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

Challenges of the Physical: slides from my keynote at XII Conferência Internacional de Tecnologias de Informação e Comunicação na Educação, September 2021

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Here are the slides from my opening keynote today for the XII Conferência Internacional de Tecnologias de Informação e Comunicação na Educação in Portugal. first slide of the presentation

The conference theme was ‘challenges of the digital’ so I thought it might be fun to reverse the problem, and to think instead about the challenges of in-person education. In this presentation I imagined a world in which in-person teaching had never been invented, and presented a case for doing so. In fairness, it was not a very good case! But I did have fun using some of the more exotic voice changing features of my Voicelive Play vocal processor (which I normally use for performing music), presenting some of the arguments against my suggestions in different voices using a much better mic than my usual (pretty good) Blue Yeti. I might not use the special effects again that often, but I was quite impressed with the difference the better microphone made.

My central points (mostly implicit until the end) were:

  • That the biggest challenge of the digital is all the baggage that we have inherited from in-person teaching, and our continuing need to interoperate with in-person institutions.
  • That pedagogies are neither universal nor neutral. They are solutions to problems of learning in a particular context, in assembly with countless constraints and possibilities provided by that context: people, tools, structures, methods, systems, and so on.
  • That solutions to learning in a physical context – at least in the one-to-many model of traditional education systems – inevitably lead to a very strong power imbalance between teacher and learner, where the teacher is in control of every moment that the teaching event occurs. This has many repercussions, not least of which being that needs for autonomy and competence support are very poorly addressed (though relatedness comes for free), so it is really bad for intrinsic motivation.
  • Thus, the pedagogies of physical spaces have to compensate for the loss of control and achievable challenge that they naturally entail.
  • That the most common approach – and, again, an almost inevitable (i.e. the shortest path) follow-on from teaching a lot of people at once – involves rewards and punishments, that massively impair or destroy intrinsic motivation to learn and, in most cases, actively militate against effective learning.
  • That the affordances of teaching everyone the same thing at once lead fairly naturally to credentials for having learned it, often achieved in ‘efficient’ ways like proctored exams that are incredibly bad for learning, and that greatly reinforce the extrinsic motivation that is already highly problematic in the in-person modality. The credentials, not the learning, become the primary focus.
  • That support for autonomy and competence are naturally high in online learning, though support for relatedness is a mix of good and bad. There is no need for teachers being in control and, lacking most of the means of control available to in-person teachers, the only reliable way to regain it is through rewards and punishments which, as previously mentioned, are fatal to intrinsic motivation.
  • That the almost ubiquitous ways that distance educators inherit and use the pedagogies, methods, and structures of in-person learning – especially in the use of coercion through rewards and punishments (grades, credentials, etc) but also in schedules, fixed-length courses, inflexible learning outcomes, etc – are almost exactly the opposite of what its technologies can best support.

Towards the end, acknowledging that it is difficult to change such complex and deeply entangled systems (much though it is to be desired) I presented some ways of reducing the challenges of the physical in online teaching, and regaining that lost intrinsic motivation, that I summarized thus:

  • Let go (you cannot and should not control learning unless asked to do so), but stay close;
  • Make learning (not just its products) visible (and, in the process, better understand your teaching);
  • Make learning shared (cooperation and, where possible, collaboration built in from the ground up);
  • Don’t ever coerce (especially not through grades);
  • Care (for learners, for learning, for the subject).

It’s a theme that I have spoken and written of many, many times, but (apart from the last few slides) the way I presented it this time was new for me. I had fun pretending to be different people, and the audience seemed to like it, in a challenging kind of a way. There were some great questions at the end, not all of which I had time to answer, though I’m happy to continue the conversation here, or via Twitter.

Why do we work from home but learn remotely?

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I am slowly getting used to the ugly abbreviation WFH that has emerged during the pandemic, though I don’t much like it because it’s not always accurate. Even in pandemic times I often work from my boat (WFB). In non-pandemic times I’ve worked from a tent (WFT), a library (WFL), a hotel room (WFHR), a park bench (WFPB), a conference (WFC), a plane (WFP), a bus (WF… OK, you get the picture), and much, much more. I have even worked at Athabasca University’s own buildings (Working from Work?) on rare occasions. But why do most of us in the trade so rarely use terms like learning from home when working from home (WFH) is so ubiquitous?

