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

 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

My latest paper – Educational technology: what it is and how it works

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

EdTech Books

This is a great, well presented and nicely curated selection of open books on education and educational technology, ranging from classics (and compilations of chapters by classic authors) to modern guides, textbooks, and blog compilations, covering everything from learning theory to choice of LMS. Some are peer-reviewed, there’s a mix of licences from PD to restrictive CC , and there’s good guidance provided about the type and quality of content. There’s also support for collaboration and publication. All books are readable online, most can be downloaded as (at least) PDF. I think the main target audience is students of education/online learning, and practitioners – at least, there’s a strong practical focus.

Originally posted at: https://landing.athabascau.ca/bookmarks/view/7161867/edtech-books (where you can find some really interesting comments, including the one that my automated syndicator mistakenly turned into the main post the first time it ran)

Skills lost due to COVID-19 school closures will hit economic output for generations (hmmm)

Snippet from OECD report on covid-19 and education This CBC report is one of many dozens of articles in the world’s press highlighting one rather small but startling assertion in a recent OECD report on the effects of Covid-19 on education – that the ‘lost’ third of a year of schooling in many countries will lead to an overall lasting drop in GDP of 1.5% across the world. Though it contains many more fascinating and useful insights that are far more significant and helpful, the report itself does make this assertion quite early on and repeats it for good measure, so it is not surprising that journalists have jumped on it. It is important to observe, though, that the reasoning behind it is based on a model developed by Hanushek and Woessman over several years, and an unpublished article by the authors that tries to explain variations in global productivity according to amount and  – far more importantly – the quality of education: that long-run productivity is a direct consequence of the cognitive skills (or knowledge capital) of a nation, that can be mapped directly to how well and how much the population is educated.

As an educator I find this model, at a glance, to be reassuring and confirmatory because it suggests that we do actually have a positive effect on our students. However, there may be a few grounds on which it might be challenged (disclaimer: this is speculation). The first and most obvious is that correlation does not equal causation. The fact that countries that do invest in improving education consistently see productivity gains to match in years to come is interesting, but it raises the question of what led to that investment in the first place and whether that might be the ultimate cause, not the education itself.  A country that has invested in increasing the quality of education would, normally, be doing so as a result of values and circumstances that may lead to other consequences and/or be enabled by other things (such as rising prosperity, competition from elsewhere, a shift to more liberal values, and so on).  The second objection might be that, sure, increased quality of education does lead to greater productivity, but that it is not the educational process that is causing it, as such. Perhaps, for instance, an increased focus on attainment raises aspirations. A further objection might be that the definition of ‘quality’ does not measure what they think it measures. A brief skim of the model used suggests that it makes extensive use of scores from the likes of TIMSS, PIRLS and PISA, standardized test approaches used to compare educational ‘effectiveness’ in different regions that embody quite a lot of biases, are often manipulated at a governmental level, and that, as I have mentioned once or twice before, are extremely dubious indicators of learning: in fact, even when they are not manipulated, they may indicate willingness to comply with the demands of the powerful more than learning (does that improve GDP? Probably).  Another objection might be that absence of time spent in school does not equate to absence of education. Indeed, Hanushek and Woessman’s central thesis is that it is not the amount but the quality of schooling that matters, so it seems bizarre that they might fall back on quantifying learning by time spent in school. We know for sure that, though students may not have been conforming to curricula at the rate desired by schools and colleges, they have not stopped learning. In fact, in many ways and in many places, there are grounds to believe that there have been positive learning benefits: better family learning, more autonomy, more thoughtful pedagogies, more intentional learning community forming, and so on.  Out of this may spring a renewed focus on how people learn and how best to support them, rather than maintaining a system that evolved in mediaeval times to support very different learning needs, and that is so solidly packed with counter technologies and so embedded in so many other systems that have nothing to do with learning that we have lost sight of the ones that actually matter. If education improves as a result, then (if it is true that better and more education improves the bottom line) we may even see gains in GDP. I expect that there are other reasons for doubt: I have only skimmed the surface of the possible concerns.

