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2007 Reflections

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It was an interesting year, starting with some sojourns in Taiwan and Norway, and ending with some time in Colombia and Denmark. That has been my most international year yet with Quinnovation, and I hope it’s a sign that a deeper approach to elearning is being recognized everywhere as the way to go.

I hoped that this past year would be the year of the model, and did my best to make it happen. Interestingly, I had lunch today with a guy who has had great success training programming and has made some initial moves to eLearning. It sounded very much like he was proving my proposed approach (providing the model, some examples, and then picking a series of disparate problems to practice that drill applying the model in different practices). This means you don’t have to train all the possible situations, just a representative-enough selection to facilitate abstraction and transfer. There’re details of course, such as ensuring that the alternatives to the right answer address the reliable misconceptions, having the feedback explicitly refer to the model, etc, but it should be a most effective way to train.

I also felt that, this year, (serious) games, aka ILS, moved firmly into the mainstream. Similarly, it’s becoming clear that mobile is how where games were a year or two ago, poised for a push into the spotlight, to be followed by mainstream in the near future. I’m hoping that a few other clear opportunities also will soon see attention, such as effective portals, structured content and single-sourcing, etc. It’s time to fully populate the performance ecosystem.

Which, of course, requires thinking broader than just training, and really just learning. It’s not about learning, after all, it’s about doing. Of course, making that transition on thinking requires some transitions in other organizational mindsets and cultures. I did see more of it this year, and really felt like the whole notion of strategic elearning was beginning to be heard. I do recommend, BTW, Marc Rosenberg’s Beyond eLearning, which does a nice job of setting up that way of thinking.

Overall, I had great conversations with my colleagues, and many of you, over Immersive Learning Simulations, Mobile Learning, and more. I also had the chance to work on some very interesting projects, continuing to push the envelope over how we use technology to support people achieving their goals. I hope that the next year continues to provide deep learning, wise use of technology, and meaningful outcomes for us all, and may it be our best year yet. Happy New Year!

Blended Doing

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I was reading last week’s issue of the Economist (I don’t always agree with them, but their analysis is quite enlightening) including their technology quarterly, and a really interesting thought struck me. The issue was rife with fascinating advances, but an overarching pattern emerged.

Let me set some context: in elearning we talk about blended learning, and I regularly say it’s not about learning, it’s about doing. Really, the view of elearning I’m trying to propagate is more like blended doing, where technology partners with us to make a more effective problem solver. This comes from Don Norman‘s point that from the problem’s point of view, a human augmented by technology is a more fearsome force than just the human alone.

Look, our brains are good at pattern matching (see above) and big picture, but bad at remembering rote things and details. Technology is just the opposite! That’s what performance support is all about. Of course, sometimes our brains need major skill shift changes, and there’s a role for courses, but some times we need information, and sometimes we need people, and sometimes we need support for massive computation.

Jim Schuyler has a mechanism he uses to authenticate comments on his blog. With Captcha, it’s the familiar challenge/response where you type in the familiar image of letters, with a twist. There’re two words, and while the first is known to the system, the second comes from some OCR text with a word it’s not sure of. So not only are you showing you’re human, you’re assisting the digital archiving of some important text.

The Economist mentioned this type of blending that gets people to do a difficult task for computers in what otherwise is a computing intensive task. They mentioned the ESP game where people playing also get some work done, in this case tagging images on the web.

They also talked about evolutionary algorithms (I first learned about them through John Holland’s work on genetic algorithms at UMichigan) to design things. You match a design problem to a set of parameters that then try to evolve to solve the problem, using mutation and selection to populate the solution space. Holland et al were looking to match how the brain works (getting solutions similar to those with neural nets, but with a less directly mappable approach), but others are just attacking design challenges.

Where a human would get massively bored searching through every permutation, this approach turns it into a computation problem and the computer merrily works away. There’s no guarantee of solution, but it really gets into situations where brute force can work and elegance might not. They mention some great outcomes, including better wireless antennas, optic cable designs, and more.

The point being to consider a different point of view, not of the performer, but of the task, and what’s the best solution to achieving the goal? A clue: if it requires rote-memorization on the part of the human, particularly of a set procedure, it probably should be automated. Let computers do what they do well, and let us do what we do well!

So, think of the tasks your performers need to accomplish, and don’t be afraid to think out of the box when you look for solutions. I’ll suggest that what will make a difference going forward isn’t focused on knowledge, but on problem-solving and innovation.

Clive on resources vs instruction

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That may not be how he’d think of it, but Clive Shepherd’s got a post about whether to provide well-structured learning solutions (using a balanced meal metaphor) or a suite of resources (I think of a buffet to extend the metaphor). My suggestion is to have the buffet, with some support on choosing a balanced meal. That is, don’t assume the learner’s good at self-learning, but don’t force them into a cookie-cutter solution either.

Why don’t we spend more effort on helping learners acquire self-learning skills? It seems such an obviously valuable investment that Jay Cross and I spent some time carrying the torch and still feel it’s valuable (he’s got a whole chapter on it in his Informal Learning book). If you don’t, I reckon you’re not equipping your workers for ultimate success. It’s like leaving money on the table.

