Git for teachers — Medium

Git logoThis is a nice set of reflections on the potential value of GitHub to teachers. The title is broader, referring to the Git source code version control system, an open standard with hundreds of implementations, but most of the article is about GitHub, a closed commercial system that packages up Git with a deeply social workflow and friendly interface, making the bulk of its money from those that want support for closed projects and teams rather than open source goodness. Ben rightly points out that a source control system is great for text but less great for binary files and that, despite the quite friendly interface, there is quite a learning curve needed to use it effectively, especially if you are not used to the complexities of writing MarkDown code. Essentially, though it is a soft tool that can be repurposed and reassembled in many different ways, it is built for programmers, and structured in ways that support application development, not other things.

Ben’s suggestions are (typically) thought-provoking and good…

  1. An open source, freely-available content control tool designed for people working with non-code. It’s okay for it to not know about fancy file formats like Word, but it should be able to handle more than line-by-line changes. Perhaps call it scribe.
  2. A proprietary, beautiful city ecosystem built around it. A ScribeHub.

Nice idea and, as he observes, one that some people have already tried and failed to do, providing some good examples of tools that go part of the way. There’s a good discussion of some of the issues of doing so in the follow-up comments to a post by David Wiley a while back. That said, the big advantage of GitHub is that it does already exist (and is thriving) and does get used for much more than just coding. I really like some of the innovative uses of GitHub for things like journal production: https://github.com/ReScience/ for instance, uses it to make articles and research into living documents, updated as reviews and replications come in. But, as Ben says, it is not optimal for anything other than coding and text documentation and, though there are some great exemplars, it is not likely to hit the mainstream as an alternative means of production outside the coding and documentation community for some time, if ever. Also, much as I love GitHub for its innovative and smooth community integration, it is a commercial monolith. Such things should be distributed and open.

What makes GitHub so cool

Perhaps the biggest differentiating feature in GitHub that makes it stand out from other similar tools is the combination of (for the unpaid variant) required openness, and the ability for anyone at all to make a ‘pull request’. Anyone can make a copy (a ‘fork’) of an existing GitHub project and (and here is the good bit), if they make changes that would be useful in the upstream project, submit a pull request to the author(s) so that their changes can be reincorporated (merged) back into the main branch of the code. Github provides tools that, at least for text, make such merging relatively pain-free. Through this mechanism, the work of many loosely coupled people can cooperatively work on complex projects without the need for further mechanisms of collaboration, teams, collaboration, or complex project management. GitHub does, of course, have rich communication tools for discussing such changes and passing them back and forth, so it can be used very effectively for closed teams as well as in a more open, networked community, but its central social motif is the network, not the group.

An idea

I have been thinking for some time about building a programming course that uses GitHub or, perhaps better, an open variant such as GitLab, or a related coding support tool with similar intent like Phabricator. The basic idea would be that the course itself would evolve through pull requests – if students or others have ideas for improvements, they would simply implement them and submit a pull request which the course owner could choose to merge or reject. Others could, of course, build their own versions of the course at will. I don’t think this is particularly original in itself – many have built OERs this way – but it makes sense to me as both a way of actually hosting a course, and as a way of building in student participation in the development and evolution of a course. Amongst other things, it opens up the potential for students to customize courses for their particular needs: if the basic model contains stuff that is irrelevant or already known, they could adapt it to the way they want it and, of course, share that with others. This in turn opens up some interesting options for scalability and personalization (the good sort). Rather than providing a single, monolithic MOOC, courses could branch off into many related versions, each with its own communities and interests. Someone might, for example, adapt the structure for a different language, focus down on a particular element, restructure it for different pedagogical designs, or extend it for more or less advanced learners. As the ‘course’ itself would be hosted on GitHub (or whatever) there would be no need for additional tools, and the course communities/cohorts could relatively easily blend with one another, or overlap. There would be evolutionary competition between the various branches, perhaps, leading to ever better (or, more accurately, better adapted) versions of the courses.

At least a part of the assessment of the course would be based around taking an existing codebase (in some possible variants, perhaps the code used for the system employed to host the course?) and making improvements to it. Credit would be awarded to those whose pull requests were accepted. One particularly nice thing about that is that all work would, by its very nature, be original. There would be no value at all in simply copying what someone else had done, and success would be measured according to real-world metrics: it would have to be good enough to enter production. It might get a bit complicated as the course matured and there were fewer obvious things to be improved, but I have yet to come across any perfect software beyond very trivial and, with a plugin/service-based architecture the potential for improvements could be virtually limitless. There’s scope for most skill levels, apart from absolute beginners, here. And even relative newbies could contribute to things like documentation.