I may be wrong to be sceptical –  in fairness, I have not read the many papers and books produced by Hanushek and Woessman on the subject, I am not an economist, nor do I have sufficient expertise (or interest) to analyze the regression model that they use. Perhaps they have fully addressed such concerns in that unpublished paper and the simplistic cause-effect prediction distorts their claims. But, knowing a little about complex adaptive systems, my main objection is that this is an entirely new context to which models that have worked before may no longer apply and that, even if they do, there are countless other factors that will affect the outcome in both positive and negative ways, so this is not so much a prediction as an observation about one small part of a small part of a much bigger emergent change that is quite unpredictable. I am extremely cautious at the best of times whenever I see people attempting to find simple causal linear relationships of this nature, especially when they are so precisely quantified, especially when past indicators are applied to something wholly novel that we have never seen before with such widespread effects, especially given the complex relationships at every level, from individual to national.  I’m glad they are telling the story – it is an interesting one that no doubt contains grains of important truths – but it is just an informative story, not predictive science.  The OECD has a bit of track record on this kind of misinterpretation, especially in education. This is the same organization that (laughably, if it weren’t so influential) claimed that educational technology in the classroom is bad for learning. There’s not a problem with the data collection or analysis, as such. The problem is with the predictions and recommendations drawn from it.

Beyond methodological worries, though, and even if their predictions about GDP are correct (I am pretty sure they are not – there are too many other factors at play, including huge ones like the destruction of the environment that makes the odd 1.5% seem like a drop in the barrel) then it might be a good thing. It might be that we are moving – rather reluctantly – into a world in which GDP serves as an even less effective measure of success than it already is. There are already plentiful reasons to find it wanting, from its poor consideration of ecological consequences to its wilful blindness to (and causal effect upon) inequalities, to its simple inadequacy to capture the complexity and richness of human culture and wealth. I am a huge fan of the state of Bhutan’s rejection of the GDP, that it has replaced with the GNH happiness index. The GNH makes far more sense, and is what has led Bhutan to be one of the only countries in the world to be carbon positive, as well as being (arguably but provably) one of the happiest countries in the world. What would you rather have, money (at least for a few, probably not you), or happiness and a sustainable future? For Bhutan, education is not for economic prosperity: it is about improving happiness, which includes good governance, sustainability, and preservation of (but not ossification of) culture.

Many educators – and I am very definitely one of them – share Bhutan’s perspective on education. I think that my customer is not the student, or a government, or companies, but society as a whole, and that education makes (or should make) for happier, safer, more inventive, more tolerant, more stable, more adaptive societies, as well as many other good things. It supports dynamic meta-stability and thus the evolution of culture. It is very easy to lose sight of that goal when we have to account to companies, governments, other institutions, and to so many more deeply entangled sets of people with very different agendas and values, not to mention our inevitable focus on the hard methods and tools of whatever it is that we are teaching, as well as the norms and regulations of wherever we teach it. But we should not ever forget why we are here. It is to make the world a better place, not just for our students but for everyone. Why else would we bother?

Originally posted at: https://landing.athabascau.ca/bookmarks/view/6578662/skills-lost-due-to-covid-19-school-closures-will-hit-economic-output-for-generations-hmmm

Technology, technique, and teaching

These are the slides from my recent talk with students studying the philosophy of education at Pace University.

This is a mashup of various talks I have given in recent years, with a little new stuff drawn from my in-progress book. It starts with a discussion of the nature of technology, and the distinction between hard and soft technologies that sees relative hardness as the amount of pre-orchestration in a technology (be it a machine or a legal system or whatever). I observe that pedagogical methods (‘pedagogies’ for short) are soft technologies to those who are applying them, if not to those on the receiving end. It is implied (though I forgot to explicitly mention) that hard technologies are always more structurally significant than soft ones: they frame what is possible.

All technologies are assemblies, and (in education), the pedagogies applied by learners are always the most important parts of those assemblies. However, in traditional in-person classrooms, learners are (by default) highly controlled due to the nature of physics – the need to get a bunch of people together in one place at one time, scarcity of resources,  the limits of human voice and hearing, etc – and the consequent power relationships and organizational constraints that occur.  The classroom thus becomes the environment that frames the entire experience, which is very different from what are inaccurately described as online learning environments (which are just parts of a learner’s environment).

