e-Literate

Present is Prologue

Tag: Jay-Cross

  • Let's All Live In Jay's House

    I’m insanely jealous. It turns out that Jay Cross lives in a house built by the great architect Christopher Alexander. I’m a huge fan of Alexander’s work. Furthermore, I think anyone who does instructional design should read Alexander’s book. No, I don’t mean The Nature of Order, which is the book that Jay is apparently reading now; I haven’t read that one yet (though I intend to). I mean A Pattern Language: Towns, Buildings, Construction.

    To begin with, if ever there was a book that prefigured hypertext, this is it. Written in 1977, it is a honeycomb of short, cross-referenced entries. You can’t really read it cover-to-cover; instead, you browse. You scan. You jump around. You…surf.

    But the real value is in the way Alexander changes your thinking about design. In stark contrast to the whole idea of architect as designer and architecture as engineering, Alexander sees the architect as an ecologist and architectural design as the product of natural selection. He points to the distinctive qualities of old buildings throughout the world that have stood for hundreds or thousands of years while other buildings around them were torn down. What qualities do they have in common? What features can we deduce as natural, as creating a pleasurable and healthy living environment? What remains useful to people generation after generation? And what remains beautiful? What are the patterns that emerge?

    Then notice how these things fit together. Certain patterns will fit together nicely while others will not. There is a grammar for stringing together architectural elements, Alexander argues. A natural language. A pattern language. If you surf his book and see the pictures, I’ll bet money that you’ll become convinced he’s right. I did.

    We should be thinking about our instructional design, our information architecture, and our software user interfaces in the same ways. Despite the newness of computers, there are going to emerge more or less natural ways of interacting with it. The only way to find out what the more natural ways are is to let people build their own systems, move the furniture around, tear things down, and start over again. That’s hard to do with software, though HTML makes it somewhat easier by lowering the knowledge requirements. (Hypercard was probably the first step in this direction.) Likewise, we need course management systems that are highly configurable, allowing instructors to experiment with plugging in new pieces and arranging them in different ways. And above all, we need a pattern language for learning objects.

    Perhaps this sounds like a stretch. If so, then it’s not the furthest stretch that anyone has made with Alexander’s work. Software engineers have taken to pattern languages big-time.

  • Yet Another Take on Emergence

    This piece by Richard Seel (found by way of the Wrede article referenced in the previous post) is yet another version of emergent learning that seems to live roughly in the same neighborhood as Kathleen Gilroy’s and Godfrey Parkin’s (though I’m not suggesting that he precisely agrees with either of them). Seel suggests a small-group brainstorming method that he calls “emergent inquiry.” It has the following process elements:

    • Everyone speaks with many others.
    • Relevant and ‘irrelevant’ inputs
    • Many short ’rounds
    • Safe, egalitarian environment
    • Clear question, tight time-keeping
    • Relevant topic, desire for answer
    • Wait for the question…

    Some of these aren’t explicit in their meaning, but you can get the gist. Now, this looks like a fine way to do brainstorming. But it seems to reduce the concept of “emergence” to good ideas that come out of a well-functioning group discussion. Yeah, sure, some ideas come from the product of conversation; they don’t belong to any one person in the group. And yeah, sure, it seems like magic when that happens. But it’s not a new phenomenon that’s just been discovered or newly explained by some paradigm-shifting theory, and I’m not sure what’s gained by calling it “emergence.”

    My understanding of emergence is phenomena like the one described in Jay Cross’ eLearn article:

    You’re witnessing bottom-up decision-making in the swift turn of a school of fish but we’re not used to seeing it in business. MIT Professor Tom Malone equipped an audience with hand-held paddles whose position could be read by a computer. On the screen up front, he projected a flight simulator. A hundred people jointly took the controls of the plane and, against all expectation, flew the plane without a pilot and without a crash.

    This is surely emergence and it is surely not emergent learning. In fact, there doesn’t appear to be any learning going on here at all. Nobody is claiming that the individuals who entered the demonstration not knowing how to fly a plane left the demonstration ready to jump into the cockpit. Nor would the speed at which the group arrived at their collective piloting judgments indicate that they were consciously teaching and learning from each other; that would have taken much more time. In fact, we have no reason to believe that there was a single skilled pilot in the room or, if one was in the room, that he or she directly influenced the judgments of the non-pilots. What is emergent here is knowledge, and the reason that it is emergent is not because the people in the group learned from each other (they didn’t) and not because they came to an explicit consensus through discussion (though it may be fair to say that they pooled–not transferred, but pooled–tacit knowledge in the moment) but because the group as a whole was able to exercise judgment that was better than that of most or all of its individual members. You could say that piloting skill “emerged” from the group because the group members did not individually posess the skill either before or after the exercise.

