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Clark Quinn’s Learnings about Learning

Better Benchmarking

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I was on a phone conversation and was asked whether I compared my clients against others in the business to help them figure out where they’re at. E.g. do I offer my partners the chance to benchmark. And after a bit of thought, I said that no, I didn’t, and explained why. Moreover, they found my answer intriguing, so I thought I’d share it with you.

So, as I’ve said before, I don’t like best practices. In fact, as I’ve written before, I think we shouldn’t benchmark ourselves against others. That’s a bad practice. Why? Because then we’re comparing ourselves against a relative measure. And I think we should be comparing ourselves to a principled metric about where we could and should be.

Principles and Approaches for L&DIn fact, in the Revolution book, I created such a benchmark.  Using my performance ecosystem model, I took the six fundamental elements and elaborated them. The first core element I documented is a learning  culture. That’s accompanied by the approach to formal learning, looking at your instructional design and delivery. Then you move to performance focus, how you’re supporting performance in the world. We move on to social, how you’re facilitating informal learning and innovation. The next step is how you measure what you’re doing. Finally, there’s your infrastructure, how you’re creating the ecosystem environment. For each here I have a principle and an approach.

What I’ve done in the benchmarking instrument is take each of these and extend them. So, for each element broke it into two components, as there are nuances. And, for each, I proposed four levels of maturity:

  • Unaware: here you’re not thinking ecosystem
  • Initiating: now you’re beginning to establish an ecosystem approach
  • Mature: you’ve reached a working approach
  • Leading: at this level you’re setting the pace, thinking ahead

Thus, rather than benchmarking yourself against others, you have a principled approach with which to measure yourself. This instrument is fully elaborated in the Revolutionize L&D book, and goes into detail on each of the twelve rows.

And that was my response to the query. As a person, on principle you’re not supposed to compare yourself to others, but to your own progress. How to set your benchmarks? Against formal criteria. The same is true for organizations. I’ve tried to make a scrutable framework, the Revolution Field Guide, so to speak. So, please, look to best principles, not practices, and evaluate yourself similarly.

 

Chasing Technology Good and Bad

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I’ve been complaining, as part of the myths tour, that everyone wants the magic bullet. But, as I was commenting to someone, there are huge tech opportunities we’re missing. How can I have it both ways?  Well, I’m talking about two different techs (or, rather, many).  The fact is, we’re chasing the wrong technologies.

The problem with the technologies we’re chasing is that we’re chasing them from the wrong beginning. I see people chasing microlearning, adaptive learning, video, sims, and more as  the answer. And of course that’s wrong. There  can’t be one all-singing all-dancing solution, because the nature of learning is remarkably diverse. Sometimes we need reminders, sometimes deep practice, some times individualization makes sense, and other times it’s not ideal.

The part that’s really wrong here is that they’re doing this  on top of bad design!  And, as I believe I’ve mentioned, gilded bad design is still bad design.  Moreover,  if people actually spent the time and money first on investing just in improving their learning design, they’d get a far better return on investment than chasing the latest shiny object.  AND, later investments in most anything would be better poised to actually be worthwhile.

That would seem to suggest that there’s not a sensible tech to chase. After, of course, authoring tools and creating elearning. And that’s not true. Investment in, say, sims makes sense if you’re using it to implement good design (e.g. deep practice).  As part of a good learning design  strategy.  But there’s something deeper I’m talking about. And I’ve talked about it before.

What I’m talking about are content systems. They may seem far down the pike, but let me (again) make the case about why they make sense now, and for the future. The thing is, being systematic about content has both short-term  and  long-term benefits. And you can use the short-term ones to justify the long-term ones (or vice-versa).

In the short term, thinking about content from a systems perspective offers you rigor. While that may seem off-putting, it’s actually a benefit.  If you design your content model around good learning design, you are moving towards the first step, above, about good design. And, if you write good descriptions within those elements, you  really provide a foundation that makes it difficult to do bad design.

My point is that we’re ignoring meaningful moves to chase chimera. There are real value steps to make, including formalizing design processes  and  tools about good design. And there are ways to throw your money away on the latest fad.  It’s your choice, but I hope I’ve made a case for one interpretation. So, what’s yours?

Curriculum or pedagogy?

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In a conversation today, I mentioned that previously I’ve thought that perhaps the best next ‘man in the moon’ project would be to put an entire K12 curriculum up online. And, I’ve also thought that the only way to really fix things is to train trainers of teachers to learn to facilitate learning  around meaningful activity. And, of course, both are needed. What am I thinking?