Because of physical constraints, the traditional classroom context is inherently very bad for intrinsic motivation. It leads to learners who don’t necessarily want to be there, having to do things they don’t necessarily want to do, often being either bored or confused. By far the most common solution to that problem is to apply externally regulated extrinsic motivation, such as grades, punishments for non-attendance, rules of classroom behaviour, and so on. This just makes matters much worse, and makes the reward (or the avoidance of punishment) the purpose of learning. Intelligent responses to this situation include cheating, short-term memorization strategies, satisficing, and agreeing with the teacher. It’s really bad for learning. Such issues are not at all surprising: all technologies create as well as solve problems, so we need to create counter technologies to deal with them. Thus, what we normally recognize as good pedagogy is, for the most part, a set of solutions to the problems created by the constraints of in-person teaching, to bring back the love of learning that is destroyed by the basic set-up. A lot of good teaching is therefore to do with supporting at least better, more internally regulated forms of extrinsic motivation.

Because pedagogies are soft technologies, skill is needed to use them well. Harder pedagogies, such as Direct Instruction, that are more prescriptive of method tend (on average) to work better than softer pedagogies such as problem-based learning, because most teachers tend towards being pretty average: that’s implicit in the term, after all. Lack of skill can be compensated for through the application of a standard set of methods that only need to be done correctly in order to work. Because such methods can also work for good teachers as well as the merely average or bad, their average effectiveness is, of course, high. Softer pedagogical methods such as active learning, problem-based learning, inquiry-based learning, and so on rely heavily on passionate, dedicated, skilled, time-rich teachers and so, on average, tend to be less successful. However, when done well, they outstrip more prescriptive methods by a large margin, and lead to richer, more expansive outcomes that go far beyond those specified in a syllabus or test. Softer technologies, by definition, allow for greater creativity, flexibility, adaptability, and so on than harder technologies but are therefore difficult to implement. There is no such thing as a purely hard or purely soft technology, though, and all exist on a spectrum,. Because all pedagogies are relatively soft technologies, even those that are quite prescriptive, almost any pedagogical method can work if it is done well: clunky, ugly, weak pedagogies used by a fantastic teacher can lead to great, persistent, enthusiastic learning. As Hattie observes, almost everything works – at least, that’s true of most things that are reported on in educational research studies :-). But (and this is the central message of my book, the consequences of which are profound) it ain’t what you do, it’s the way that you do it, that’s what gets results.

Problems can occur, though, when we use the same methods that work in person in a different context for which they were not designed. Online learning is by far the most dominant mode of learning (for those with an Internet connection – some big social, political, economic, and equity issues here) on the planet. Google, YouTube, Wikipedia, Reddit, StackExchange, Quora, etc, etc, etc, not to mention email, social networking sites, and so on, are central to how most of us in the online world learn anything nowadays. The weird thing about online education (in the institutional sense) is that online learning is far less obviously dominant, and tends to be viewed in a far less favourable light when offered as an option. Given the choice, and without other constraints, most students would rather learn in-person than online. At least in part, this is due to the fact that those of us working in formal online education continue to apply pedagogies and organizational methods that solved problems in in-person classrooms, especially with regard to teacher control: the rewards and punishments of grades, fixed length courses, strictly controlled pathways, and so on are solutions to problems that do not exist or that exist in very different forms for online learners, whose learning environment is never entirely controlled by a teacher.

The final section of the presentation is concerned with what – in very broad terms – native distance pedagogies might look like. Distance pedagogies need to acknowledge the inherently greater freedoms of distance learners and the inherently distributed nature of distance learning. Truly learner-centric teaching does not seek to control, but to support, and to acknowledge the massively distributed nature of the activity, in which everyone (including emergent collective and networked forms arising from their interactions) is part of the gestalt teacher, and each learner is – from their perspective – the most important part of all of that. To emphasize that none of this is exactly new (apart from the massive scale of connection, which does matter a lot), I include a slide of Leonardo’s to-do list that describes much the same kinds of activity as those that are needed of modern learners and teachers.

For those seeking more detail, I list a few of what Terry Anderson and I described as ‘Connectivist-generation’ pedagogical models. These are far more applicable to native online learning than earlier pedagogical generations that were invented for an in-person context. In my book I am now describing this new, digitally native generation as ‘complexivist’ pedagogies, which I think is a more accurate and less confusing name. It also acknowledges that many theories and models in the family (such as John Seely Brown’s distributed cognitive apprenticeship) predate Connectivism itself. The term comes from Davis’s and Sumara’s 2006 book, ‘Complexity and Education‘, which is a great read that deserves more attention than it received when it was published.

