This morning Elliott interviewed Cathy Casserly from Creative Commons and Dean Kamen. Cathy was a passionate advocate for openness and sharing. She talked about going further into learning, and I was reminded about Project Tin Can, making a more general learning path. Dean recited his interesting childhood and then launched into his inspiring project to make science cool again.
Michio Kaku keynoted the DevLearn keynote today. With his signature phrase,”in the future…”, he covered new techs and made tentative connections to learning.
Yesterday I attend SDL’s DITAFest. While it’s a vendor-driven show, there were several valuable presentations and information to help get clearer about designing content. And we do need to start looking at the possibilities on tap. Beyond deeper instructional design (tapping into both emotion and effective instruction, not the folk tales we tell about what good design is), we need to start looking at content models and content architecture.
Let me put this a bit in context. When I talk about the Performance Ecosystem, I’m talking about a number of things: improved instructional design, performance support, social learning and mobile. But the “greater integration” step is one that both yields immediate benefits, and sets the stage for some future opportunities. Here we’re talking investing in the underlying infrastructure to leverage the possibilities of analytics, semantics and more, and content architecture is a part of that.
So DITA is Darwin Information Typing Architecture, and what it is about is structuring content a bit. It’s an XML-based approach developed at IBM that lets you not only separate out content from how it’s expressed, but lets you add some semantics on top of it. This has been mostly used for material like product descriptions, such as technical writers produce, but it can be used for white papers, marketing communications, and any other information. Like eLearning. However, the elearning use is still idiosyncratic; one of the top DITA strategy consultants told me that the Learning and Training committee’s contribution has not yet been sufficient.
The important point, however, is that articulating content has real benefits. A panel of implementers mentioned reducing tool costs, reduced redundancy savings, and decreasing time to create and maintain information. There were also strategic benefits in breaking down silos and finding common ground with other groups in the organization. The opportunity to wrap quality standards around the content adds another opportunity for benefits. Server storage was another benefit. As learning groups start taking responsibility for performance support and other areas, these opportunities will be important.
And, the initial investment to start focusing on content more technically is a step along the path to start moving from web 2.0 to web 3.0; custom content generation for the learner or performer. A further step is context-sensitive customization. This is really only possible in a scalable way if you get your arms around paying tighter attention to defining content: tagging, mapping, and more.
It may seem scary, but the first steps aren’t that difficult, and it’s an investment in efficiencies initially, and into a whole new realm of capability going forward. It may not be for you tomorrow, but you have to have it on your radar.
In case you didn’t see it, eLearn Mag has posted my book review of Mark Warschauer’s insightful book, Learning in the Cloud. To quote myself:
This is … a well-presented, concise, and documented presentation of just what is needed to make a working classroom, and how technology helps.
As one more teaser, let me provide the closing paragraph:
The ultimate message, however, is that this book is important, even crucial reading. This is a book that every player with a stake in the game needs to read: teachers, administrators, parents, and politicians. And not to put too delicate a point on it, this is what I think should be our next “man in the moon” project; implementing these ideas comprehensively, as a nation. He’s given us the vision, now it is up to us to execute.
I most strongly urge you, if you care about schooling, to read the book, and then promote the message.
I attended the CLO Symposium with my ITA colleagues Jay Cross and Jane Hart. It was an interesting event, with a theme of “Game-Changing Learning: Development for the New Normal“, held at a classy venue on the beach, and was well-organized. (You can see Jay’s writeup here.) And the keynotes that I saw were in synch: Stephen Covey talked about the need for trust and Jon Katzenbach on how to build culture were both excellent, as was Dan Pontefract’s story on making collaboration intrinsic to Telus. At a lower level, however, the conference felt mired in the past.
Jay, Jane, and I ran a unpanel where we took questions from the audience and took turns answering it. Some folks even had trouble with the format, apparently! We got questions about how the role of the learning unit changes, about myths and new tools, and about measurement. Our riff inspired some subsequent inquiries if we could assist. Well, but of course!
A lot of the other sessions also seemed to deal with measurement. A special lunch was held specifically around creating a standard set of measurements: effectiveness, efficiency, and business impact. While the latter is business specific, the other two could be handled. Efficiency tends to mean things like amount per hour of training, etc. Effectiveness was less clear, but I’m afraid we’d see pre-post test messages instead of number of people completing the competency test (happy to be wrong). My problem here is that this stuff shouldn’t be a topic in 2011, it should be already well-practiced and in the repertoire. We should be thinking about how to start tracking meaningful activity in social networks, the value of performance support and more, not old stuff about courses. And, how to tie it back to important deltas in organizational performance.