So, there are huge gaps in the ways in which folks have access to learning. For example, I worked on a project that was trying to develop some K12 curricula online, to provide support for learners in HS that might not have sufficiently capable learners. The project had started with advanced learners, but recognized that wasn’t the only gap. And this is in California!  So I have argued for a massive project, but using advanced curricula and pedagogy.

And, at the other end, as I spoke at a conference looking to talk about improving education in India. There, they have a much bigger need for good teachers than they can reach with their education schools. I was arguing for a viral teacher prep. The idea being not just to train teachers, but train the trainers of those teachers. Then the training could go viral, as just teaching teachers wouldn’t go fast enough.

And both are right, and not enough. In the conversation, I resurrected both points and am now reflecting how they interact. The simple fact is that we need a better curriculum and a better pedagogy. As Roger Schank rightly points out, things like the quadratic equation are nuts to keep in a K12 curricula. The fact is that our curricula came from before the  Industrial Age and is barely adequate there. Yet we’re in an Information Age. And our pedagogy is aligned to tests, not to learning nor doing. We should be equipping kids with actionable knowledge to make meaningful decisions in their lives, not with arbitrary and abstract knowledge that isn’t likely to transfer.

And, of course, even if we did have such a curriculum online, we’d need teachers who could facilitate learning in this way. And that’s a barrier not just in India. The point being that most of the world is suffering with bad curricula and pedagogy. How do we make this change.

And I don’t have an answer. I think we should put both online, and support on the ground. We need that content, available through mobile to reach beyond the developed world, and we need the facilitators. They can be online, as I think about it, but they need to understand the context on the ground if they’re not there. They are context-specific necessities. And this is a massive problem.

Principle says: start small and scale. There are institutions doing at least parts of this, but scaling is a barrier. And again, I have no immediate solution other than a national (or international) initiative. We don’t want just one without the other. I don’t want teachers facilitating the old failed curricula, and I don’t want current pedagogies working on the new curricula. (And I shudder at the thought of a pre-college test in the old style trying to assess this new model!) I welcome your thoughts!

Thoughts on strategy from Training 19

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So last week I was the strategy track coach for the Training 19 conference. An experiment! That meant that I picked the sessions from a list of those who put their session proposals up for ‘strategy’, and could choose to open and/or close the track. I chose both. And there were thoughts on strategy from the sessions and the attendees that are worth sharing.

I chose the sessions mainly on two criteria: coverage of the topics, and sessions that sounded like they’d give real value.  I was lucky, the latter happened! While I didn’t get the complete coverage I wanted, I  did get a good spread of topics. So I think the track worked. As to the coaching, there wasn’t much of that, but I’ve sent in suggestions for whoever does it next year.

I knew two of the presenters, and some were new. My goal, again, was real coverage. And they lived up to it. Friend and colleague Michael Allen practiced what he preached while talking about good learning design, as he does. He was followed by Karen Polhemus &amp Stephanie Gosteli who told a compelling tale of how they were managing a  huge initiative by combining training with change management. Next was JD Dillon, another friend, talked about his experiences building learning ecosystems that deemphasized courses based upon data and his inferences. Alwyn Klein made an enthusiastic and compelling case for doing performance consulting  before you start.  Haley Harris & Beth Wisch went deep about data in talking about how they met the needs for content by curating.  Joe Totherow talked games as a powerful learning tool. Finally, Alex Kinnebrew pushed for finding stakeholder voices as a complement to data in making strategy.

Performance EcosystemI bookended these talks. I opened by making the case for doing optimal execution right, meaning doing proper learning design and performance support. Then I talked about driving for continual innovation with social and informal.  I closed by laying out the performance ecosystem diagram (ok, so I replaced ‘elearning’ in the diagram with ‘training’, and that’s probably something I keep), and placed the coming talks on it, so that attendees would know where the talks fit. I mostly got it right ;).  However, the feedback suggested that for those who complained, it’s because  I took too long to get to the overview. Useful feedback.  

I finished with a 3 hour strategy session where I walked people through each element of the ecosystem (as I cut it), giving them examples, providing self-assessment, and items to add to their strategy for that element. I closed by suggesting that it was up to them to sequence, based upon their particular context. Apparently, people  really liked this opportunity. One challenge was the short amount of time; this is usually run as a full day workshop.

It’s clear that folks are moving to thinking ‘outside of the box’, and I’m thrilled. There were good audiences for the talks in a conference focused on doing training! It’s definitely time for thoughts on strategy. Perhaps, as has happened before, I was ahead of the time for the revolution. Here’s to a growing trend!

Danielle Feinberg #Trgconf Keynote Mindmap

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Danielle Feinberg of Pixar shared her story of using computer science to create the visual art and storytelling for Pixar movies. She illustrated the process of being creative under constraints by being ‘scrappy and clever’. She also illustrated the process with representations of intermediate stages and the stunning results from the movies. Inspiring, as hard to capture in a mindmap.

