This past week, I spent two days at ATD’s Techknowledge conference. I gave a talk on ‘transforming learning’, and another (largely) on myths. And I participated in a couple other things, including helping out a colleague for  her session. But I want to reflect on the rest of the event. So here’s an ATD TK2020 retrospective.

First, I should note, I did  not mindmap the keynotes (in case you missed them). I used to do it all the time. However, the app that I used to do it has a new edition out, and it’s pricey.  And, I don’t have enough other use for it. I can sketch out ideas in my note-taking app. So…guess that’s gone by the wayside. We’ll see if I find out an alternative.

I  did try to take notes. And, because I’d read recently that drawing was a better note-taking technique (don’t recall the exact link, but this suggests the benefit), I  tried to draw. Old habits…I mostly wrote. And they weren’t worth publishing.

The conference itself was interesting because they were experimenting. For instance, there was no expo. Vendors had suites, and several tried to get me to meet with them. But didn’t have a viable business case for me to care (I’m not a candidate for your LMS, for instance ;). And they were set up to have several simultaneous speakers at the same time. Even on the same stage!

What I’m talking about here is that there was this little audio device you hung around your neck. It had 6 channels, and a plug for earphones (also provided). So, right after the opening keynote, there was the first of what they called ‘supersessions’. Here, three people were up on different parts of the same stage, and gave three different talks. You set the channel to the one you wanted to hear (or the two you wanted to switch between ;). And, it worked. Largely. One of the presenters for one of the sessions kept running around and interacting (interrupting) the others.

And there were six stages in one room, and you could jump between them, or sit and listen to one. Without, note, being distracted by the others. On the other hand, it was hard to have audience interaction. They couldn’t hear one another, and for instance the one I did I really could’ve benefited from a flip chart (which I asked for but didn’t get).  Still, it largely worked.

There were some more traditional talks in another room (I did one of those, too). And they were, well, familiar. Not that that’s a bad thing.

One other thing that was interesting was a ‘hackathon’. Here, a worthwhile not-for-profit posed a challenge and volunteers were divided up into teams to address it. Unfortunately, it seemed to be more focused on visual design. I tend to think that infusing learning science is more likely to be a problem in their elearning.  (So, of course, I made that my own challenge.) Still, it helped the org, and provided an opportunity to interact.

I ran into my friends and colleagues more, and the discussions were perhaps a little easier to engage in. I liked the more intimate feel. Though I confess to having missed the expo (perhaps because I couldn’t find as much to criticize!). And the food was quite good (the Wed lunch in particular).

I did note that there were still some zombies running around. There was a dialog between two folks who were supposedly talking about the future of work, but played a lot of the ‘millennial’ card. Bad speaker, no Twinkie!

Overall, I laud their willingness to experiment. I know the Guild does a fair bit of it as well, but this was more unusual from a large (and often inflexible) organization. As a fan of ‘learning out loud’, I hope it’s useful to provide an ATD TK2020 retrospective, and if you were there, I welcome your thoughts!

Last week, I ranted about a myth that seems inextinguishable. And I ran across another one in a place I shouldn’t have. And I keep seeing others, spotting them roaming around loose. Like zombies, they seem to rise from the dead. We need death to zombies. Particularly learning myth zombies!

There are several that seem overly prolific. I’ve already ranted about learning styles, but it’s pernicious. And others keep cropping up. In addition to the ‘images 60K faster than text’, I saw the Millennials and Generations twice this week!  And…the list goes on.

And this is despite a continued effort to debunk these deathwalkers!  There’re mythbusters who continually call out the false claims. There’s the Debunker  Club. Amongst the publications by Jane Bozarth for the research library of the eLearning Guild, there are several myths-related compendiums.

And, immodestly, I wrote a whole book about myths!  Trying to point out why it’s appealing, showing why they’re wrong, and providing alternative approaches that are sounder. And I was asked to do it, so there’s a clear need. I’m not asking you to buy it, unless it helps, but you need to be aware of the myths.

What to do? Well, first, please help. If you see a myth, call it out. You don’t  have to do it publicly, you can always talk to the person quietly afterward. But don’t let it slide. (Some of those at the event will read this blog; long story but thanks, Paul. ;)

So, I’m calling you all to be zombie hunters. Please!  Death to zombies, for the sake of our industry, our professionalism, and our learners.

Update:  In fact, after I’d queued up this post for publication, I went to an event where people were sharing. While most were very useful and thoughtful, three of the shares violated what’s known!  One was so-called ‘brain training’, in this case activating right-left brain simultaneously. That also violates the right/left brain myth! Another was on Strengths, which I haven’t addressed, but the one cited was the one that doesn’t have peer reviewed research (ie  not the VIA strengths). Finally, one was on ‘color’ personality, which is based upon Meyers-Briggs, which is flawed both theoretically and psychometrically. Yikes, they’re everywhere!