The idea appeals to me though, as others have found when trying to do something similar with OERs, the complexities mount up pretty quickly. One of the issues is that, unlike in the case of most programming code, one size does not fit all: it is not about producing one useful course or toolset. We are not talking about building an open textbook here, but a course that is suitable for many people in many different contexts. It is therefore more likely that forks would be more useful than merges for most people. In the coding community, this can be a problem – you wind up with many similar forks of code, each of which goes its own (increasingly incompatible) way, diluting the value and community around the original and making it difficult to choose between them (for instance, the many forks of MySQL or the two major branches of Open/LibreOffice). Big products can spawn so many forks and pull-requests that the original authors can be overwhelmed. For courses, forking would allow for the kind of repurposing – contextualization around individuals and communities – that makes OERs worthwhile in the first place. More than with open source applications, though, there would also be issues with diluting the learning community: this might be a benefit for something like a MOOC, where numbers are too large to be managed in the first place, but not so good for smaller courses.  There’s a balance to be sought. Having recently tried (and I am still trying) to incorporate changes from a main branch into a modified version of an OER course, I can verify that it can be fiendishly complex.  I want to maintain our own localizations but the updates are great and, in some cases, necessary. Merging is really difficult, because there is a great deal more involved than simple text, hierarchical directories and a few dependencies to deal with.

A system that would do as Ben suggests for complex media would be a great help in such things. Among those rich media I would love it if it could cope with, say, an exported Moodle course, where it is not just content but process and structure that needs to be tracked, and where changes to structure could greatly impact the meaning and value of the content. The complex, soft dependencies and need for narrative flow make such things structurally very different from the relatively proscribed ways that programs can change, so I don’t have a clear idea of how that could be done right now. It would certainly be possible to use an XML interchange format to track such things but those are made for machines, not people, to read. In fact, the only human-friendly way that I can think of for dealing with it would be to build it into the authoring environment itself – to have a Git-like thing at the backend of (say) Moodle. At Athabasca we do kind-of the same sort of thing using Alfresco to track changes, but the process is clunky, discontinuous, lacks the elegant cooperation of GitHub, is very document-centric (no fine-grained merging at all), and is very much a group, not a network environment, with teams and roles that are anything but open and that exist in very rigid organizational hierarchies, with roles that limit what they can do, and only a single, unforked course as the outcome.

Perhaps such a project – to build that friendlier front end – might be what course takers might use as raw material. Early, and more advanced, takers of the course would be building the infrastructure for later students. I rather like the idea.

Address of the bookmark: https://medium.com/@benwerd/git-for-teachers-e993d2ca423d#.nqby85xqs

Humpback whale in English Bay

Damn it, I didn’t bring my big camera. The camera in my phone does not do this justice…

Humpback whale in English Bay

There is something genuinely awesome – in the original sense of the word – about being out on the water in a boat that is smaller than the creature swimming next to you. The humpback whale swam around us for about 40 minutes before moving on. Somewhere between 10 and 20 seals hung around nearby hoping for some left-overs, as did a small flock of seagulls. We tried to keep our distance (unlike a couple of boats) but the whale was quite happy to swim around us.

Whale

Prizes as Curriculum • How my school gets students to “behave”

A harrowing report on systematic child abuse in an American school. What’s particularly tragic about that is that the teachers who are inflicting such abuses are not bad people: they genuinely believe that they are doing good or, if not good, then at least they are doing their best to help.

Louisa was a warm and well-meaning person. After this incident, she wanted to reflect on what had happened—it had been an upsetting day for all. Louisa asked herself certain questions and didn’t ask others. In the end, she was able to justify her decision in a way that enabled her to see her decision as a moral one. “Eric has problems entertaining himself, and that’s something we need to support him with. Maybe something is going on at home,” she sighed.

Very sad. We must change this reward and punishment culture. It does not work.

Address of the bookmark: http://www.rethinkingschools.org/archive/30_03/30-3_lagerwerff.shtml

Learning and the Kardashians

As I am preparing for a talk next week on the future of online learning and writing a bit in a paper about the same kind of thing, I am pleased to see another timely publication in a long line of excellent Pew reports on American life, this time focusing on lifelong learning, which is hugely relevant to what I will be speaking and writing about about. As I need to think a bit more on this topic anyway, this seems like a good opportunity for reflection.

Findings of the report

Before moving on to my reflections, there are a few things that particularly stand out for me. For instance:

  • 74% of Americans have engaged in some deliberate personal learning (as measured by the researchers) over the past year, though only 16% have taken an online course.
  • 73% consider themselves to be lifelong learners.

This makes me worry greatly about over a quarter of Americans that have done no such thing and that do not consider themselves to be lifelong learners. It is hard to understand how one could be human and not consider oneself a learner but the study’s design likely shaped the kind of answers it received. I will have more to say on that. It is also interesting that courses play such a small role. More on that later too.

I am fascinated by the motivations of the subjects of the study:

  • 80% of personal learners say they pursued knowledge in an area of personal interest because they wanted to learn something that would help them make their life more interesting and full.
  • 64% say they wanted to learn something that would allow them to help others more effectively.
  • 60% say they had some extra time on their hands to pursue their interests.
  • 36% say they wanted to turn a hobby into something that generates income.
  • 33% say they wanted to learn things that would help them keep up with the schoolwork of their children, grandchildren or other kids in their lives.