Slides: Technology, technique and teaching

Beyond learning outcomes

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

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

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

I frame this in terms of the relationships between:

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

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

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

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

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

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

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

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

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

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

DT&L2018 spotlight presentation: The Teaching Gestalt

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.

Small talk, big implications

fingerprint (public domain) An article from Quartz with some good links to studies showing the very many benefits of interacting with others, even at a very superficial level. I particularly like the report of a study showing the (quite strong) cognitive benefits of small talk.

It’s all solid stuff that supports much of what I and many others have written about the value of belongingness and social interaction in learning but, like much research in fields such as psychology, education, sociology, and so on, it makes some seemingly innocuous but fundamentally wrong assertions of fact. For instance:

“Those who were instructed to strike up a conversation with someone new on public transport or with their cab driver reported a more positive commute experience than those instructed to sit in silence.”

What, all of them? That seems either unbelievably improbable, or the result of a flawed methodology, or a sign of way too small a sample size. The paper itself is inaccessibly paywalled so I don’t know for sure, but I suspect this is actually just a sloppy description of the findings. It is not the result of bad reporting in the Quartz article, though: it is precisely what the abstract of the paper itself actually claims. The researchers make several similar claims like “Those who were instructed to strike up a hypothetical conversation with a stranger said they expected a negative experience as opposed to just sitting alone.” Again – all of them? If that were true, no one would ever talk to strangers (which anyone that has ever stood in a line-up in Canada knows to be not just false but Trumpishly false), so this is either a very atypical group or a very misleading statement about group members’ behaviours. The findings are likely, on average, correct for the groups studied, but that’s not the way it is written.

The article is filled with similarly dubious quotes from distinguished researchers and, worse, pronouncements about what we should do as a result. Often the error is subtly couched in (accurate but misleadingly ambiguous) phrasing like “The group that engaged in friendly small talk performed better in the tests.” I don’t think it is odd to carelessly read that as ‘all of the individuals in the group performed better than all of those in the other groups’, rather than that, ‘on average, the collective group entity performed better than another collective group entity’, which is what was actually meant (and that is far less interesting). From there it is an easy – but dangerously wrong – step to claim that ‘if you engage in small talk then you will experience cognitive gains.’ It’s natural to want to extrapolate a general law from averaged behaviours, and in some domains (where experimental anomalies can be compellingly explained) it makes sense, but it’s wrong in most cases, especially when applied to complex systems like, say, anything involving the behaviour of people.

It’s a problem because, like most in my profession, I regularly use such findings to guide my own teaching. On average, results are likely (but far from certain) to be better than if I did not use them, but definitely not for everyone, and certainly not every time.  Students do tend to benefit from engagement with other students, sure. It’s a fair heuristic, but there are exceptions, at least sometimes. And the exceptions aren’t just a statistical anomaly. These are real people we are talking about, not average people. When I do teaching well – nothing like enough of the time –  I try to make it possible for those that aren’t average to do their own thing without penalty. I try to be aware of differences and cater for them. I try to enable those that wish it to personalize their own learning. I do this because I’ve never in my entire life knowingly met an average person.

Unfortunately, our educational systems really don’t help me in my mission because they are pretty much geared to cater for someone that probably doesn’t exist. That said, the good news is that there is a general trend towards personalized learning that figures largely in most institutional plans. The bad news is that (as Alfie Kohn brilliantly observes) what is normally meant by ‘personalized’ in such plans is not its traditional definition at all, but instead ‘learning that is customized (normally by machines) for students in order that they should more effectively meet our requirements.’  In case we might have forgotten, personalization is something done by people, not to people. 

Further reading: Todd Rose’s ‘End of Average‘ is a great primer on how to avoid the average-to-the-particular trap and many other errors, including why learning styles, personality types, and a lot of other things many people believe to be true are utterly ungrounded, along with some really interesting discussion of how to improve our educational systems (amongst other things). I was gripped from start to finish and keep referring back to it a year or two on.