Update 2: I was pointed to a post on LinkedIn about building a VR demo…on the MBTI!  Ouch. The MBTI is flawed theoretically (it’s based on Jungian archetypes, which he just made up) and psychometrically. It’s pretty horrific to think of VR being used to present information (like attending a PowerPoint presentation in 2nd Life, which happened); to do it on such a flawed concept is doubly scary.

My post earlier this week on the images processed 60K faster prompted some discussion (over on LinkedIn ;). And there appears to be some debate about the topic. I think it revolves around the issue of just  what’s  in an image. So let’s unpack that.

So, the claim is that ‘images’ are processed 60K faster than text. And, of course, trying to find the actual citation has been an exercise in futility. But can we address it on principle? I’ll suggest we can.

Let’s take it apart. What’s in an image?  Is it a photo? A diagram? An infographic? Even a video?  I think we need to nail it down. So let’s talk about the presumed cognitive processing that goes on.

Let’s start with photos. They capture context. If it’s a familiar context, processing likely happens almost immediately. But others? Not so fast. Unless a context has already been established, a picture isn’t going to make much sense. That is, we probably should account for the context processing as part of the story.

As soon as we get to diagrams, the story gets more complex. Ok, Jill Larkin and Herb Simon once opined on  Why a Diagram is worth 10000 words, but it’s about mapping conceptual relationships to spatial relationships. And I’ll still argue you need to process the elements, and the relationships, before you understand it. So it’s not instantaneous.

And, yes, there’s the lovely example in Don Norman’s  Things That Make Us Smart, where he showed how a relationship was more quickly processed than the equivalent text description (he kindly didn’t mention it was from my Ph.D. thesis ;). Yet not all text can be replaced by images.  What would convey Nike’s  Just Do It  slogan more concisely than that text? You’d have to establish the relationship  first. E.g. their ‘swoop’.  As I mentioned, familiar words are processed essentially as images, as whole words, not being processed by individual characters.

The same holds true for infographics, by the way. They’re not ‘grokked’ immediately. They need to be parsed in terms of message, and flow, and information. They’re a mashup of text and info, but that doesn’t make it any faster. Though they  may support retention, but we should use diagrams and images appropriately  with text.

Video’s even more complex. It’s a linear medium, as is text. And it’s powerful, but is it processed more efficiently? Again, I think it depends on what you’re saying. A video can be a narrated slide show. Is that faster than reading the text? I read faster than folks speak.

Which brings me to my take-home conclusion. A simple statement like “images processed 60K faster than text) is misleading.  What image? It all hinges on  what’s  in an image. Be vary wary of such claims. In the previous article, I provided some questions to ask yourself. And I may have to rant again about myths in general!

Thinking more about Friston’s Free Energy Principle and the implications for learning design prompted me to think about play. What drives us to learn, and then how  do we learn?  And play is the first answer, but does it extend? Can we play to learn beyond the natural?

The premise behind the Free Energy principle is that organisms (at every level) learn to minimize the distance between our predictions and what actually occurs. And that’s useful, because we use our predictions to make decisions. And it’s useful if our decisions get better and better over time. To do that, we build models of the world.

Now, it’d be possible for us to just sit in a warm dark room, so our predictions are right, but we have drives and needs. Food, shelter, sex, are drives that can at least occasionally require effort. The postulate is that we’ll be driven to learn when the consequences of not learning are higher than the effort of learning.

At this level, animals play to learn things like how to hunt and interact. Parents can help as well.  At a higher level than survival, however, can play still work? Can we learn things like finance, mathematics, and other human-made conceptions this way? It’d be nice to make a safe place to ‘play’, to experiment.

Raph Koster, in his  A Theory Of Fun,  tells us that computer games are fun just because they require learning. You need to explore, and learn new tricks to beat the next level.  And computer games can be about surviving in made-up worlds.

The point I’m getting to is that the best learning should be play; low stakes exploration, tapping into the elements of engagement to make the experience compelling. You want a story about what your goal is, and a setting that makes that goal reasonable, and more.

To put it another way, learning  should be play. Not trivial, but ‘hard fun’.  If we’re not making it safe, and providing guided discovery to internalize the relationships they need, to build the models that will make better decisions, we’re not making learning as naturally aligned as it can be. So please, let your people play to learn. Design learning experiences, not just ‘instruction’.