Blogging once a month isn’t exactly the frequency I want or imagine. I’ll try to step things up a bit. I’ve no lack of things to mull over here–perhaps the superflux is the problem–but the real answer, for me anyway, is just to do it.
So here’s today’s “just do it.”
January was an exceptionally full month for me, beginning with the trek back from Virginia, continuing with presentations at the University of Delaware, at Wheaton College (for NITLE) and two presentations at the EDUCAUSE Learning Initiative annual meeting, and concluding with a big push to get some more programs (and a website–stay tuned) launched for the Academy for Teaching and Learning at Baylor. (Video from the Delaware presentation is online at the link above; podcasts are on the way for the other three presentations–again, stay tuned.) I’ve also begun teaching at Baylor: a first year seminar that continues my work in New Media Studies (course front-page blog here). Four intrepid souls who don’t know me from Adam signed up for the journey. It’s great to hear “Dr. C.” again–I always feel energized when I hear that call.
As I’ve carried on my work this month, I’ve returned again and again to the role of computers in learning. It’s not all I think about, but it’s a topic that grabbed me decades ago and never turned loose. I keep trying to understand not only the subject itself, but the sources of my own fascination. The presentation at Delaware was perhaps my fullest effort to date to get at the vexed question of what a computer is, or rather, what it symbolizes. The Delaware visit drew heavily from my experience late last year, when I was (and remain) captivated by the discussion at the Program for the Future, where I got to shake Doug Engelbart’s hand and tell him “thank you,” and where I saw visionary after visionary wrestle with their own fascinations and attempts at understanding.I saw yet again how passionate these visionaries are, not because they’re techno-utopians, but because they recognize the exhilarating, liberating potential of computers to represent ourselves and our world back to us in a way that will allow us to access the traces of our own engagement, to think about ourselves with both commitment and critical detachment. Most of all, these computers represent our own powers of representation, our endless curiosities, our troubling and hopeful attempts at communication and community. They are truly protean, as Seymour Papert observes in the wonderful collection Falling for Science: Objects in Mind. (Alice over at “Just Musing” blogs wonderfully about that book. It’s a magic book and I recommend it to everyone I talk to these days–but that’s another blog post from me.)
Protean. Yes, and in their protean nature, computers are proto-objects, meta-objects, emergence engines: not because they are intelligent, but because they are complex symbols of intelligence, of investigation, of making, of knowing. And when they are networked, either locally or via the Internet, they are communications devices that fold meta-layer after meta-layer onto our awareness of the very processes of communication, of “lending our minds out,” as the poet Robert Browning’s Fra Lippo Lippi says of art.
Why then are computers still used in education as document manipulation devices on steroids? They can be used for that, yes, of course they can. And often those uses are quite valuable. But that model only scratches the surface of their potential. Worse yet, that model diverts our attention, our resources, and our risky investigations away from the uses that most closely align with what we say we want for education: intellectual maturity; deeply considered interaction in words, images, sounds; innovation; invention; the joy of our communal mental processes; strategic leadership in a world that lives from one rushed tactic to another; a “capability infrastructure,” to use Doug Engelbart’s words.
As I taught J. C. R. Licklider’s foundational essay “Man-Computer Symbiosis” last week, it occurred to me that Licklider set us on the right course and the wrong course simultaneously. “Symbiosis” is right. His description of human cognition is pretty robust as well. But here’s his description of “computer,” one that is accurate for the time, perhaps, but not at all the generative paradigm he hoped for:
“It may be appropriate to acknowledge, at this point, that we are using the term ‘computer’ to cover a wide class of calculating, data-processing, and information-storage-and-retrieval machines. The capabilities of machines in this class are increasing almost daily. It is therefore hazardous to make general statements about capabilities of the class.”
The problem here, as I see it, is not Licklider’s confidence that the calculating, data-processing, and information-storage-and-retrieval machines will become ever more capable. History has certainly borne that confidence out. The problem is that Licklider’s classification downplays the role of computers as representation- or symbol-making devices, and ignores altogether the role of computers as a communications medium. The two deficits in his argument are closely related, and I’d say that the two deficits still characterize most of the way we think about computers. Yet if we think about symbols, representations, and the shared symbol-making, symbol-exchanging activities we call “communication” (and directed internally, “thought”), we open up a much richer, more complex, and more catalytic universe to explore.