Neural meta-learning

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Getting my PhD where they arguably started the field of cognitive science, I got exposed to philosophy, sociology, anthropology, and neuroscience as well as psychology. One of the blogs I like to follow is Eide Neurolearning, and in their most recent post, they talk about complex thinking. The take-home I’m fascinated by is this:

Maybe basic skill sets for schooling should not be thought of as the 3 R’s (reading, writing, and ‘rithmetic), but rather beyond the memorization of facts and procedures, the efficient working of working memory and long term memory, the strategic use of brain resources for dynamic problem solving and multi-tasking, and the organization of ideas and perceptions for all types of output: verbal as well as non-verbal.

I’m not quite sure, off-hand, how we might teach the efficient working of memory (though they may be exercised, ala Brain Age), but I strongly support guided practice in problem-solving (which David Jonassen elegantly talks about; see his forthcoming chapter in Michael Allen’s eLearning Annual from Pfeiffer). It’s clear to me that the curriculum we need to worry about is about not passing knowledge tests (see Ken Carroll on the Chinese system).

What’s nice here is some evidence about the types of things we can and cannot do, and what the implications are for learning. I think this is relevant from K-12 to lifelong learning, and corporate learning as well. When we need to innovate and problem-solve, and I argue we do, then we better make sure we are developing the skills of individuals. Learn on!

Knowledge marketing

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Brent Schenkler points out this connection: using web 2.0 tracking software to find out who’s commenting to whom. It’s about a company with a technology that lets you track who’s talking about what and identify the top talkers (for marketing purposes; presumably to know who to seed with information/product). Brent’s interesting point is that such technology could be used internally to track who’s talking about what within the company, and it’s a great idea. He’s talking about measuring learning outcomes but I see it more as a knowledge management tool to see who knows what.

The problem I see is that the technology first requires you to identify a topic that you want to track. Of course, you could put in a series of words or phrases of interest to the company, but how do you find what’s emergent and new in the conversations? There are KM tools that check your email to see what you know (and with ways to avoid the obvious concern about having your email checked), but your blog posts and comments, wiki edits, etc are another way to look at what you talk about (and, presumably, know).

So, a very interesting and eye-opening perspective on how we might look for who really knows what.

What did I learn about learning in 2007?

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This is the Learning Circuit‘s Blog Big Question of the Month. It caused me to go back and look at what I blogged about this past year. I talked a lot about mobile (rightly so), and of course about games, but what struck me as I read was the regular occurrence of talking about models. When I got near the beginning of the year, I found that I’d suggested that it should be the Year of the Model, so that’s it, a self-fulfilling prophecy.

The point is that we don’t use conceptual/mental models enough in our learning and training (as I was just complaining in a project on training call answering). And we can. Increasingly, the power of visualization is being understood and taken advantage of. But that’s only part of the benefit. The notion of thinking in terms of systems and causal relationships is at core. I knew it before, but it’s been something I’ve been thinking about more, and wishing I had a way to work on more.

The potential benefits are big: while we might need to spend a bit more time to ensure we get the models, and communicate them, what we stand to gain are reduced time in training (fewer examples and practice needed), and what should be big wins in terms of retention and transfer, as well as flexibility to deal with situations that we didn’t anticipate.

As Karyn Romeis points out, it’s not like it’s a big new thing I learned, it’s just an increasing awareness that it’s a big untapped opportunity.

Reflecting and data

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My Mom’s been here the past few days visiting (hence the lack of action here). She hadn’t been up in a long time since my Dad wasn’t strong enough to travel, and after he passed away she’s been afraid to leave since she’s trying to sell her mobile home. However, I finally convinced her she didn’t have to be around for the place to sell. She had a great time, having been afraid the logistics would be difficult, but they weren’t.

It’s been a time for a multitude of reflections, about aging, slowing down, but also about learning and trying to be wiser. Age brings gifts as well as infirmities. If you pay attention (and that can be a big if), you have the opportunity to learn from the events in your life, and also across them. Most of us do the one, but I think the larger one, looking for patterns, is less ubiquitous.

Speaking of looking for patterns, I was reminded of the value of collecting data. On a project I learned about the Personal Software Process (PSP) from Carnegie Mellon’s Software Engineering Institute, which is about documenting your estimates, your actual work effort, and then the Team Software Process (TSP) where within the team you circulate your work to find errors, and document those too. The point is to improve your estimates, and your code. The interesting thing is that there’s no reason that applies only to software! They say that the overhead is more for a couple of weeks, but then drops down. I confess I haven’t tried it, but that’s partly because what I’m doing varies so much I can’t figure out how to categorize it.

Ideally we have people to work with who can provide good feedback, but that’s not always possible or easy. I think one of the things about software is the ‘cowboy’ mentality where they crank out code without reflection and often without review. Extreme programming has helped, and recently someone posted about using that approach in elearning design. I’m having a senior moment remembering who said it, but it’s an idea worth thinking about. Speaking of senior moments, I learned the term from my Mom. Having come full circle, I’ll stop there.