This accords better with my understanding of human beings. People love to learn, and learning has huge social value in both process and product. It is notable that far fewer of the study’s subjects have extrinsic than intrinsic motivation, and it appears that, for the vast majority, the extrinsic driver is at most a catalyst for them to do something that is intrinsically fulfilling. This is reinforced in the following graphs, that are a terrific confirmation of the predictions of self-determination theory (SDT):

the value of educational experiences to learners in the US

As we already know from SDT, the value of learning is fundamentally about achieving competence as a good thing in itself, deeply social in purpose and value, and highly concerned with being in (or gaining) control: in brief, competence, relatedness and autonomy support. This is exactly what we see here. It is noteworthy that, though advancement in occupations matters to professional learners, there is no mention of money nor of qualifications in any of this. This accords with the fact that only 16% of those in the study took courses, given that courses tend to lead to formal or less formal credentials. It is very unfortunate that institutional learning has become so much concerned with courses and credentialing that all of these very good reasons for learning are incredibly crowded out. Much of the time, people in institutions learn in order to get the qualification, not for the pleasure that is so profoundly obvious in these findings. The luckiest ones get both. Most are not so lucky. More than a few get neither fulfillment nor credentials.

Matthew Effects: the rich get richer

The survey finds very strong links between existing education, prosperity and culture, and lifelong learning. Furthermore, the digital divide is, at least by some measures, widening:

As a rule, those adults with more education, household incomes and internet-connecting technologies are more likely to be participants in today’s educational ecosystem and to use information technology to navigate the world.

This is not too surprising – it’s pretty much there in the definition – but the Matthew Effect is in full swing here:

For personal learning, 87% of those with college degrees or more (throughout this report adults with college degrees or more refers to anyone who has at least a bachelor’s degree) have done such an activity in the past year, compared with 60% for among those with high school degrees or less. For professional learning, about three quarters (72%) of employed adults with at least college degrees have engaged in some sort of job-related training in the past year, while half (49%) of employed adults with high school degrees or less have done this.

Those that have learned to learn, and to see the value in it, learn more. They probably have more time and resources for it:

Among those with a smartphone and a home broadband connection (just over half the population), 82% have done some personal learning activity in the past year. For the remaining adults (those with just one of these connection devices or neither of them), 64% have done personal learning in the past year.

It is interesting that technology appears to have quite a large effect on learning. This is causal, not just a correlation. It’s not the tools, per se, but the adjacent possible that the tools bring. Basically, the tools can support learning or not but, if you don’t have the tools, the opportunity never arises. Those that claim technology has no effect on learning are simply wrong, but what is significant here is that it is not the teachers, but the learners, that make this so. There may be some very faint and equivocal glimmer of truth in the belief that technology does not normally do much to improve teaching, but it sure does a lot to improve learning.

Being America, a land of conspicuous inequality, the report shows that there are also strong divisions along ethnic lines, with African Americans and Hispanics considerably less likely to have engaged in personal learning, and somewhat less likely to have engaged in professional learning. The report is less clear whether this is a socio-economic issue or a more broadly cultural concern. I’m guessing a bit of both. When a social system separates particular groups, for whatever reason (and ethnicity is a deeply stupid reason), then patterns of behaviour are likely to cluster. As always, diversity (and the celebration of diversity) is much to be wished for here. We are wisest when we are exposed to and open to diverse views, values and opinions.

Finally, an opportunity for distance institutions like Athabasca University. Some of the notable preference for face to face learning (81% to 54%) is almost certainly down to lack of awareness of digital learning methods:

Noteworthy majorities of Americans say they are “not too” or “not at all” aware of these things:

  • Distance learning – 61% of adults have little or no awareness of this concept.
  • The Khan Academy, which provides video lessons for students on key concepts in things such as math, science, the humanities and languages – 79% of adults do not have much awareness of it
  • Massive open online courses (MOOCs) that are now being offered by universities and companies – 80% of adults do not have much awareness of these.
  • Digital badges that can certify if someone has mastered an idea or a skill – 83% of adults do not have much awareness of these.


It seems we have not been particularly smart about getting the message out! That’s a huge and untapped population of people who do not even know our methods of teaching exist, let alone of our own existence. At least some of those appear to be educated people with a thirst for knowledge.

Learning and the Kardashians

A lot of the inequalities demonstrated in the Pew report are deeply worrying and endemic. It seems to me that, as well as trying to address that imbalance directly, we in education should give a bit more thought to how we might embed productive learning more deeply into all our interactions, rather than just concentrating on making courses and tutorials in educational systems. While some of this embedding can be addressed with deliberate intent – popular channels, celebrity scientists and artists, accessible and appealing museums and galleries, subsidies for Internet access, libraries, etc – a lot of this is about system design. It’s about building tools and environments where critical and reflective engagement is part of the fabric of the system.

With that in mind, I think it is important to note a strong methodological bias in these findings. Significantly, they rely on self-reporting of deliberate learning activities that are largely defined by the researchers. There’s a strong bias towards things like courses, tutorials, guides, workshops, conferences and clubs that are explicitly designed to support learning. It is worth observing that most learning is not designed and not intentional (including in formal education). Almost every act of communication involves at least a hint of learning and, especially for interactive media such as Internet or Mobile technologies, the percentage of time spent learning in the process is normally significant. Almost all reading, watching and dialogue involves learning. We might not recognize it as such, but every time we learn of Bieber’s latest exploits, or Trump’s latest vileness, or our friend’s new puppy, we are deeply engaged in acts of learning. It is not just (and rarely most importantly) about the content of what is learned, but the ways of being that such learning engenders. Our values, beliefs and attitudes are deeply dependent on our interactions with others, mediated or not, and what we perceive of the world around us (especially the people and their creations within it). What we choose to observe or communicate changes us. Often, we engage critically with what we read or watch or talk about. Even simple learning from observation is not just about copying but about interpreting and constructing. Internet technologies, in particular, have massively increased the quantity and breadth of such observation and communication. Most of what we know is not learned deliberately but emerges through our interactions with other people and the world around us. Most of what even traditional teachers teach is not the content of what they teach but the ways of being and thinking that go along with it.