This is where Engelbart diverges most profoundly from Licklider, I think. Engelbart understood that concepts are symbols, and also frameworks for those symbols. He envisioned computers as enabling more complex symbol-making and symbol-sharing. Engelbart maintains to this day that we will become more effective problem-solvers if we become more effective symbol-makers. I agree, though I’m not at all sure that the most powerful symbols emerge from hierarchical models of meaning and meaning-making. (Actually, I’m pretty sure they don’t.)
What’s most fascinating for me remains the ways in which computers allow us not only to make and share more powerful, complex, rich, and resonant symbols, but the ways in which the making and sharing become themselves the ghostly outline, visible most brightly when we like astronomers use our more-sensitive peripheral vision, of the consciousness and community we build together. That’s what I keep trying to get at, how humanity writes the poetry of its life into being, together. Now the question of whether we’re writing doggerel or an epic poem is another question altogether. Computers can augment our drivel as well as our most noble articulations. They’re a medium, not a silver bullet, panacea, or Miracle-Gro. But what’s important is the way they reveal yet another level, a proto-level and a macro-level, of what’s hidden in plain sight: our essential collaboration emerging from our lives together. You can see this in a library, in a gym, at a good meeting (they do happen), in a church or synagogue or mosque, in a fire-dance, even in a grocery store. What computers do is reveal the universes within a universe, the nested infinities, in the most complexly and dynamically symbolic medium we have yet invented (outside of poetry, that is).
And so back to education. Are our students not universes within a universe? Are our faculty and staff not likewise? Are we not a university? If so, why all the talk of management? Why not more talk of exploration, of representation, of communal mental activity, of the exciting and taxing co-labors of symbol-making and symbol-sharing? That’s the test of life, as Michael Wesch has poignantly observed. (By the way, I firmly believe we need to include “poignance” as an essential analytical and expressive skill, particularly for scholars.) That’s what we all need to know for that test. Insofar as computers can represent those universes and help those universes map and travel through and share the universe they all inhabit, they are extraordinary proto- and meta-objects. Insofar as computers reinscribe the clerical only, allowing us to store and retrieve managed, measured, and boxed-in lives and days, they are of limited worth, and potentially quite dangerous as they empower our most impoverished imaginations, our most stubborn wrongheadedness.
In the meantime, I hope it’s not another month before I arm-wrestle myself in this space, and I am most grateful to those who’ve invited me to explore these issues with them in their own communities. I always learn a ton and leave with many more ideas than I came with. Sometimes I even leave with way-cool swag!
Go Dr. C! Keep the blog publish button warm.
Computers may approach your descriptions when they more transparent in the ways we think, interact, reach, or don’t reach for them. In talking with a friend visiting this weekend, and spending some time looking at the creative expression his son is doing in YouTube form, both for school and out of school with friends, I was struck by the notion of people (and not just ‘young’) using their personal time to *create* media. Thinking of my pre-internet youth, at best, we were consuming media.
Gardner:
Wonderful stuff, as always. As I read I was thinking about a companion notion (obviously not original to me): what we humans can do with our minds has been limited (for all but a few) by our inability to mentally construct the means of dealing with the complexity inherent in the notion of human life in ever expanding, multiplying and overlapping communities. In the past, we’ve tried to deal with that complexity when we encounter its edges by reductionist/simplification strategies. Seems to me we’re now exploring means by which we start fundamentally engaging that complexity rather than seeking to explain it in simpler terms that our minds could more comfortably grasp. That’s because–now–our minds are augmented by ever more sophisticated computing technologies; our actual capabilities are growing past old limits, rapidly (faster than we’re perceiving the growth) and continuously, thanks to those computing technologies. And, wonder upon wonder, we discover in our increasing capacity to grok the complexity of human life on the macro scale that the same increased capacity gives us deeper, richer insight into how an individual mind (our own) works too. This strikes me as the exact opposite of hive mind–rather than being oblivious to the gestalt of it as bees in a hive likely are, we’re starting to swim perceptively in the complexity now, thanks to the augmentation effect of computing technologies. Said another way, we’re both living the complexity and we’re beginning to conceive it too (mindful of complexity). Talk about a new epistemology. Really starts to screw around with one’s thinking about education (among other things, or, I should say, everything). Way cool.
Definitely increase your blog rate Gardner – what may be an idle musing to you is carefully articulated argument to the rest of us.
Quick question – I know it was an aside, but wonder if you could elaborate on the poignancy comment?
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