Surprise, Transformation, & Learning

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wrapped presentRecently, I came across an article about a new explanation for behavior, including intelligence. This ‘free energy principle’ claims that entities (including us) “try to minimize the difference between their model of the world and their sense and associated perception”. To put it in other words, we try to avoid surprise.  And we can either act to put the world back in alignment with our perceptions, or we have to learn, to create better predictions.

Now, this fits in  very nicely with the goal I’d been trying to talk about yesterday, generating surprise. Surprise  does seem to be a key to learning! It sounds worth exploring.

The theory is quite deep. So deep, people line up to ask questions of the guy, Karl Friston, behind it!  Not just average people, but top scientists need his help. Because this theory promises to yield answers to AI, mental illness, and more!  Yet, at core, the idea is simply that entities (all the way down, wrapped in Markov blankets, at organ and cell level as well) look to minimize the differences between the world and their understanding. The difference that drives the choice of response (learning or acting) is ‘surprise’.

This correlates nicely with the point I was making about trying to trigger transformative perceptions to drive learning. This suggests that we  should  be looking to create these disturbances in complacency. The valence of these surprises may need to be balanced to the learning goal (transformative experience or transformative learning), but if we can generate an appropriate lack of expectation and outcome, we open the door to learning. People will want to refine their models, to adapt.

Going further, to also make it desirable to learn, the learner action that triggers the mismatch likely should be set in a task that learners viscerally get is important to them.  The suggestion, then, is create a situation where learners want to succeed, but their initial knowledge shows that they can’t. Then they’re ready to learn. And we (generally) know the rest.

It’s nice when an interest in AI coincides with an interest in learning. I’m excited about the potential of trying to build this systematically into design processes. I welcome your thoughts!

Transformative Learning & Transformative Experiences

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In my quest to not just talk about transformation but find a way to go beyond just experience, I did some research. I came across a mention of transformative experiences. And that, in turn, led me to transformation learning. And the distinction between them started me down a path that’s still evolving. Practicing what I preach, here’s how my thinking’s developing.

I’ll start with the reverse, transformative learning, because it came first  and it’s at the large end.  Mezirow was the originator of  Transformative Learning  Theory. It’s addressing  big learnings, those that come about from a “disorienting dilemma”. These are life-changing events. And we do want to be able to accommodate this as well, but we might also need something more, er scalable.  (Do we really want to ruin someone’s life for the purpose of our learning goals?:) So, what’s at core? It’s about a radical reorientation. It’s about being triggered to change your worldview. Is there something that we can adapt?

The author of the paper pointed me to her co-author, who unveiled a suite of work around Transformative Experience Theory. These are smaller experiences.  In one article, they cite the difference between transformative learning and transformative experiences, characterizing the latter as “smaller shifts in perspective tied to the learning of particular content ideas”.  That is, scaling transformative learning down to practical use, in their case for schools. This sounds like it’s more likely to have traction for day to day work.

The core of transformative experience, however, is more oriented towards the classroom and not the workplace. To quote: “Transformative experiences occur when students take ideas outside the classroom and use them to see and experience the world in exciting new ways.”  All well and good, and we  do want our learners to perceive the workplace in new ways, but it’s not just presenting ideas and facilitating the slow acquisition. We need to find a handle to do this reliably and quickly.

My initial thought is about ‘surprise’. Can we do less than trigger a life-changing event, but provide some mismatch between what learners expect and what occurs to open their eyes?  Can we do that systematically; reliably, and repeatedly?  That’s where my thinking’s going: about ensuring there’s a mismatch because that’s the teachable moment.

Can we do small scale violations of expectations that will trigger a recognition of the need for (and willingness to accomplish) learning?  My intuition says we can. What say you?  Stay tuned!

Fish & Chips Economics

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A colleague, after hearing my take on economics, suggested I should tell this story. It’s a bit light-hearted, but it does make a point. And I’ve expanded it here for the purposes of reading versus listening. You can use other services or products, but I’ve used fish and chips because it’s quite viscerally obvious.

Good fish and chips are a delight.  When done well, they’re crispy, light, and not soggy. Texturally, the crunch of the batter complements the flakiness of the fish as the crunchier exterior of the chips (fries, for us Yanks) complements the softness of the potato inside. Flavorwise it’s similarly a win, the battered fish a culinary combination of a lightly savory batter against the simple perfection of the fish, and the chips provide a smooth complement. Even colorwise, the light gold of the chips set against the richer gold of the fish makes an appealing platter.  It’s a favorite from England to the Antipodes.