    I’m probably beating a dead horse here, but I just feel like we won’t benefit from the insights of new scientific discoveries if we’re not careful to characterize them correctly. Seel’s method is probably dandy; I just don’t think that what it cultivates can be fairly called “emergence.”

  • Emergent Emergence

    Godfrey Parkin blogs:

    In the E-literate blog, Michael Feldstein has recently had a couple of jabs at the burgeoning interest in emergent learning, as enthusiastically promoted by Jay Cross and others. I suspect that he’s overthinking it and just doesn’t get it.

    If so, it wouldn’t be the first time. However, at the risk of compounding the error of “overthinking it,” I’m going to try to parse through Godfrey’s definition of “emergent learning.” Because he’s right about one thing: I don’t get it yet.

    Godfrey claims that I’m misunderstanding the conversation:

    He’s using “emergent” in the Steven Johnson sense of the increasing collective smartness of dumber parts, as in smart hives of dumb bees or smart brains of dumb neurons. And by that rather narrow use of the term, he’s right — emergent learning is something of an oxymoron. But “emergent learning” is not used in that sense, at least I have never heard it used that way. Those talking about emergent learning are not talking exclusively about how groups of people get smarter by being connected with each other, though it’s part of the discussion. And they are certainly not talking about rapid consensus-building.

    Part of the problem is that he and I are clearly participating in different conversations. He attributes the “emergent learning” meme to Jay Cross, while I was primarily responding to Kathleen Gilroy. And I know Kathleen was talking about “emergence” in the same sense as Steven Johnson because she explicitly references his book.

    More importantly, I think Godfrey misreads Steven Johnson’s position when he claims that Johnson talks about “increasing collective smartness of dumber parts, as in smart hives of dumb bees or smart brains of dumb neurons” (though I understand where Mr. Parkin may have gotten that interpretation from reading my own post). Emergence really isn’t about smarts; it’s about behaviors. And because the emergent behaviors that are most interesting and worthwhile to study are usually adaptive behaviors, we mistake them for “smarts.” This was really my point when I said that emergent learning is an oxymoron; to the extent that we equate emergent adaptive behaviors with smarts, we are making a category mistake.

    So, given Parkin’s understanding of emergence in the sense of the scientific phenomenon, it’s understandable that he has missed Jay Cross’ hints that he, too, means to invoke the research that Johnson writes about (though possibly in a very different way than Kathleen does). In CLO Magazine, Jay writes:

    Businesses are complex adaptive systems. In a complex system, independent pieces join together to form something entirely different and unexpected.

    The best metaphor for a complex adaptive system is a living thing. Take a complex system apart, and you no longer have a complex system. As Verna Allee writes, “Cut a cow in half and you don’t have two cows. You have a mess.”

    In their book, “It’s Alive,” management theorists Stan Davis and Christopher Meyer make a compelling case that business entities are living, complex systems. Many nodes-brains-come together to form something new-the corporate body. As my friend David Grebow says, it even has a Corporate IQ and, according to author David Batestone, a Corporate Soul.

    Emergence is the key characteristic of complex systems. It is the process by which simple entities self-organize to form something more complex. Emergence is also what happened to that “utopian dream” of e-learning on the way to the future. Simple, old e-learning has combined with bottom-up self-organizing systems, network effects and today’s environment to morph into emergent learning.

    The phrases “complex adaptive systems” and “self-organize” are dead givaways; Jay is clearly invoking the same “emergence” that Johnson means and not simply the broader dictionary definition.

    So it seems we have at least three different definitions of “emergent learning;” Jay’s, Godfrey’s, and Kathleen’s. I’ve already made clear what I think about Kathleen’s definition: it’s an oxymoron. I’m not sure that I’m fully wrapping my head around Jay’s definition yet. Reading the passage above carefully, it seems he’s not necessarily talking about learning that is itself emergent. Instead, he seems to refer to the organization itself as exhibiting emergent behavior. Read this way, “emergent learning” might mean, roughly, “learning in the context of emergence” or “the learning strategies that make sense when dealing with complex adaptive systems.” I’m not sure if I’m reading Jay correctly on this; perhaps he will be kind enough to post a clarification in his own blog.

