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Clark Quinn’s Learnings about Learning

Non-invasive Brain Surgery

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Changing behavior is hard. The brain is arguably the most complex thing in the known universe. Simplistic approaches aren‘t likely to work. To rewire it, one approach is to try surgery. This is problematic for a several reasons: it‘s dangerous, it‘s messy, and we really don’t understand enough about it. What‘s a person to do?

Well, we do know that the brain can rewire itself, if we do it right. This is called learning. And if we design learning, e.g. instruction, we can potentially change the brain without surgery. However, (and yes, this is my point) treating it as anything less than brain surgery (or rocket science), isn‘t doing justice to what‘s known and what‘s to be done.

The number of ways to get it wrong is long. Information dump instead of skills practice. Massed practice instead of spaced. Rote knowledge assessment. Lack of emotional engagement. The list goes on. (Cue the Serious eLearning Manifesto.) In short, if you don‘t know what you‘re doing, you‘re likely doing it wrong and are not going to have an effect. Sure, you‘re not likely to kill anyone (unless you‘re doing this where it matters), but you‘ll waste money and time. Scandalous.

Again, the brain is complex, and consequently so is learning design. So why, in the name of sense and money, do we treat it as trivial? Why would anyone buy a story that we can achieve anything meaningful by taking content and adding a quiz (read: rapid eLearning)? As if a quiz is somehow going to make people do better. Who would believe that just anyone can present material and learning will occur? (Do you know the circumstances when that will work?) And really, throwing fuzzy objects around the room and ice-breakers will somehow make a difference? Please. If you can afford to throw money down the drain (ok, if you insist, throw it here ;), and don‘t care if any meaningful change happens, I pity you, but I can‘t condone it.

Let‘s get real. Let‘s be honest. There‘s a lot (a lot) of things being done in the name of learning that are just nonsensical. I could laugh, if I didn‘t care so much. But I care about learning. And we know what leads to learning. It‘s not easy. It‘s not even cheap. But it will work. It requires good analysis, and some creativity, and attention to detail, and even some testing and refinement, but we know how to do this.

So let‘s stop pretending. Let‘s stop paying lip-service. Let‘s treat learning design as the true blend of art and science that it is. It‘s not the last refuge of the untalented, it‘s one of the most challenging, and rewarding, things a person can do. When it‘s done right. So let‘s do it right! We‘re performing brain surgery, non-invasively, and we should be willing to do the hard yards to actually achieve success, and then reap the accolades.

OK, that‘s my rant, trying to stop what‘s being perpetrated and provide frameworks that might help change the game. What‘s your take?

Showing the World

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One of the positive results of investigations into making work more effective has been the notion of transparency, which manifests as either working and learning ‘out loud‘, or in calls to Show Your Work.  In these  cases, it’s so people can know what you’re doing, and either provide useful feedback or learn from you.  However, a recent chat in the L&D Revolution group on LinkedIn on Augmented Reality (AR) surfaced another idea.

We were talking about how AR could be used to show how to do things, providing information for instance on how to repair a machine. This has already been seen in examples by BMW, for instance. But I started thinking about how it could be used to support education, and took it a bit further.

So many years ago, Jim Spohrer proposed  WorldBoard, a way to annotate the world. It was like the WWW, but it was location specific, so you could have specific information about a place  at the place.  And it was a good idea that got some initial traction but obviously didn’t continue.

The point, however, would be to ‘expose’ the world. In particular, given my emphasis on the value of models, I’d love to have models exposed. Imagine what we could display:

  • the physiology of an animal we’re looking at to flows of energy in an ecosystem
  • the architectural or engineering features of a building or structure
  • the flows of materials through a manufacturing  system
  • the operation of complex devices

The list goes on. I’ve argued before that we should expose our learning designs as a way to hand over learning control to learners, developing their meta-learning skills. I think if we could expose how things work and  the thinking behind them, we’d be boosting STEM in a big way.

We could go further, annotating exhibits and performances as well.  And it could be auditory as well, so you might not need to have glasses, or you could just hold up the camera and see the annotations on the screen. You could of course turn them on or off, and choose which filters you want.