To suggest or imply, therefore, that lack of deliberate learning through conventional channels means that no learning is happening is deeply mistaken, and somewhat dangerous, because it ignores all but the visible tip of the iceberg. By far the biggest opportunities for education lie not in the stuff that we educators currently do for a job, but in embedding learning in the everyday; in designing pedagogies that are not pedagogies; in creating architectures where learning can thrive rather than in deliberately leading people in directions we think they should go. It is possibly sad but definitely true that the Kardashians are far better teachers with far greater reach than most professional teachers, apart from (maybe) celebrities like David Attenborough, Randall Munroe, David Suzuki or Neil Degrasse Tyson. What the Kardashians teach might seem to have little value and, arguably, might have negative value, but it should not be discounted as irrelevant learning. Nor, for that matter, should what we learn (directly and indirectly) from politicians, musicians and sports stars. The shapers of our emerging global society are many and varied, and I would be hesitant to suggest, snobbishly, that the reflective, critical, synthetic, analytic and creative skills that professional teachers try to support should have a monopoly over the emotional, social, value-forming ways of thinking that other contributors to society provide in greater measure.

Boundaries and education

Personally, I think the things we try to formally teach (not so much the content as the reflective, critical, synthetic, analytic and creative skills) matter a great deal. Taught well, they directly and demonstrably lead to better, healthier, richer, more creative, more caring, more productive societies, where people can look more critically on the likes of Trump and the Kardashians, with greater perspicacity, with greater creativity, and with more kindness to and understanding of those that think differently. But they also lead to a lot of things that are not so healthy, especially in their institutionalized control-freakery and cataleptic attitudes to change. Educational institutions have done and continue to do a lot of good but, if we really want to bring about a better, more educated world, there is a very good chance that they are no longer the ideal platform for it, and definitely far from the only one.

In my talk next week I will be exploring the ways that physical boundaries, notably of time and place, have deeply influenced how we go about the process of education. Almost all of our pedagogies are predicated on the assumption that a number of people need to gather in a particular place at a particular time, with associated structures, rules and processes to support that. Teachers are a scarce resource, classrooms are rival goods, and schedules matter. So we invented classes, courses, timetables, and methods of managing them. This in turn inevitably demands that people learn things they don’t need to learn, that they may be unable or unwilling to learn, at times that may not suit them, under conditions that greatly restrict their autonomy. All in all, despite good support for relatedness, this is terrible for motivation, and it crowds out almost all the great benefits that are reported on in the Pew study. One-to-one learning works much better because it largely avoids those constraints but is, for all but a few, economically unviable. Voluntary attendance to learning activities when needed (much of what is reported on in the study) is also good, but not well catered for in our educational systems that need to adopt tight schedules and lack much flexibility. Thus, much of our pedagogical practice and almost all of our educational system is designed to overcome or reduce the demotivating side-effects of simple physics. All too often, and all too often institutionalized, the solution is to fall back on primitive behaviourist models of motivation that do a great deal more harm than good. Such physics seldom if ever applies online, where boundaries are inherently fuzzy, metaphorical, fluid and malleable. However, most of us still adopt substantially the same pedagogies and we pointlessly (or worse) attempt to fit our teaching into systems that were designed for and with different boundaries. We even build tools like learning management systems that embody them, saving them from exinction and perhaps even magnifying them (it’s often easier to see what is going on in a live classroom than within the confines of an LMS). And, having done so, we cement the demotivational effects by controlling learners through grades and certificates, rewarding and punishing with Skinnerian efficiency. It’s no surprise that, when you take such things away, MOOC completion rates, though improving thanks mainly to better self-selection and increasing use of real reward and punishment through more recognized credentials (often becoming significantly less open in the process), average no more than 15%

Shifting boundaries and open spaces

Though online boundaries are different, there are lessons to be drawn from the built environment. I am incredibly lucky to live in Vancouver, where public art, information and hey-wow architecture and design is everywhere to be seen. It is hard to look anywhere without being informed, delighted or provoked in useful ways, from the shapes of leaves immortalized on the sidewalks to street art and poetry on the walls. Our cognition is fundamentally distributed, and the richness of the spaces around us, virtual or physical, contributes considerably to how and what we know, as well as our values and behaviours. Even simple separation of space can make a huge difference. It took a while after coming here to realize what was the main difference between schools here and in the UK: fences. In the UK, a school is normally enclosed by tall fences that both keep people out and keep children in. Around the school along the sea wall from me there are no such barriers, and children play at break-time in the parks and playgrounds outside. It’s still very safe – many eyes see to that, as well as a culture of trust – but it makes all the difference in the world to the meaning of the space, especially to the children but also to the community around them. Such little things make big differences. Part of the value of that is, again, diversity: being exposed to different stimuli and people is always a good thing, and another of Vancouver’s immense strengths. The area around the school is a wonderful mix of expensive luxury waterfront property and cheap but attractive and well cared-for community housing: unless you happen to know that red roofs signify community housing, you would be very unlikely to spot the difference. Messing with boundaries and celebrating diversity is, of course, a big part of the thinking behind the Landing. It’s a space where boundaries are deliberately softened, where learning can be visible and shared, but which is still safe and where everyone is accountable. Simply opening up the space is enough to bring about greater and different learning, and a different attitude towards it. 