Terms like e-learning, online learning, distance learning, remote learning, and so on, are weird. Learning is never remote, electronic, online, or at a distance.  There is more sense to terms like distance education, online education, remote teaching, and so on, because education and teaching describe relationships between people, and there are different ways that those relationships can be mediated, that do (or should) deeply affect the process. There is also a whole slew of intentional and implicit structures, systems, methods, and toolsets that are assumed when we prefix education with terms like distance or online. But why online or distance learning?

As teachers we are (rightly) taught that it’s not about the teaching, it’s about the learning. For at least the last 30 years or more we have, for instance, therefore been strongly encouraged to use the term ‘learning & teaching’ instead of ‘teaching & learning’ because learning must come first. I’ve corrected people myself for getting the order wrong, many times. Charitably, therefore, it might be that we are trying to draw attention to the fact that it’s about learning. But, if so, why distance or online?

Ricardo Liberato, CC BY-SA 2.0 via Wikimedia Commons I think something nasty has happened to the term ‘learning’ when it is used this way, because I think that what we actually mean by it is ‘teaching’.  Some British English dialects take that dubious elision fully on board. When something nasty happens to someone as a consequence of something they have done that is perceived to be wrong, or even when some punishment is inflicted on them by someone else, it is common in some circles to say ‘that’ll learn yer’ (the ‘yer’ is important – don’t imagine the Queen saying in received pronunciation ‘that will learn you’ because it would be wrong). When I hear the phrase I imagine it being said with a snarl. It’s a cruel thing to say, though it can be used kind-of humorously, at least if, as many of my compatriots do, you appreciate a particularly crude form of Benny-Hillish shadenfreude (‘Ha ha, you fell flat on your face and hurt yourself. That’ll learn yer’).

Outside a subset of British and perhaps some other minor English vernaculars, learning is never something that we do to people. It’s something done by people, with what and with whom is around them (and that might include a teaching website, textbook, or course pack). So let’s stop calling people distance or online learners because it devalues and obscures what they are actually doing. They are not being learned at. They are being taught at a distance, and learning from home (or wherever they happen to be).

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/.

How distance changes everything: slides from my keynote at the University of Ottawa

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These are the slides from my keynote at the University of Ottawa’s “Scaffolding a Transformative Transition to Distance and Online Learning” symposium today. In the presentation I discussed why distance learning really is different from in-person learning, focusing primarily on the fact that they are the motivational inverse of one another. In-person teaching methods evolved in response to the particular constraints and boundaries imposed by physics, and consist of many inventions – pedagogical and otherwise – that are counter-technologies designed to cope with the consequences of teaching in a classroom, a lot of which are not altogether wise. Many of those constraints do not exist online, and yet we continue to do very similar things, especially those that control and dictate what students should do, as well as when, and how they should do it. This makes no sense, and is actually antagonistic to the natural flow of online learning. I provided a few simple ideas and prompts for thinking about how to go more with the flow.

The presentation was only 20 minutes of a lively and inspiring hour-long session, which was fantastic fun and provided me with many interesting questions and a chance to expand further on the ideas.

uottawa2020HowDistanceChangesEverything

Beyond learning outcomes

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

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

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

I frame this in terms of the relationships between:

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

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

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

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

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

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

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

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

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

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

DT&L2018 spotlight presentation: The Teaching Gestalt

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The teaching gestalt  presentation slides (PDF, 9MB)

This is my Spotlight Session from the 34th Distance Teaching & Learning Conference, at Wisconsin Madison, August 8th, 2018. Appropriately enough, I did this online and at a distance thanks to my ineptitude at dealing with the bureaucracy of immigration. Unfortunately my audio died as we moved to the Q&A session so, if anyone who was there (or anyone else) has any questions or observations, do please post them here! Comments are moderated.

The talk was concerned with how online learning is fundamentally different from in-person learning, and what that means for how (or even whether) we teach, in the traditional formal sense of the word.