Learning Futures

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Yesterday, the Institute For The Future held an event that focused on some work they’d done for the Knowledge Works foundation last year, looking 10 years out on Forces Affecting Education. They mapped 6 “Drivers of Change” (grassroots economics, smart networking, strong opinions strongly held, sick herd, urban wilderness, and the end of cyberspace) across 5 categories (family & community, markets, institutions, educators & learning, and tools & practices). I won’t define them, because you can look at the map yourself. A small group of us representing educators, learning technologists, learning foundation folks, learners, and parents, all concerned and informed, reacted as part of their ongoing research.

Some of the premises were an embarrassment of riches in resources and changes in the market dynamics, and there were some interesting juxtapositions. For instance, there were potentials for both coming together and increasing divisiveness. The ability to view different opinions is broader, but so is the ability to find people of like views and form a hermetic group. A related concern is one that’s been appearing in the Serious Games discussion list, about how to strike a balance between a Second Life and a first life. Some may be happier in an alternate persona, and others completely reject it.

Another issue was learning to learn (not only by me :). That is, given this breadth of channels, how does one learn effectively? We talked about where the locus of that responsibility, and I suggested that’s the new role of schools. A concomitant concern is how to make these resources accessible in a manageable way. One point made was about the differences between textual literacy and new literacies around interactive worlds. Are they equivalent?

Similarly, we touched on curriculum and pedagogy: what should we teach, and how should we teach it? We didn’t get to service learning (which I picked up on from another’s scribbling), but I think there’s a lot to say for that approach as a pedagogical approach which integrates assisting community, building skills in an integrated and useful way, and allowing values to emerge (back to wisdom).

I pointed out as a side note that everyone’s view of context-sensitivity has to do with location, but we’re ignoring time as an alternate opportunity, it’s not only where you are, but what you’re doing there. If you’re at a school for classes versus a sporting event, you might want different information. If you’re in an important meeting, it might not matter where it is so much as this is one that is about negotiation and you could use some support.

I don’t think there’s an easy answer to one of the underlying questions: we know we need change, but where is it going to come from? It’s coming in lots of small ways, but the ‘school’ is so institutionalized not only in law but in culture that it’s almost impossible to replace, yet it’s also remarkably resistant to change. So can it happen incrementally, or will it have to be cataclysmic?

Overall, there’s some great fodder for thought in the map, and opportunities to discuss it as well. What do you think is in the future of learning?

Performance

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Yesterday I was delighted to have lunch with Jay Cross, elearning guru, author, bon vivant, mentor, friend, (and now drummer). We’re almost neighbors (15 mi) and share passions for learning (and the meta-version), the capabilities technology can provide (not the technology itself), good food and drink. We’ve shared many adventures. I was helping him pick a new computer (a Mac), and of course having good conversation. Jay in WC

One of the things to talk about was performance support, as he’s writing an elegant update on the history and importance of this approach. It triggered many thoughts, not the least because performance support is the real focus of my mobile design piece I did for the recent eLearning Guild mobile research report.

It occurred to me that the new technologies make performance support even more effective. Semantic tagging, combined with user models, for instance, gives us opportunities to customize our support. As I’ve said before, mobile’s been a tale of convenience, making information available when needed, even if it’s a small screen, or over a small speaker, but the real opportunity still awaits: context sensitivity. We can track more than location, we can take a meeting, wrap support around it, and turn it into a learning event. Wrapping performance support around our lives, improving us as it improves our performance, is a true quantum shift in developing human capability.

Of course, we can also take performance support and meta- it, too! Our devices can not only support our performance on task, but support our performance on learning from the performance. It sounds a bit recursive, but I think that helping people become effective self-learners is a second great opportunity.

In Jay’s excellent book Informal Learning, he makes the point that “Dialogue is the most powerful learning technology on earth”, and it’s certainly true that when I get together with great thinkers, my own thinking gets sparked. I’m not a ‘big group’ person, but I love small conversations, and try to get together with folks and share conversation and comestibles. Let’s do lunch!

Critical Thinking

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Harold Jarche writes about the need for critical thinking, and has a map of the skills mapped to particular tools. I agree, and added:

I’ve been a fan of critical thinking for years, since I was a grad student and TA’d for Jean Mandler’s class on it. We used Diane Halpern’s book as a text, and that approach is still relevant.

I think we need to do more, however. Just having the tools isn’t enough. To develop new skills, we need support: motivation, examples, guided practice. The received wisdom is that it has to be layered on to authentic tasks. Of course, I say build it into a game! (there’s a bit in Quest).

I sympathize with [] cynicism, but I believe it can be taught, and there’s evidence to support my position. But we do it by making it a priority (before college), and making it part of what we test (meaning a whole new type of testing, but that’s what we need anyway).

We need to build critical thinking on top of our systems, into our content (Pellegrino’s brilliant article for the New Commission on the Skills of the American Workforce has a section on this, it’s available from this page), and make it a priority. Not to put too big a point on it, our future’s at stake!