Openness alone is not enough, though. Far too many public forums and comment areas (e.g. most newspaper sites) that are quite open are filled with vitriol, inanity and stupidity. Sure, a lot of learning happens, but mostly not in a productive or useful way, at least from my biased perspective and that of a lot of people that are turned off by it. I am guessing that this might well be what would happen if fences around UK schools were torn down without considering the surrounding community and environment. Community makes a huge difference: though I am sure they have to indulge in a bit of judicious pruning and moderation, when I read blogs by people like, say, Stephen Downes, George Siemens , Terry Anderson, or David Wiley, I see almost nothing but intelligent dialogue from those that comment, because those with an interest in the area have shared concerns and contested but concordant values. Well, perhaps the dialogue is not always intelligent, but at least it is always a learning dialogue. The downside of that is, of course, a relative lack of diversity in the communities that read their work.

So, environment matters too, and often helps to shape the community. For instance, I am still much smitten, after nearly two decades, by the model of SlashDot, which shapes learning dialogues through a combination of smart algorithms and, most importantly, the actions and interactions of people using the system. The best of these dialogues is more than a match for any textbook or classroom, and the worst are not too bad: anything else evolves away. The algorithms are complex and it takes skill to get the most out of them, so it is way too geeky to be of general use, but it shows the general methods and principles that might underlie a system that makes knowledge grow and learning happen simply by shaping the space of interaction, giving individuals the tools to filter and form the space, and providing a space to gather. Less sophisticated/effective but more generally usable tools of this nature include Reddit and StackExchange, which combine ratings and karma information to allow the community to shape what the community sees. While both are flawed and neither is infallible, the combination of human organization and machine filtering generally makes both quite useful for a wide range of topics.  I am also much encouraged by how Wikipedia has evolved: its more deliberate structuring and guidance of the flow means it involves higher maintenance than more obviously collectively guided tools but it is incredibly successful at supporting and spreading useful knowledge (including about the Kardashians). The approach of each of these systems to diversity is a little like that of the Vancouver City planners: to design for it. There are places where communities meet and interact but there is also parcellation, with signals of their boundaries but no significant barriers, that supports the growth of a supportive culture (at least in places – there are, of course, some areas that thrive on dischord), and that makes trust visible.

There are potential opportunities for analytics tools, collaborative filters, and similar forms of data-driven algorithmic approaches here too. Such methods come with enormous risks, mostly due to the insatiable desire of programmers to control what other people do: to erect new boundaries. Even when done with good intentions, they can have harmful effects. Almost the last thing we need in such spaces is filter bubbles and echo chambers, but such approaches can embed and reinforce patterns and attitudes simply by doing their job, building boundaries that are all the more dangerous because they are invisible and unmentioned. The absolute last thing we need is machines to make decisions for us based on what a programmer has decided is best for us or, just as bad, using criteria over which we have no say. There are huge risks of designing new boundaries that are just as controlling and just as demotivating as the ones they replace. I don’t resent Amazon’s recommendations of what I might like to read next at all, for example, especially when it tells me why it is making those recommendations, because it does nothing to enforce those recommendations and learns when I disagree. I do resent Netflix limiting what it shows me that I might want to watch, though: this reduces my autonomy. I greatly dislike learning analytics tools that tell me how well I am meeting someone else’s goals, but I approve of those that help me to define and reach my own. I am happy for Google Search to suggest relevant sites I might want to visit, as long as it continues to show me those it is less impressed with, but I am deeply unhappy that Facebook shows me a tiny percentage of posts I might like to see. I love that clicking a word or phrase in an e-book will give me a definition and a link to Wikipedia or Google Search. I hate that clicking a help link will tell me what someone else thinks I need to know (especially when the nugget I need is hidden in a lengthy video that gives me no clues about where to find it). What all of this boils down to is support for the fundamental drivers found in the Pew report: autonomy, relatedness and competence. Take away any one of those, and you take away the love of learning. But, with care, scrutability, and attention to supporting human needs, such systems can be expansive and liberating.

In conclusion

For now, most of the new systems we use to replace the formal process of teaching show promise but most have numerous weaknesses, most of which formal teaching overcomes: concerns about reliability, trust, safety, efficiency, and the effects of deliberate malice are well founded, and there are big issues of control and autonomy to overcome. But it seems to me that, as we start to dismantle the boundaries of traditional educational practice, the opportunities to extend and improve learning through reinvention of our learning spaces online are (virtually!) limitless, while we reached a state of near stasis in physically located learning many hundreds of years ago. Sure, there have been incremental improvements here and there but they have been uneven at best, and it is possible to see examples of great pedagogies being used thousands of years ago that are barely, if at all, improved today. It’s all down to physics. 