Address of the bookmark: https://qz.com/1134958/small-talks-positive-benefits-outweigh-your-fear-of-being-awkward/

Originally posted at: https://landing.athabascau.ca/bookmarks/view/2849927/small-talk-big-implications

No, you aren't a 'visual' learner

It’s a damning indictment of our collective resistance to truth that the point of this article still has to be restated, yet again. Amazingly, 93% of the general public and 76% of educators still erroneously believe that we should be taught in ways that match our learning styles. I assume this is so in the US – unless things have changed recently, the percentages, for teachers at least, are even worse in some other countries where the idea has been pushed harder from the top down, such as the UK and Netherlands. To be quite clear: this belief is not supported by any compelling evidence at all.

The fact that it is false (or, at best, no more provable than, and just as likely as, astrology) doesn’t mean that designing for learning styles necessarily a terrible idea, inasmuch as it can encourage reflective practice on the part of teachers and can even result in quite useful outcomes. As the article puts it:

“If you’re trying to vary what you do in the classroom to respect different styles, variation in instruction is probably a good thing, anyway,” he says. But rather than formatting lessons differently for auditory, kinetic or visual learners, he and Macdonald suggest that teachers tweak their instruction based on content.

“I think it really depends on your objectives for the lesson,” Macdonald says. “Some types of content really lend themselves to visual presentation … if you’re teaching maps, that’s got to be visual. If you’re teaching music, those are [the] types of things that need to be auditory.

“But if your goal is to get a multifaceted exposure to certain content, it can be helpful to weave in all different types of modalities.”

That thinking about learning styles can be a useful design tool is a fair point, and one that I have often made myself (including in quite some detail in my first book), though it’s a happy side effect of a mistake, rather than a consequence of a good theory. Using star signs would probably work just as well.  I am not convinced that content should always lead design either: objectives-driven teaching is not the only fruit and, for some expansive subject areas and pedagogies, it is positively (positivistly?) harmful. But, notwithstanding its constraints and limitations, at least it is not based on a fiction.

There are many risks to using a false world model, even if it has some practical value or plausible results (pre-Copernican geocentric astronomy was better than Copernicus’s own theory at predicting movements of planets), not least of which being that it blinds us to real possibilities and leads us in worthless, wasteful, or even harmful directions. Even when the consequences include better teaching, it’s a terrible lesson to teach someone that they are a visual (or sensing, or whatever nonsense the particular theory suggests) learner. No they are not. They might have some habits, reinforced patterns, or preferences, sure. But that just means they need to try a bit harder to extend themselves and to learn to use some alternative approaches because they are definitely going to have to use them at some point when there’s no teacher in control of things but themselves, and nothing to fit their preferred style available. My learning style is and should be whatever the hell I need.

I’ve mentioned before that I believe a better (if less attractive) term would be ‘being-taught habits’ because one of the least savoury aspects of the whole learning styles gestalt is that it actually has little to do with learning, and everything to do with achieving better indoctrination; of asserting the power of the teacher (at least, it would if it worked). For that kind of thing, we’d learn more from the sciences and arts of the advertising industry than from any snake oil learning style theory. We might equally learn from preachers and religions: they are mostly pretty good at making people think and behave the way they wish.

There are other ways to gain the useful side-effects of designing for learning styles that do not rely on falsehoods, or that make no claims that they match reality one way or the other – de Bono’s Thinking Hats, for instance, or design-based research. And it doesn’t take much to make learning style theories less dumb. I am personally quite fond of Gordon Pask’s serialist/holist model, despite coming perilously close to a learning styles theory at times, because it describes a continuum of learning strategies, without suggesting too much (OK, fair enough, Pask slipped here and there) that such strategies be fixed, habitual, or generally preferred by particular learners.  They are simply perspectives we can choose as and when it is helpful to do so. However, if possible, when designing learning activities, we should use approaches that are based as much as we are able on how the world is, not how we think it should be. From that perspective, learning styles are a potentially dangerous and time-consuming dead end.

