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Clark Quinn’s Learnings about Learning

Representing openness

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I was asked about my thoughts on creative commons concepts:

“free resources that are available to users but that also come with the pretense that by sharing the material openly, users will be able to perhaps improve upon the original”

This is an interesting question, and it got me thinking about shared editing. Increasingly, it’s about representations. I use diagrams, but am trying to be more visual and include photos in my presentations, and of course I’ve been textual (life as an academic). Others are looking to video. Someone recently had a presentation at the Institute For The Future (which I missed, unfortunately) on how it’s media literacy that’s important, not just traditional textual literacy, and I have to fully agree.

So, increasingly it’s going to be about using web-based tools for creation and sharing. Rip/mix/burn! Wikis are important, but so are things like Google’s tools: open spreadsheets & documents, and diagrams (e.g. Gliffy. where BTW no one’s taken me up on collaborating, well that’s a learning too). Newer representations are possible, including 3D in Second Life, audiocasts, videocasts, photos, it’s all fair game via Flick’r, YouTube, etc.

However, I don’t believe in the teaching of particular applications. For instance, if you learned PowerPoint, the new version’s rearrangement could throw you for a loop unless you’ve used lots of apps and know your, so you can figure it out. But what if you’d learned it by rote (as at least one teacher at our elementary is doing)?

So, instead, I want to teach the principles of goal-oriented collaboration, the notion of finding important questions, gathering data, creating hypotheses, conducting experiments, writing up results, and sharing. With interim question, post thoughts, share, reflect, review, at every stage. Then, have them use different tools at different times with the same goals, so they abstract the principles and can carry them forward regardless of the latest tool du jour.

What are your thoughts?

Spores of Imagination

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A wise colleague of mine pointed me to this video of Will Wright talking about his new game Spore to the TED conference (I was invited once, years ago when I was in Australia, but it was a lot of money at the time, on an academic salary with the exchange rate then…). It’s a fascinating talk, covering the game design but also the philosophy behind it.

Will Wright, in case you don’t know, is the genius behind Sim City and The Sims, two famous games. He’s revered among game designers because his games are complete leaps to a new game space, and successful. He has a talent for taking something he finds interesting, building a model (a simulation is just a model, a scenario is when you put it in an initial state and ask the player to take it to a goal state, and a game is when you tune that experience until it’s engaging), and then making the experience of manipulating the model into a game. In particular, one of the hallmarks of his work is his ability to tune it in unique and non-obvious ways (e.g. monsters coming in to smash your cities) to create a compelling and yet thought-provoking experience.

Here he talks about the game design, but couples it to important issues. How games are toys that can help us learn. It’s the final statement that resonates, about using this new game as a tool to foster long-term thinking. Really, that’s what I’m on about, using games as tools to develop new ways to think. And here’s a master. Enjoy, and reflect.

Virtual World Learning

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Yesterday I had the privilege of an in-world meeting with my colleague Claudia L’Amoreaux, who’s now a major part of Linden Lab‘s education efforts with Second Life. Second Life, if you’ve been in a cave the past few years, is the first major successful virtual world. It’s a massively multi-player online environment, but it’s not a role-playing game, as there are no quests or NPC (non-player characters). In 2nd Life, you can build things, earn ‘money’ (Linden dollars; which have a cash exchange value for US$), and of course socialize. Many companies have set up places or islands in 2nd Life, and are holding learning events or creating learning places.

It was very gracious of her to give me time in her busy schedule, and I’m grateful because she refined and extended my understanding. I’ve talked before about virtual world learning affordances, so I let me focus on the new understandings.

First, I have to say that she didn’t change my fundamental take on the affordances. It is very much about spatial opportunity, both in place and in 3D representations. These are not trivial at all, but instead may have unique appeal for special needs rather than being general purpose. When those are the need, however, the virtual world is very compelling.

A second issue is one that I undervalued, and that’s the ability to represent yourself how you’d like to be seen, in more ways than one. The overhead is somewhat high, but I think I didn’t really ‘get’ how important this can be, as Tony O’Driscoll has let us know. There was another facet of this, however, which I truly missed, and that’s the ability to create a place to meet (if you own land, or you can presumably choose a meeting place that represents the ‘atmosphere’ you want to convey).

What Claudia helped me see is that the ability to create a look and environment serves as a powerful channel to communicate much information. She teleported me to a location she’s created to hold meetings with people and it’s a beautiful, comfortable place, very relaxing. She showed me Pathfinder Linden‘s in-world place which is very different, full of cool toys.

She emphasized the informal learning potential in such spaces, which can be building things to share if you’re appropriately skilled, or taking people to places with appropriate things. In formal learning, it’s more about, as said above, spatial and immersive experience. She mentioned learners making a ‘film’ of a book about a child soldier, and it did occur to me that if you have internet access, you could create a set and have actors and record it with much less overhead than a live movie. So there are some barrier-reductions involved in this world too.

So, all in all, I have to say I’ve underestimated virtual worlds. By the same token, I still think they’ve been over-hyped. Claudia’s lasting message, however, is intriguing. She said that when the world wide web was established, no one truly imagined how it would grow. Claudia sees virtual worlds as a similarly new platform with as yet unexplored potential, where we’re still repeating old activities with the new technology. Which we know is historic precedent, and gives us reason to pause in judgment.. As she said, no one she knows who’s really gotten into it has subsequently ‘got out’.

At the DevLearn conference, Paul Saffo pointed out that our technology expectations are linear, but the capabilities grow in a non-linear manner. Consequently, we’re liable to find that such innovations underperform our expectations initially, and outperform as they reach critical mass. And I know that my old boss/mentor/colleague Joe Miller and the folks within Second Life are continually driving new innovations, so we can probably expect things to get simpler, more powerful, or both. So there’re unexplored opportunities. I’ll stick with my (modified) position now, but eagerly await new understandings.

Meta-learning and the future

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Sky’s blog post on meta-learning is sparked by Jessica Margolin’s post on helicopter parenting. Now we’re talking! I’m probably a bit guilty, frankly, of hovering, but I do also try and point out the meta-lessons on process, and model what I’m doing.

But Sky pulls out the important bit, that the skills going forward aren’t the skills that schools are focused on. It’ll be about process, about creativity. As Einstein said: “We can’t solve problems by using the same kind of thinking we used when we created them.”

I’d suggest that we do face some quite serious problems, for instance there was an interesting debate on a discussion list I belong to, sparked by an animated editorial on our current state. One side was saying we needed to slow down and evaluate our values. The other side said that we weren’t giving enough credit to our ability to innovate. Where do you come down on this?

I’ve suggested the type of curriculum I think we need. Of course, if we follow Einstein’s dictum, once we make that step, we’ll create new problems, and then we’ll need the step after. Not that I know what that step is…

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.