Footnote

I wouldn’t know a Kardashian if one kicked me in the face and, until just now, I had little idea about what they were apart from being a family that is known across the Internet for nothing more substantial than their own celebrity. For quite a long time I actually thought the headlines and post titles about them were about a fictitious race from Star Trek. What’s quite interesting about that is that I had learned what little I knew on the subject without, until just now, any intention of doing so. I found out a bit more just now by way of fact checking, through Wikipedia, but it seems that what I already knew was pretty much accurate. Education happens whether we seek it or not. It would be good if that education were more valuable more of the time.

Exams as the mothers of invention

I’m often delighted by the inventiveness and determination of exam cheats. It would be wonderful were such creativity and enthusiasm put into learning whatever it is that exams are supposed to be assessing but, tragically, the inherently demotivating nature of exams (it’s all about extrinsic motivation and various ways they diminish intrinsic motivation) means that this is a bit of an uphill struggle. I particularly like the ingenious but not very smart approaches mentioned in this article:

“One test taker apparently hid his or her mother under the desk, from where she fed the student answers, while in a second case, someone outside the test taker’s room communicated answers by coughing Morse code.”

Of course, the smart ones are not so easily discovered.

This is an endless and absurd arms war that no one can win. The inventiveness and determination of exam cheats is nearly but not quite matched by the inventiveness and determination of exam proctors. My favourite recent example is the Indian Army’s reported efforts to prevent exam cheating by making examinees remove all their clothes and sit in an open field, surrounded by uniformed guards. It is hard to believe this could happen but the source seems reliable enough and there are videos to prove it. I’m prepared to bet that they didn’t stop cheating altogether, though. 

I’ve found one and only one absolutely foolproof method of preventing cheating in proctored exams: don’t give them in the first place, and challenge yourself to think of smarter ways of judging competence instead. Everyone is better off that way. But, if you are determined to give them, despite the overwhelming evidence that they are demotivating, unfair, unreliable, unkind and costly, don’t make it possible for the answers to be given in morse code.

Address of the bookmark: https://www.insidehighered.com/quicktakes/2016/03/30/examity-shares-data-cheaters

Study: People Want Power Because They Want Autonomy

An article from The Atlantic describing a study that reveals autonomy is, almost entirely, the reason people like to have power. This accords very well with the predictions of self-determination theory.

Power (in the most meaningful sense of the word) is pretty much the same thing as autonomy, I think: it’s about feeling that you are in control of your life, regardless of whether that feeling is justified. This suggests that some forms of what we generally recognize as power (ie. positions of authority, with control over what others do) might not be so great, inasmuch as the accompanying responsibilities can considerably reduce autonomy. Those in middle management, myself incuded, are in a great many ways less autonomous than those over whom they have purported power, in part because of their responsibility to those they lead, and in part due to their accountability to those with greater power. I’m guessing that the same is true right up to leaders of institutions, who are accountable to governments and other funding bodies in much the same way as those lower in the pecking order are accountable to them.

For optimal happiness, organizational hierarchies (not those that occur in natural systems but that are designed by humans) are an inherently weak idea, most notably because they must always be antagonistic to autonomy. They survive as a reasonably effective compromise made to make  organizations and societies function like machines: indeed, they are one of our most fundamental enabling technologies. They are the main way that large groups of people can efficiently live in peace and prosperity together. Hierarchies are responsible for many good things, a foundational technology on which much of human society, culture and technology is based, without which we would likely still be in the trees. But it is important to remember that they are just technologies: they are inventions that can be improved upon and that could easily be superceded by better inventions. Democratic governance was likely the last major successful innovation in the technology, but it doesn’t solve many of the inherent weaknesses. For the most part, the inevitable inefficiencies, filtering of information and, above all, diminution of intrinsic motivation make organizational hierarchies a deeply flawed solution to the problems of large scale human coordination that they are designed to solve.

With modern technologies, especially those involved in and emerging from ubiquitous communication and availability of knowledge, we can and should do better than hierarchies. I am increasingly intrigued by and drawn to the model of The Morning Star Company, that thrives without hierarchies, where everyone, from temporary tomato pickers to the CEO, is a manager, and where power is not given but taken as a natural right. What’s remarkable about it is not so much the pattern (which is not unlike that of traditional academia and many other organizations and social forms) but the fact that the pattern works really well.

 

Address of the bookmark: http://www.theatlantic.com/health/archive/2016/03/people-want-power-because-they-want-autonomy/474669/?single_page=true

The LMS of the future is yours! | Michael Goudzwaard

I think this is, from a quick skim through, the beginnings of a very good idea. An LMS that does almost nothing. Quoting directly:

What would this LMS look like? In my view, it would have three things:

1) a course roster with stellar SIS integration

2) a gradebook

3) a rock-star LTI and API

That’s it! Oh, except it would also be open source, students would control their own data, including publishing any of their work or evaluations to the block chain, and you could host it locally, distributed, or in the cloud. Never mind the pesky privacy laws (or lack thereof) in the country hosting your server, because the LMS is back on campus. Not connected to the internet? That’s okay too, because there is a killer app that syncs like a boss (like Evernote. Has Evernote ever given you a sync error? No, I didn’t think so.)