    At any rate, back to Godfrey. He writes:

    More typically, they are using emergent in the sense that most dictionaries would define it — coming into being or coming into notice. What they are looking at is how emerging technologies (and unexpected applications of them) are changing learning strategies, learning organization, learning implementation, and generally changing the way we go about learning as individuals and as organizations. Learning, and the way it is promulgated, is evolving visibly as it becomes a persistent survival skill. And we need to understand what is happening so that we can recognize it, influence those developments, or leverage any emergent opportunities. (That is, opportunities that are coming into being or becoming recognizable). One of the challenges of emergent learning (and I guess of business generally these days) is to recognize what among all of the chaos coming at us is significant and to exploit it before it is a speck in the rear view mirror

    In some ways, this is not so different from the stab I made above at interpreting Jay’s version of “emergent learning.” One of the interesting things about emergence (in the Johnsonian sense) is that it really screws up some traditional accounts of causality. You can’t really do a top-down analysis and hope to understand why some things happen. Forget about looking for that pacemaker cell directing the others; if you want to understand how slime mold cells work together, then you have to look at the behavior of each individual cell and how the whole turns out to be greater than the sum of its parts. This, in turn, seems to fit well with the theme of “unexpectedness,” which is a major point that Godfrey emphasizes, i.e., things are chaotic and moving fast; therefore, our learning strategies must enable us to recognize change and adapt to it quickly.

    Naturally, you don’t need the concept of complex adaptive systems (in the rigorously defined sense) to accept the point of view that we need to have rapid response capabilities built into our learning strategies. But without that concept, I’m not sure that there’s much left beyond an obvious assertion about the state of the world we live in. Sure, change is a constant. So what are we going to do about it? By itself, Godfrey’s definition of “emergent learning” seems to say nothing beyond “we need to deal with this.” Which is fine, as far as it goes, but it doesn’t seem to be a new kind of learning. It says we need a new kind of learning, without saying what that kind of learning is.

    It’s possible that adding the more rigorous notion of emergence into the mix will get us somewhere different. At the very least, it suggests more specific places to look for answers (theoretically speaking). But I’m not sure yet. Jay himself seems to acknowledge that we don’t have a clear idea of what “emergent learning” is at the moment:

    Emergent learning implies adaptation to the environment, timeliness, flexibility and space for co-creation. It is the future. We haven’t figured it out yet. Or, from the perspective of complexity science, it hasn’t figured itself out yet.

    As I mentioned to Jay in an email, I’m a recovering philosophy major. I don’t do well with fuzzy definitions. So yeah, Godfrey is right. I don’t get it yet.

  • Crossed Wires: The Workflow Intitute Responds and I Apologize

    I have had several really gratifying exchanges with folks at the Workflow Insititute over the last couple of days. To begin with, two days ago, I got an email from Anne Henry at the Workflow Institute responding to this post, thanking me for spreading the use of the term “workflow learning” and sending me a white paper with more details about how they define the term. Delightful! Not only was somebody actually reading my blog; somebody official was reading it and responding to it.

    Later in the day, I get an email from Jay Cross himself. He apparently had just discovered my admittedly harsh critique of an article he wrote in e-Learn. Jay’s tone was pretty cordial and good-natured, especially given that he was responding to a post that called his article “annoying hype.” (And for the record, let me apologize publicly for my somewhat less than collegial tone. While I stand by the substance of my comments, I certainly could have made more of an effort to present my critique in a tone that invited dialogue.) At any rate, Jay let me know that he felt that there was more to his position than I had gleaned from his article, lamented that there was no place on my blog to comment on posts, and suggested that I give him a call. Again, wonderful! That’s what I would call a gracious response.

    Now, Jay did respond in his own blog before we had a chance to talk. All in all, it was a pretty gentle retort. While Jay made it clear that he is not going to apologize for being a visionary, he mostly took a “live and let live” position. Nevertheless, I do feel compelled to quibble with one particular sentence:

    The author goes on to explain that I am blissfully ignorant, misleading people with Panglossian optimism, and that Web Services has nothing to do with the future of IT and learning.

    Well, that’s not exactly what I said. I never suggested that web services has nothing to do with the future of IT and learning; rather, what I said was that web services are not sufficient to achieve the future that he projects. I still believe that. (I suspect that Jay does too; it just didn’t come out in his article.) I also certainly never suggested (or intended to suggest, anyway) that Jay was blissfully ignorant; to the contrary, I tried to make it clear that I generally like what he has to say (which is why his blog is on my blogroll). In fact, the reason his article got under my skin was precisely because I respected his work enough to hold him accountable for his words. I did suggest that that Jay’s optimism in the article was misleading, and that’s where the sound and fury came from.