As for addressing the social and informal metrics, while I addressed this a bit earlier, let me go a bit further. If you are putting in performance support (e.g. a portal, but *ahem*, well-designed) or social network, you should be asking yourself what it should be achieving. Is it closing more sales? Generating higher revenue per sale? How about less time spent on customer calls? If you put in an HR portal, you should expect less calls to HR. If you put in a social network among sales folks, you might expect a higher percentage of closing. Figure out what change this should affect, and then find a way to measure it. Which should be the indicator that you have a problem in the first case!
Which is not to say there weren’t good topics on tap too: leadership development for agility, bridging the gap between IT and the learning unit, informal learning, etc. But when other topics are ‘how to talk to executives’, in- or out-sourcing talent, and on-demand training, it’s clear we’re not where we can, and should, be.
“The future is already here, it’s just not very evenly distributed”, as William Gibson has said, but I guess my concern is with some of what is considered game-changing in an era where the new normal is continual innovation and perpetual beta. Things are moving too fast not to already have mastered the basics of measurement, and be thinking about adapting. The ability to talk ‘business’ should be a pre-requisite for the job, and the strategic issues need to be culture and collaboration. We’re getting there, but then patience has never been one of my strong suits ;).
The travel schedule is booting up again, and I’ll be hither and yon speaking about this and that for a good part of the coming two months. More specifically:
That may seem like a lot (and it is), but traveling on only one continent will seem easy after this past May-August ;). I hope to see you at one or more of these learning events!
Recently, a colleague videotaped me responding to some questions about how mobile could change learning. I find I riff a bit in such situations, and one of the ideas I had then is something I wanted to explore a little more. It had to do with context.
What we do, in so many of our formal learning designs, is create artificial contexts. In face-to-face learning, we’ll do role-plays, and in online learning we’ll create simulations or games. Now, this makes sense; you want to do practice away from real performance if the consequences are costly. Yet other times, e.g. after the learning experience, they end up performing (and, too often, before they’ve received sufficient practice because of time and money constraints as well as just bad habits). A further opportunity is that out there in the real world, there may be some contexts that the learner comes across that may be relevant, and we could extend the learning experience.
Context-aware systems give us a chance to do something more here. If you’re performing a task that’s related to some formal learning, your system could be equipped to notice, and bring in some appropriate content. This was the promise of electronic performance support systems, and we can now start doing it not just in custom-designed environments, but we can connect context clues to associated content with semantic rules. So, if you’re in a coaching meeting, the system could prepare you beforehand, provide support during, and some reflective evaluation afterward. Say, a checklist.
Similarly, we can notice the context of the learner and even if it’s not a performance situation, if there’s a meaningful connection (I didn’t want to use semantic again :), the system could provide some mention of the linkage, which reactivates and contextualizes the learning, making it more likely to be retained and transferred.
Mobile, of course, decouples this capability from the desktop, and increases the likelihood that the connection opportunities are capitalized on, and even the performance support model can be brought to bear. The two necessary components are the context-awareness (done via GPS, calendar) and semantic linkages (done with tagging). This is no longer rocket science, just a product of decent task analysis and content engineering.
I reckon it’s time that we can, and should, lift our game a little to start looking at more sophisticated support technologies. If improving performance matters…and it should.
The notion that soon everything will be in the cloud, and we’ll just use an interface surface near us is not new. The notion is that the technology will recognize you and present your environment, ready for you to accomplish your goals. This is a nice idea, and I can see it working, but it’s not trivial.
Contrast this to the element that Judy Brown talks about as important component of mobile learning. For her, mobile devices have to be something you’re familiar with and have with you all the time. And that, to me, is the sticking point.
With an interface surface you come upon, would you necessarily recognize the different ways the interface would manifest? You don’t want a big touchscreen (despite Minority Report imaginings) for very complex work, because the research shows your arms fatigue too quickly. So you might have a keyboard on some devices. And the variety could be high. And, yes, it’s your interface, but with all the different possible form-factors, could you make it comprehensible? And you’re still at the mercy of availability of surfaces (kinda like waiting in line for computers to check email at conferences has been).