Who wins with the new LMS? Students because they own and control their data and it costs less to buy and run. Instructors because they have a solid core with the option to plug any LTI into a class hub. Institutions because costs are lower and the system more secure.
Who loses? The EdTech companies. Or do they? Without standard wiki features and discussion portals, startups and the old standard barriers can invest their R&D and venture funds in really great tools.”

The principle is a little like that of Elgg, that consists of a very small core, with everything else coming from plugins that use the API.

It seems to me that, though this concept allows its users (teachers, students, admins alike) to do what they like with tools and data, it is still firmly based around the assumption of a traditional classroom model, and seems, as much as the traditional LMS, to reinforce that view. It’s still a course and grading management system, not a learning management system. It needs something that goes beyond the classroom, even in a traditional institutional setting. It needs much more flexible groupings, networks and sets.

With that in mind, this lightweight LMS still seems heavier than needed. A SIS might well provide course information, so that might be redundant. If not, a plugin or service could be written, rather than including it in the core. I am not at all sure that an integral gradebook is needed either, for much the same reason. It might, instead, benefit from a standards-based open source learning record store using xAPI (TinCan), like Learning Locker.  Or, perhaps, an integration of an OpenBadges backpack. Either, along with APIs that allow integration with things like SISs that could make badges look like grades or that could identify relevant learning records, could serve the necessary functions and allow a great deal more openness. Perhaps integrated support for some kinds of grouping and networking would help satisfy the needs of those that want to build institutional courses. All that is really needed is that rockstar API to pull it all together. This begins to sound a lot more like Elgg, and something that could, in principle, be implemented within it.

The blockchain idea is a good one: being able to free data from a central machine is much to be wished for. But it bothers me that privacy laws are seen as pesky and that they should be circumvented. They are pesky, for sure, but with good reason. We cannot force students to part with private data where laws do not protect them (I do have at least one course that does this, but it’s one of the conditions of enrolling because we are actually studying such things). What people do of their own accord is, of course, just fine, but the tacit assumption that this LMS-lite continues to reinforce is that learning happens in courses that lead directly to accreditation. That’s not about people doing things of their own accord.

With that in mind I can foresee a few interesting issues with authorization too, whatever path is taken. The mechanisms for deciding who allows what to be seen by whom might turn out to be quite complex because of the tension between hierarchical roles implied by this system and individual access authority implied by the freedom to use anything from anywhere, especially given the balkanization of social media space that currently exists and that is likely to form a good part of the basis of actual learning activities. Anything that is not public is going to have to interface with this in some quite tricky ways.

For all its embedded assumptions, I like the idea. Building an Elgg-like system with integral LTI, especially if it could support more learner-centric technologies like xAPI, OpenBadges and so on, seems like a sensible way to go

Address of the bookmark: http://mgoudz.com/2016/02/26/the-lms-of-the-future-is-yours/

Reactions to Facebook's reactions

I quite like the word ‘reactions’ that Facebook is using to describe their new options to express feelings about a post. I wish I’d thought of it. This is a matter of much more than passing interest to me as it relates closely to something that occupied a lot of my time over some years of my life. In my own CoFIND social bookmarking system (that first saw the light of day about 18 years ago and underpinned my PhD work) I used to refer to something quite similar as ‘qualities’ – metadata (tags) to show not just that something is good or interesting but how it is good or interesting, that could then be used to rate and thus help to filter and rank a feed of bookmarked resources. CoFIND is an acronym – Collaborative Filter in N Dimensions – that refers to this n-dimensionality of ratings. Facebook’s Reactions feature is a simplified version of this: it’s about categories more than tags, but the thinking behind it is broadly similar. The differences, though, are interesting.

Fuzzy ratings

One of the things that is most notable about Facebook Reactions is that ratings are, like its Likes before them, binary: a simple ‘yes’ or ‘not-rated’.  In most versions of CoFIND (it iterated a lot), users could choose to what extent something was good/loved/annoying/interesting/etc through a Likert scale. Giving the option to choose the strength of a feeling seems much more sensible when talking about fuzzy values like this. I want to be able to signify that I quite like something, or that is is mildly amusing, especially if my intent is to communicate my feelings to others. Facebook’s Reactions are a coarse as a means of expression: it is quite appropriate that its emoticons are literal caricatures.  In all the methods I tried – radio buttons, clickable links, etc – introducing scalar ratings turned out to be way too complex to be usable, but web interfaces were not as rich in those days: I think things like popup draggable sliders (not dissimilar to Facebook’s interface) might make it more feasible nowadays.