Teaching is always a gestalt process, an emergent consequence of the actions of many teachers, including most notably the learners themselves, which is always greater than (and notably different from) the sum of its parts. This deeply distributed process is often masked by the inevitable (thanks to physics in traditional classrooms) dominance of an individual teacher in the process. Online, the mask falls off. Learners invariably have both far greater control and far more connection with the distributed gestalt. This is great, unless institutional teachers fight against it with rewards and punishments, in a pointless and counter-productive effort to try to sustain the level of control that is almost effortlessly attained by traditional in-person teachers, and that is purely a consequence of solving problems caused by physical classroom needs, not of the needs of learners. I describe some of the ways that we deal with the inherent weaknesses of in-person teaching especially relating to autonomy and competence support, and observe how such pedagogical methods are a solution to problems caused by the contingent side effects of in person teaching, not to learning in general.

The talk concludes with some broad characterization of what is different when teachers choose to let go of that control.  I observe that what might have been Leonardo da Vinci’s greatest creation was his effective learning process, without which none of the rest of his creations could have happened. I am hopeful that now, thanks to the connected world that we live in, we can all learn like Leonardo, if and only if teachers can learn to let go.

Evidence mounts that laptops are terrible for students at lectures. So what?

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The Verge reports on a variety of studies that show taking notes with laptops during lectures results in decreased learning when compared with notes taken using pen and paper. This tells me three things, none of which is what the article is aiming to tell me:

  1. That the institutions are teaching very badly. Countless decades of far better evidence than that provided in these studies shows that giving lectures with the intent of imparting information like this is close to being the worst way to teach. Don’t blame the students for poor note taking, blame the institutions for poor teaching. Students should not be put in such an awful situation (nor should teachers, for that matter). If students have to take notes in your lectures then you are doing it wrong.
  2. That the students are not skillful laptop notetakers. These studies do not imply that laptops are bad for notetaking, any more than giving students violins that they cannot play implies that violins are bad for making music. It ain’t what you do, it’s the way that you do it. If their classes depend on effective notetaking then teachers should be teaching students how to do it. But, of course, most of them probably never learned to do it well themselves (at least using laptops). It becomes a vicious circle.
  3. That laptop and, especially, software designers have a long way to go before their machines disappear into the background like a pencil and paper. This may be inherent in the medium, inasmuch as a) they are vastly more complex toolsets with much more to learn about, and b) interfaces and apps constantly evolve so, as soon as people have figured out one of them, everything changes under their feet. It becomes a vicious cycle.

The extra cognitive load involved in manipulating a laptop app (and stopping the distractions that manufacturers seem intent on providing even if you have the self-discipline to avoid proactively seeking them yourself) can be a hindrance unless you are proficient to the point that it becomes an unconscious behaviour. Few of us are. Tablets are a better bet, for now, though they too are becoming overburdened with unsought complexity and unwanted distractions. I have for a couple of years now been taking most of my notes at conferences etc with an Apple Pencil and an iPad Pro, because I like the notetaking flexibility, the simplicity, the lack of distraction (albeit that I have to actively manage that), and the tactile sensation of drawing and doodling. All of that likely contributes to making it easier to remember stuff that I want to remember. The main downside is that, though I still gain laptop-like benefits of everything being in one place, of digital permanence, and of it being distributed to all my devices, I have, in the process, lost a bit in terms of searchability and reusability. I may regret it in future, too, because graphic formats tend to be less persistent over decades than text. On the bright side, using a tablet, I am not stuck in one app. If I want to remember a paper or URL (which is most of what I normally want to remember other than my own ideas and connections that are sparked by the speaker) I tend to look it up immediately and save it to Pocket so that I can return to it later, and I do still make use of a simple notepad for things I know I will need later. Horses for courses, and you get a lot more of both with a tablet than you do with a pencil and paper. And, of course, I can still use pen and paper if I want a throwaway single-use record – conference programs can be useful for that.

 

 

 

 

Address of the bookmark: https://www.theverge.com/2017/11/27/16703904/laptop-learning-lecture

Originally posted at: https://landing.athabascau.ca/bookmarks/view/2871283/evidence-mounts-that-laptops-are-terrible-for-students-at-lectures-so-what