    At any rate, I really can’t complain about the response, over all (and he gets extra credit in my book for using the word “Panglossian” gracefully in a sentence). Jay and I have since talked on the phone about exploring ways to continue this dialogue in a more direct manner; neither of us thinks that blogging about each other (or toward each other, or whatever it is that you do when you engage in the indirect dialogues that blogs allow) is the most productive way to dig into the issues. I’m not sure where we’ll end up on this, but regardless, Jay and his colleagues at the institute deserve credit for responding with class.

  • Annoying Hype

    In general, I like Jay Cross’ writings. While I have never personally met the guy, I find that his articles usually have something interesting and sensible to say. Which is why I’m so disappointed with his overly exhuberant fluff piece in e-Learn:

    “For some, the work of the future will resemble an elaborate, personalized video game front-end that’s connected to the physical operations of their company.

    Life will be simpler five years from now. We’ll be comfortable living in a world of organizations without bosses, computing without programmers, and webs without weavers. “

    And the lion will lie down with the lamb.

    All this bliss supposedly comes from web services. What are web services? At the root, web services are really just a better way for software developers to develop and maintain components of a large application or system. In the (really) old style of programming, (called procedural programming), there was no easy way to separate dependencies within software code. That meant if you changed one piece of the code it might have a ripple effect that broke things elsewhere and it was sometimes hard to predict in advance where those breakages would occur. In other words, modifying large programs was hard and took a very long time (and cost a lot of money). Then along came object-oriented programming. In this world, you could take a piece of the software and wrap it up in a kind of a package, or “encapsulate” it. With encapsulation, you write a list of all the communications (commands and responses, basically) that your object understands. Once that’s done, then you can change the code inside the object all you want, and as long as its methods of communicating with the rest of the software don’t change, then nothing will break. With software objects, modifying large programs is still hard (in fact, in some ways it’s harder, since object-oriented programming requires more expertise and skill than procedural programming), but it often takes skilled programmers a lot less time to do the job.

    Web services can be thought of, in part, as a new wrinkle on encapsulation that makes it easier to keep the various parts of your program stored on different computers. And because web services also include some other nifty features (like auto-discovery, which lets one software component advertize to other components what it does and what commands and responses it understands), web services make it easier for programmers to create new programs out of pieces of the old programs much more quickly and easily, even if those old programs live on different computers supported by different companies in different parts of the world.

    But here’s the problem: Web services only solve a few of the many problems that have to be solved in order to reach Jay’s paradise. The harder problems in designing software that really changes the world are always the ones that revolve around what the humans actually need the software to do. In order for applications to be able to help all knowledge workers throw off the shackles of command-and-control and respond in concert in real time, we need to have some idea of how human beings would work the way that Jay describes if only the software would create the necessary environment. This is a very, very, very hard problem. And web services do nothing to solve it.

    Jay’s way of dealing with it is by gesturing toward emergent behavior, which is the notion that a system of independent agents (in this case, knowledge workers), can spontaneously develop organized positive behaviors without any clear directive or conscious cooperation:

    Skeptical? You’re witnessing bottom-up decision-making in the swift turn of a school of fish but we’re not used to seeing it in business. MIT Professor Tom Malone equipped an audience with hand-held paddles whose position could be read by a computer. On the screen up front, he projected a flight simulator. A hundred people jointly took the controls of the plane and, against all expectation, flew the plane without a pilot and without a crash

    OK, admittedly, that’s pretty cool. But emergence is a new, complex, and tricky idea that we only have the vaguest idea of how to create on command. Does anybody really believe that having a few dozen people in a room fly a plane together is equivalent to having a few thousand people all over the world run a profitable corporation? Does anybody have any idea how to get from the success at the first thing to success at the second?

    So while I applaud Jay’s enthusiasm for new technologies, I wish he would take a chill pill and not wind people up about sexy ideas that are vastly easier to demo than they are to implement in the real world. I understand that he’s trying to get the whole “workflow learning” meme spreading as agressively as possible, and I support that. It’s a valuable way of framing performance support that may finally get non-trivial traction in the Enterprise. But really…

    For some, the work of the future will resemble an elaborate, personalized video game front-end that’s connected to the physical operations of their company.

    Bowling scores will be way up; miniature golf scores will be way down.

    *Sigh.*