And we know how to do it.  We know that having the proper temperature, and a balanced batter, and the right sized fries, are key to the perfection. There is variation, the thickness of the fries or the components of the batter, but we know the  parameters.  We can do this reliably and repeatably.

So why, of all things, do we still have shops that sell greasy, sodden fish and chips? You know they’re out there. Certainly consumers should avoid such places and only patronize purveyors who are able to replicate a recipe that’s widely known.  Yet, it is unfortunately all too easy to wander from town to town, from suburb to suburb, and find a surprising variation.  This just doesn’t make sense!

And that’s an important “doesn’t make sense”.  Because, economics tells us that competition will drive a continuing increase in the quality of products and services. Consumers will seek out the optimal product, and those who can’t compete will fall away. Yet these variations have existed for decades!  “Ladies & gentlemen, we have a conundrum!”

The result? The fundamental foundation of our economy is broken.  (And, of course, I’m using a wee bit of exaggeration  for humor.) However, I’m also making a point: we need to be careful about the base statements we hear.

The fact of the matter is that consumers  aren’t optimizing, they’re ‘satisficing’. That is, consumers will choose ‘satisfactory’ solutions rather than optimal. It’s a tradeoff: go a mile or two further for good fish and chips, or just go around the corner for the less desirable version. Hey, we’re tired at the end of a long day, or the kids are on a rampage, or…  This, in the organizational sense, was the basis of Herb Simon’s Nobel Prize in Economics, before he went on to be a leader of the cognitive science revolution.

The underlying point, besides making an affectionate dig at our economic model, is that the details matter. A joke is that economics predictions have no real basis in science, but then important assumptions are made regardless. This isn’t a political rant, in any case, it’s more a point about the fundamentals of society, and how we evaluate them.  As requested.

Getting brainstorming wrong

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There’s a time when someone takes a result, doesn’t put it into context, and leads you to bad information. And we have to call it out. In this case, someone opined about a common misconception in regards to brainstorming. This person cited a scientific study to buttress an argument about how such a process should go. However, the approach cited in the study was narrower than what brainstorming could and should be. As a consequence, the article gave what I consider to be bad information. And that’s a problem.

Brainstorming

Brainstorming, to be fair, has many interpretations.  The original brought people into a room, had them generate ideas, and evaluate them.  However, as I wrote elsewhere, we now have better models of brainstorming. The most important thing is to get everyone to consider the issue  independently, before sharing. This taps into the benefits of diversity. You should have identified the criteria of the problem to be addressed or outcome you’re looking for.

Then, you share, and still refrain from evaluation, looking for ideas sparked from the combinations of two individual ideas, extending them (even illogically). the goal here is to ensure you explore the full space of possibilities. The point here is to  diverge.

Finally, you get critical and evaluate the ideas. Your goal is to  converge on one or several that you’re going to test. Here, you’re looking to surface the best option under the relevant criteria. You should be testing against the initial criteria.

Bad Advice

So, where did this other article go wrong? The premise what that the idea of ‘no bad ideas’ wasn’t valid. They cited a study where groups were given one of three instructions before addressing a problem: not to criticize, free to debate and criticize, or no instructions.  The groups with instructions did better, but the criticize group were. best.  And that’s ok,  because this wasn’t an  optimal brainstorming design.

What the group with debate and criticizing were actually tasked with doing most of the whole process: freewheeling debate  and evaluation, diverging and converging. The second instruction group was just diverging.  But, if you’re doing it all at once, you’re not getting the benefit of each stage! They were all missing the independent step, the freewheeling didn’t have evaluation, and the combined freewheeling and criticizing group wouldn’t get the best of either.

This simplistic interpretation of the research misses the nuances of brainstorming, and ends up giving bad advice. Ok, if the folks doing the brainstorming in orgs are violating the premise of the stages, it is good advice, but why would you do suboptimal brainstorming?  It might take a tiny bit longer, but it’s not a big issue, and the outputs are likely to be better.

Doing better

We can, and should, recognize the right context to begin with, and interpret research in that context. Taking an under-informed view can lead you to misinterpret research, and consequently lead you to bad prescriptions.  I’m sure this article gave this person and, by association, the patina of knowing what they’re talking about. They’re citing research, after all!  But if you unpack it, the veneer falls off and it’s unhelpful at the core. And it’s important to be able to dig deep enough to really know what’s going on.

I implore you to turn a jaundiced eye to information that doesn’t come from someone with some real time in the trenches. We need good research translators.  I’ve a list of trustworthy sources on the resources page of my book on myths. Tread carefully in the world of self-promoting media, and you’ll be less hampered by the mud ;).