Address of the bookmark: http://theweek.com/articles/725352/no-arent-visual-learner

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Strategies for successful learning at AU

Earlier today I responded to a prospective student who was, amongst other things, seeking advice on strategies for success on a couple of our self-paced programming courses. My response was just a stream of consciousness off the top of my head but I think it might be useful to others. Here, then, with some very light editing to remove references to specific courses, are a few fairly random thoughts on how to succeed on a self-paced online programming course (and, for the most part, other courses) at Athabasca University. In no particular order:

  • Try to make sure that people close to you know what you are doing and, ideally, are supportive. Other people can really help, not just for the mechanical stuff but for the emotional support. Online learning, especially the self-paced form we use, can feel a bit isolating at times, but there are lots of ways to close the gap and they aren’t all found in the course materials and processes. Find support wherever you can.
  • Make a schedule and try to keep to it, but don’t blame yourself if your deadlines slip a bit here and there – just adjust the plan. The really important thing is that you should feel in control of the process. Having such control is one of the huge benefits of our way of teaching, but you need to take ownership of the process yourself in order to experience the benefits.
  • If the course provides forums or other social engagement try to proactively engage in them. Again, other people really help.
  • You will have way more freedom than those in traditional classrooms, who have to follow a teacher simply because of the nature of physics. However, that freedom is a two-edged sword as you can sometimes be swamped with choices and not know which way to go. If you are unsure, don’t be afraid to ask for help. But do take advantage of the freedom. Set your own goals. Look for the things that excite you and explore further. Take breaks if you are getting tired. Play. Take control of the learning process and enjoy the ride.
  • Enjoy the challenges. Sometimes it will be hard, and you should expect that, especially in programming courses like these. Programming can be very frustrating at times – after 35 years of programming I can still spend days on a problem that turns out to involve a misplaced semi-colon! Accept that, and accept that even the most intractable problems will eventually be solved (and it is a wonderful feeling when you do finally get it to work). Make time to sleep on it. If you’re stuck, ask for help.
  • Get your work/life/learning balance right. Be realistic in your aspirations and expect to spend many hours a week on this, but make sure you make time to get away from it.
  • Keep a learning journal, a reflective diary of what you have done and how you have addressed the struggles, even if the course itself doesn’t ask for one. There are few more effective ways to consolidate and connect your learning than to reflect on it, and it can help to mark your progress: good to read when your motivation is flagging.
  • Get used to waiting for responses and find other things to learn in the meantime. Don’t stop learning because you are waiting – move on to something else, practice something you have already done, or reflect on what you have been doing so far.
  • Programming is a performance skill that demands constant and repeated practice. You just need to do it, get it wrong, do it again, and again, and again, until it feels like second nature. In many ways it is like learning a musical instrument or maybe even driving. It’s not something you can learn simply by reading or by being told, you really have to immerse yourself in doing it. Make up your own challenges if you run out of things to do.
  • Don’t just limit yourself to what we provide. Find forums and communities with appropriate interests. I am a big fan of StackOverflow.com for help and inspiration from others, though relevant subreddits can be useful and there are many other sites and systems dedicated to programming. Find one or two that make sense to you. Again, other people can really help.

Online learning can be great fun as long as you are aware of the big differences, primarily relating to control and personal agency. Our role is to provide a bit of structure and a supportive environment to enable you to learn, rather than to tell you stuff and make you do things, which can be disconcerting at first if you are used to traditional classroom learning. This puts more pressure on you, and more onus on you to organize and manage your own learning, but don’t ever forget that you are not ever really alone – we are here to help.

In summary, I think it really comes down to three big things, all of which are really about motivation, and all of which are quite different when learning online compared to face-to-face:

  1. Autonomy – you are in control, but you must take responsibility for your own learning. You can always delegate control to us (or others) when the going gets hard or choices are hard to make, but you are always free to take it back again, and there will be no one standing over you making you do stuff apart from yourself.
  2. Competence – there are few things more satisfying than being able to do more today than you could do yesterday. We provide some challenges and we try to keep them difficult-but-achievable at every stage along the way, but it is a great idea for you to also seek your own challenges, to play, to explore, to discover, especially if the challenges we offer are too difficult or too boring. Reflection can help a lot with this, as a means to recognize what, how, and why you have learned.
  3. Relatedness – never forget the importance of other people. You don’t have to interact with them if you don’t want to do so (that’s another freedom we offer), but it is at the very least helpful to think about how you belong in our community, your own community, and the broader community of learners and programmers, and how what and how you are learning can affect others (directly or indirectly).

This advice is by no means comprehensive! If you have other ideas or advice, or things that have worked for you, or things that you disagree with, do feel free to share them in the comments.