Digital Learning Is Like a Snow Leopard (Real, Beautiful, Rare and Maybe To Be Outdated by a New Operating System)

Maybe it’s just because it’s my obsession of the moment, but the digital camera strikes me as the single greatest example of a new “disruptive” technology that permits a fundamentally new kind of learning experience.

However, precisely because digital photography is the best example, it also defines a limit or border: a great many other discrete skills, tasks and competencies do not have the crucial characteristics of digital photography and are therefore not nearly so open to pedagogical transformation through digitization or online communication.

What gives a digital camera a special kind of capacity for auto-didactic learning? Two things: speed and cost. As in fast and none. Add to that an unusually robust communicative infrastructure for sharing, circulating and viewing photographs, so that aspirant photographers will always have a very large, responsive community of fellow learners available to them.

Each picture taken with a digital camera is an experiment with the medium. The photographer can see in a viewfinder immediately the consequences of every press of the shutter trigger. Change the composition, the focus, and if it’s a DSLR, almost every setting, and see a new outcome. Processing software allows images, particularly those taken in RAW format, to become something radically different in a few seconds of adjustment. There is no cost to each experiment once the initial investment is made, save storage to accommodate images on-camera and in some kind of archive.

The sharing and circulation of images was one of the earliest defining practices of the Internet and is now one of the focal points of very large social media communities. Photographers who share images–and even those who just view–are now able to see exceptionally large flows of cultural work on a daily basis and to interpret the action of algorithmic practices of rating, ranking, curating, and so on–a focus of some recent writing here at this blog.

So here we have a technology whose intrinsic properties and emergent interactions with communities of use and production incidentally make it extremely easy to learn new techniques, approaches and themes. Digital photographers not only can discover through trial and error material facts about light, composition, tonality and subject but also can watch large assemblages of algorithmic culture collectively “discover” preferences and tropes, which also instruct the learning photographer not just about how to shoot but what to shoot. When you see the five hundredth image of a Southeast Asian fisherman throwing a net that is backlit by a setting or rising sun, you can come to understand both what the human eye and the algorithmic culture of the moment “like” about that trope. And maybe, as with the best learning, you can abstract that insight to other compositions and ideas. What thin or diaphanous objects catch light? What other kinds of ‘exoticized’ subjects and scenes draw attention? And so on.

This is not to say that all digital photography is auto-didactic, or that all digital photographers are equally capable of taking up these lessons. But there is an unusual density of online resources available to instruct photographers at key moments in their learning. Take for example David Hobby’s seven-year old site Strobist.com, with its Lighting 101 course, which I think deserves to be regarded as one of the first fully-realized and implemented “massively open online courses”, well before Thrun and Norvig’s Stanford AI class. The site and the course have had a major impact on digital photography over those seven years, evidence of the degree to which this particular medium has a learning community that scales up to a global expanse.

And of course there are limits here: for one, involving costly equipment and the vested cultures that gently and not-so-gently push at each other around that equipment. A photographer with an iPhone camera and an open-source or cheap processing app will have a harder time learning some of the concepts and techniques that are privileged in some cultures of photographic production and consumption. For another, there are forms of technological literacy that auto-didactic approaches to digital photography assume rather than offer, and moments in learning where the presence of a regular, physically present teacher would provide more efficient, transformative or richer understanding.

Most importantly, the camera and the software and the communities cannot provide the answer to the question, “Why do I take photographs, and what kind of art or product do I want to make?” A technology and a large community of fellow learners and users, do not tell you how to think about visuality, and how images speak to audiences and each other. A teacher–or an overall education–might make progress on that front, but the device and its infrastructure will not answer of its own accord.

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The thing is, much of the rest of what people might want to learn in 2013–for fun, for enlightenment, for immediate application to their careers–does not share either of the key attributes of digital photography: speed and cost.

Take something similarly basic to the production of digital images, and even more widely necessary in the contemporary world both in private life and in work: writing. Writing is not fast and it is not, despite word processors and spell-checkers and a host of other small embedded technologies of production, nearly so intuitive to the wetware of the human brain and body. The metaphor of the eye has all sort of misleading or deceptive application to photography but it is a good enough baseline for explaining why most people can take–or view–a picture more intuitively than they can write a letter or an essay.

You cannot write quickly and intuitively enough to experience near-simultaneous iterations of multiple examples of the same instance of writing. And therefore writing has a different kind of cost in labor time, even if it has some of the same frictionless cost of other digital culture. (E.g., the real cost in paper AND time of typing or handwriting multiple drafts is different than the cost of storing many digital files.) You can’t distribute writing to as many online audiences who have as close a consensus about what they’re seeking and the attention that reading takes is in shorter supply. (Hence: TL;DR.)

So just as with photography, questions about “what is writing”, “why write” and so on don’t self-answer, but the medium itself doesn’t even have the automatic affordances of digital photography.

Now try something as inescapably material as carpentry or emergency medicine. Here the costs of the necessary materials are very high, the process of learning them through use is very slow, and the dangers of improper or incomplete practice are extraordinary and multilayered. Or try something where the learning process is inevitably and always social, interactive and/or institutional: counseling, driving, military training. Digital or virtual processes might leaven or enrich educational experience but they can’t even begin to replace the conventional approach.

This is one of several places that the enthusiasm for MOOCs is going to founder in short order: digitization is only revolutionary in its automating possibilities for education in the exception, not the norm, and those exceptions are structured by real, physical limits long before they involve entrenched assumptions. Where digitized approaches to writing or emergency medicine or carpentry compare favorably to existing educational services, that won’t be because of the technology of digitization but because, as Clay Shirky has more or less argued recently, much existing education already sucks as much as digitized education is going to suck. But this is a very different challenge, then, from “digitize it all”: it is “make it suck much less, whatever it is and however it is delivered”.

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One Response to Digital Learning Is Like a Snow Leopard (Real, Beautiful, Rare and Maybe To Be Outdated by a New Operating System)

  1. Jay Scott says:

    Make it suck less…

    … which is easier for MOOCs because it calls more for technical advances and less for institutional and systemic advances.

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