Evolving metadata

Facebook Reactions are not just binary but fixed. CoFIND – I think, still uniquely – allowed individuals to create new qualities (reactions), which could then be used by anyone else. It was an n-dimensional rating system where ‘n’ could be any number at all. Qualities quite literally evolved for each community, with more used qualities surviving (being immediately available for use) and less used ones being relegated to backwaters of the system (effectively dying, albeit with the possibility of resurrection if added again). This allowed for such metadata to provide a mirror of the values that mattered most within a given community or network, rather than being imposed uniformly on everyone, and for those values to evolve as the community itself evolved. While I appreciate the simplicity of Facebook’s interface (CoFIND’s most fatal flaw was always that its interface was far too complex to be usable) I still think that user-created ways of emoting – what I have since called ‘fuzzy tags‘ – lead to much more useful reactions that matter within a given community, especially when users can choose the degree to which a fuzzy tag applies. When CoFIND was used in an educational setting, qualities like ‘good for beginners’, ‘authoritative’, or ‘comprehensive’ tended to emerge – they were pedagogical metadata. When used in other contexts, such as to discover what HCI students considered important in a website, site-ranking qualities like ‘slow’, ‘boring’, ‘artistic’ and ‘informative’ appeared.

CoFIND qualities

 

Parcellation

One of the things I hate most vehemently about Facebook is that it same-ifies everything: a person in Facebook has a single unchanging (and permanently reified) identity, with a single network, a single facade, a single caricatured way of being in the world, notwithstanding the odd nod to diversity like pages and lists. Facebook’s business model relies on this, because any clustering or parcellation reduces the potential to connect, and connections are everything to Facebook. This makes me highly sceptical of its claimed ‘discovery’ that people are actually separated by only 3.57 degrees rather than six. Given that the system very deliberately drives them to friend as many others as much as possible, on most tenuous grounds of connection, this is hardly surprising. It shows not that previous studies are mistaken but the extent to which Facebook has manipulated human networks for profit. Apart from evolving to fit a single community, another of the things CoFIND did was to deliberately parcellate the environment, allowing different sets of values to evolve in different contexts. What is ‘good’ in the context of learning to read is not likely to be ‘good’ in the context of learning geometry, so different topics each evolved a (largely) separate set of qualities. This might not have been the best way to drive the growth of large networks, but it was a much better way to enable the self-organized emergence of meaningful communities. It also allowed individuals to express and embrace different facets of themselves, which in turn made it easy to accommodate changing needs and interests: essential in the context of learning, which is (if nothing else) about change.

You can read about the tortuous process of CoFIND’s development and the thinking behind it in my PhD thesis. I continued to develop CoFIND into the mid 2000s but, though the final version was a bit more usable and scalable (I rewrote it in PHP and changed a lot of the mechanisms, simplifying a fair number of things, including losing the fuzzy ratings) I’m still most fond of the final version that is described in the thesis.

Address of the bookmark: http://www.huffingtonpost.com/entry/facebook-reactions-update_us_56ccb128e4b0ec6725e42861?ir=Weird+News&section=us_weird-news&utm_hp_ref=weird-news

First, Let’s Fire All the Managers

This is an article about how and why The Morning Star Company works. It’s a company where

• No one has a boss.

• Employees negotiate responsibilities with their peers.

• Everyone can spend the company’s money.

• Each individual is responsible for acquiring the tools needed to do his or her work.

• There are no titles and no promotions.

• Compensation decisions are peer-based.

Moreover, it is:

” a large, capital-intensive corporation whose sprawling plants devour hundreds of tons of raw materials every hour, where dozens of processes have to be kept within tight tolerances, and where 400 full-time employees produce over $700 million a year in revenues. And by the way, this unique company is a global market leader”.

I believe that this could serve as a superb model for academia. In fact, I strongly suspect it would work even better in academia, that has a natural leaning towards autonomy. It would increase motivation, ownership, engagement, efficiency and creativity across the board.

The title of the article is not altogether accurate because the central mechanism through which Morning Star Co achieves its remarkable success is to treat everyone – from the temporary pickers of tomatoes to the president of the company – as a manager. It’s not about getting rid of managers at all but creating a process in which everyone has power and agency, without structural hierarchies (or, at least, with very lightweight, flexible and shifting hierarchies). This is clearly very motivating: 

 “If people are free, they will be drawn to what they really like as opposed to being pushed toward what they have been told to like,” says Rufer. “So they will personally do better; they’ll be more enthused to do things.” Morning Star’s employees echo this sentiment. “When people tell you what to do, you’re a machine,” says one operator.”

One thing I particularly like is that it is hugely empowering, but it’s not about empowerment:

“the notion of empowerment assumes that authority trickles down—that power gets bestowed from above, as and when the powerful see fit. In an organization built on the principles of self-management, individuals aren’t given power by the higher-ups; they simply have it.”

The benefits – more initiative, more expertise, more flexibility, more collegiality, better judgement and more loyalty – are well explained in the article. This is a highly successful company, not just in its market but for its workers.

The article goes into some detail on how it works without centralized control and power hierarchies. It explains how those who don’t pull their weight are treated, how processes are coordinated, how success is measured and what makes it both efficient and creative at the same time. The mechanisms of control are almost entirely social and the production process is almost entirely self-organizing. The company is designed to create the conditions needed for people to work together effectively: not so much a machine as an ecosystem. Inspiring stuff. Not only would it be a great way to run a university, it would not be a bad way to run a program or even an individual course.

Address of the bookmark: https://hbr.org/2011/12/first-lets-fire-all-the-managers