Now, I can see having a mobile device and then using an accessible interface that recognizes you by the device proximity, so you’re not stuck. And I can imagine that it would be possible to make a scalable interface (just not necessarily easy). I do wonder, however, about some surfaces being so designed for aesthetics that the usability is compromised (c.f. The Design of Everyday Things).
And, particularly for my notion of slow learning (which I need to augment with ubiquity and personalization – quick, I need a new phrase! :), the ability for a device to be with you may be required to do the teachable moment thing. That is, having a context-sensitive device right that at the appropriate place and time may be needed to really develop us in the ways we deserve.
So I don’t take that vision of ubiquitous computing surfaces at face value, I think that there are some reasons why mobile devices may still make sense. Which isn’t to say there’s not a way, but I’m still holding out for something with me.
Electronic Performance Support Systems are a fabulous concept, as pioneered by Gloria Gery back in the early 90’s. The notion is that as you use a system, and have entries or decisions to make, there are tools available that can provide guidance: proactively, intelligently, and context-appropriate. Now, as I heard the complaint at the time, this would really be just good interface design, but the fact is that many times you have to retrofit assistance on top of a bad design for sad but understandable reasons.
The original were around desktop tasks, but the concept could easily be decoupled from the workplace via mobile devices. One of my favorite examples is the GPS system: the device knows where you are, and where you want to go (because you told it), and it gives you step by step guidance, even recalculating if you make a change. Everything from simple checklists to full adaptive help is possible, and I’ve led the design of such systems.
One of the ideas implicit in Gery’s vision, however, that I really don’t see, is the possibility of having the system not only assist you in performing, but also help you learn. She talked about the idea in her book on the subject, though without elaborating how that would happen, but her examples didn’t really show it and I haven’t seen it in practice in the years since. Yet the possibility is there.
I reckon it wouldn’t really take much. There is (or should be) a model guiding the decisions about what makes the right step, but that’s often hidden (in our learning as well). Making that model visible, and showing how it guides the support and recommendations that are made, could be made available as a ‘veneer’ over the system. It wouldn’t have to be visible, it could just be available at a click or as a preference for those who might want it.
Part of my vision of how to act in the world is to ‘learn out loud’. Well, I think our tools and products could be more explicit about the thinking that went into them, as well. Many years ago, in HyperCard, you could just use buttons and field, but you could open them up and get deeper into them, going from fixed links to coded responses. I have thought that a program or operating system could work similarly, having an initial appearance but capable of being explored and customized. We do this in the real world, choosing how much about something we want to learn (and I still want everyone who uses a word processor to learn about styles!) about something. Some things we pay someone else to do, other things we want to do ourselves. We learn about some parts of a program, and don’t know about others (it used to be joked that no one knows everything about Unix, I feel the same way about Microsoft Word).
We don’t do enough performance support as it is, but hopefully as we look into it, we consider the possible benefits of supporting the performance with some of the underlying thinking, and generating more comprehension with the associated benefits that brings. It’s good to reflect on learning, and seeing how thinking shapes performance both improves us and can improve our performance as well.
Recently, I’ve been hearing quite a bit of concern over the possibility that reliance on digital, and increasingly mobile, technology may make us stupider. And I don’t think this is just easy to dismiss. In a sense, it could be a case of learned helplessness, where folks find themselves helpless because after using the tools, folks might not have the information they need when they don’t have the tools.
Recently announced research shows that folks change what they remember when enabled with search engines: they don’t remember the data, but instead how to find it. Which could be a problem if they needed to know the data and are not digitally enabled in some context.
As has also been conveyed to me as a concern is whether folks might not engage in learning about their environs (e.g. when traveling), and in other ways miss out on opportunities to learn when dependent on digital devices. Certainly, as I’ve mentioned before, I’ve been concerned about how disabled I feel when dissociated from my digital support (my external brain). Yet is there a concern?
My take is that it might be a concern if people are doing it unconsciously. I think you could miss out (as m’lady points out when I am reading instead of staring out the window every moment as we take the train through another country :) on some opportunities to learn.
On the other hand, if you are choosing consciously what you want to remember, and what you want to leave to the device, then I think you’re making a choice about how you allocate your resources (a ‘good thing’). We do this in many ways in our lives already, for instance how much we choose to learn about cooking, and more directly related, how much to learn about how to do formatting in a word processing program.
Yes, I’ve been frustrated without my support when traveling, but that’s chosen (which does not undermine my dismay at the lack of ability to access digital data overseas). I guess I’m arguing for chosen helplessness :). So, what are you choosing to learn and what to devolve to resources?