E. (2021). What Teacher Educators Should Have Learned From 2020. Association for the Advancement of Computing in Education (AACE). Retrieved March 22, 2021 from https://www.learntechlib.org/primary/p/219088/.

Turns out the STEM ‘gender gap’ isn’t a gap at all

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Grace Hopper and Univac, image from en.wikipedia.org/wiki/Grace_HopperAt least in Ontario, it seems that there are about as many women as men taking STEM programs at undergraduate level. This represents a smaller percentage of women taking STEM subjects overall because there are way more women entering university in the first place. A more interesting reading of this, therefore, is not that we have a problem attracting women to science, technology, engineering, and mathematics, but that we have a problem attracting men to the humanities, social sciences, and the liberal arts. As the article puts it:

“it’s not that women aren’t interested in STEM; it’s that men aren’t interested in poetry—or languages or philosophy or art or all the other non-STEM subjects.”

That’s a serious problem.

As someone with qualifications in both (incredibly broad) areas, and interests in many sub-areas of each,  I find the arbitrary separation between them to be ludicrous, leading to no end of idiocy at both extremes, and little opportunity for cross-fertilization in the middle. It bothers me greatly that technology subjects like computing or architecture should be bundled with sciences like biology or physics, but not with social sciences or arts, which are way more relevant and appropriate to the activities of most computer professionals. In fact, it bothers me that we feel the need to separate out large fields like this at all. Everyone plays lip service to cross-disciplinary work but, when we try to take that seriously and cross the big boundaries, there is so much polarization between the science and arts communities that they usually don’t even understand one another, let alone work in harmony. We don’t just need more men in the liberal arts – we need more scientists, engineers, and technologists to cross those boundaries, whatever their gender. And, vice versa, we need more liberal artists (that sounds odd, but I have no better term) and social scientists in the sciences and, especially, in technology.

But it’s also a problem of category errors in the other direction. This clumping together of the whole of STEM conceals the fact that in some subjects – computing, say – there actually is a massive gender imbalance (including in Ontario), no matter how you mess with the statistics. This is what happens when you try to use averages to talk about specifics: it conceals far more than it reveals.

I wish I knew how to change that imbalance in my own designated field of computing, an area that I deliberately chose precisely because it cuts across almost every other field and did not limit me to doing one kind of thing. I do arts, science, social science, humanities, and more, thanks to working with machines that cross virtually every boundary.

I suspect that fixing the problem has little to do with marketing our programs better, nor with any such surface efforts that focus on the symptoms rather than the cause. A better solution is to accept and to celebrate the fact that the field of computing is much broader and vastly more interesting than the tiny subset of it that can be described as computer science, and to build up from there. It’s especially annoying that the problem exists at Athabasca where a wise decision was made long ago not to offer a computer science program. We have computing and information systems programs, but not any programs in computer science. Unfortunately, thanks to a combination of lazy media and computing profs (suffering from science envy) that promulgate the nonsense, even good friends of mine that should know better sometimes describe me as a computer scientist (I am emphatically not), and even some of our own staff think of what we do as computer science. To change that perception means not just a change in nomenclature, but a change in how and what we, at least in Athabasca, teach. For example, we might mindfully adopt an approach that contextualizes computing around projects and applications, rather than its theory and mechanics. We might design a program that doesn’t just lump together a bunch of disconnected courses and call it a minor but that, in each course (if courses are even needed), actively crosses boundaries – to see how code relates to poetry, how art can inform and be informed by software, how understanding how people behave can be used in designing better systems, how learning is changed by the tools we create, and so on.

We don’t need disciplines any more, especially not in a technology field. We need connections. We don’t need to change our image. We need to change our reality. I’m finding that to be quite a difficult challenge right now.

 

Address of the bookmark: http://windsorstar.com/opinion/william-watson-turns-out-the-stem-gender-gap-isnt-a-gap-at-all/wcm/ee4217ec-be76-4b72-b056-38a7981348f2

Originally posted at: https://landing.athabascau.ca/bookmarks/view/2929581/turns-out-the-stem-%E2%80%98gender-gap%E2%80%99-isn%E2%80%99t-a-gap-at-all