The systems exist: Layar commercially, ARIS in the open source space (with different capabilities).  The hard part is the common frameworks, agreeing what and how, etc.   However,  the possibilities to really raise understanding is very much an opportunity.  Making the workings of the world visible seems to me to be a very intriguing possibility to leverage the power we now hold in our hand. Ok, so this is ‘out there’, but I hope we might see this flourishing quickly.  What am I missing?

Learning by experimenting

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In some recent work, an organization is looking to find a way to learn fast enough to cope with the increasing changes we’re seeing.  Or, better yet, learn  ahead of the curve. And this led to some thoughts.

As a starting point, it helps to realize that adapting to change is  a form of learning. So, what are the individual equivalents we might use as an analogy?  Well, in known areas we take a course.  On the other hand, for self-learning, e.g. when there isn’t a source for the answer, we need to try things.  That is, we need a cycle of: do – review -refine.

In the model of a learning organization, experimentation is clearly listed as a component of concrete learning processes and practices.  And my thought was that it is therefore  clear that any business unit or community of practice that wants to be leading the way needs to be trying things out.

I’ve argued before that learning units need to be using new technologies to get their minds around the ‘affordances’ possible to support organizational performance and development.  Yet we see that far too few organizations are using   social networks for learning (< 30%), for example.

If you’re systematically tracking what’s going on, determining small experiments to trial out the implications, documenting and sharing the results, you’re going to be learning out ahead of the game. This should be the case for all business units, and I think this is yet another area that L&D could and should be facilitating.  And by facilitating, I mean: modeling (by doing it internally), evangelizing, supporting in process, publicizing, rewarding, and scaling.

I think the way to keep up with the rate of change is to be driving it.  Or, as Alan Kay put it: “the best way to predict the future is to invent it”.  Yes, this requires some resources, but it’s ultimately key to organizational success, and L&D can and should be the driver of the process within the organization.

The new shape of organizations?

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As I read more about how to create organizations that are resilient and adaptable, there’s an interesting emergent characteristic. What I’m seeing is a particular pattern of structure that has arisen out of totally disparate areas, yet keeps repeating.  While I haven’t had a chance to think about it at scale, like how it would manifest in a large organization, it certainly bears some strengths.

ConnectedCompanyDave Grey, in his recent book The Connected Company  that I reviewed, has argued for a ‘podular’ structure, where small groups of people are connected in larger aggregations, but work largely independently.  He argues that each pod is a small business within the larger business, which gives flexibility and adaptiveness. Innovation, which tends to get stifled in a hierarchical structure, can flourish in this more flexible structure.

OrganizeForComplexityMore recently, on Harold Jarche‘s recommendation, I read Niels Pflaeging’s  Organize for Complexity, a book also on how to create organizations that are high performance.  While I think the argument was a bit sketchy  (to be fair, it’s deliberately graphic and lean), I was sold on the outcomes, and one of them is ‘cells’ composed of a small group of diverse individuals accomplishing a business outcome.  He makes clear that this is not departments in a hierarchy, but  flat communication between cross-functional teams.

And, finally, Stan McChrystal has a book out called Team of Teams,  that builds upon the concepts he presented as a keynote I mindmapped previously. This emerged from  how the military had to learn to cope with rapid changes in tactics.  Here again, the same concept of small groups working with a clear mission and freedom to pursue emerges.

This also aligns  well with the results implied by Dan Pink’s Drive, where he suggests that the three critical elements for performance are to provide people with important goals, the freedom to pursue them, and support to succeed. Small teams fit well within what’s known about the best in getting the best ideas and solutions out of people, such as brainstorming.

These are nuances on top of Jon Husband’s Wirearchy, where we have some proposed structure around the connections.  It’s clear that to become adaptive, we need to strengthen connections and decrease structure (interestingly, this also reflects the organizational equivalents of nature’s extremophiles).  It’s about trust and purpose and collaboration and more.  And, of course, to create a culture where learning is truly welcomed.

Interesting that out of responding to societal changes, organizational work, and military needs, we see a repeated pattern.  As such, I think it’s worth taking notice.   And there are clear L&D implications, I reckon. What say you?

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