Of late, there’ve been a few dialogs on Twitter. As I opined in the recent podcast I was interviewed in, using Twitter  for a dialog is kind of new. I’m not talking about a tweet chat like #lrnchat  (which I think is a great thing), but a out-loud dialog with others weighing in. And it’s fun, and informative, but occasionally I need to go deeper. So here’s a reflection on reflection.

In that podcast interview, I opined, as I often do, about action and reflection. The starting point is a claim is that our own learning action and then reflection. What I mean is that we act in the world, and if we reflect on it we can learn.

One of the pushbacks was that we can learn without reflection. And, yes, I agree. We can learn without conscious feedback. In fact, in Kathy Sierra’s insightful  Badass, she talks about chicken sexing,  a task which no one’s been able to make consciously accessible. Things can go below consciousness.

This was related to another pushback: do we really learn differently from chickens and rats? And the answer is no, but  what  we learn is different. And, further, what we  can learn is different. I’ve yet to see rats sending rockets up to the moon to see if it’s made of cheese.

Conscious representations facilitate learning, particularly for things we learn that aren’t strongly tied to our evolved survival. Learning about cognition itself, for instance, the ability to think about our own thinking, is just something that separates us fundamentally. And, to do that well, conscious artifacts facilitate it.

We’ve found that creating conscious frameworks to facilitate our understanding and acquisition are helpful. So, specifically, models and examples are two things that help us develop skills. We use models to guide and review our performance, to guide us. M0dels are conceptual relationships that we can compare to our performance. Examples show how those models play out in particular contexts.

There’s a followup: if learning is action and reflection, then instruction  should be  designed action and  guided reflection. That is: do, get feedback, but also  more. To me, models and examples  are that additional reflection. We can present them ahead of time (but see Problem-Based Learning), but we should use them as part of the feedback, pointing out how flaws in performance didn’t align with the models, and further examples that illustrate those nuances.

Ok, so I may be playing fast and loose with the notion of reflection here, lumping in models and examples and feedback. However, my point is to try to keep learning  not being information dump and knowledge test. We know that won’t lead to meaningful change. If I label it action and reflection, we have a better chance to push for an application-based instruction.

So, I’ll stick to my claim about (designed) action and (guided) reflection, with the caveat that my ‘reflection’ is more than just noodling. And, yes, it’s for learning goals beyond ‘hitting your head on rocks hurts’. But the goals I’m focusing on are the types of goals that will make a difference in individual and organizational success in our society.  If I’m pushing too far and too hard, let me know.

Some weeks back, I posted about surprise. That is, a new model that says that that our brains work to minimize surprise. We learn so as not to be wrong. And that made sense in one way, but left another gap. Another article explains (well, partly; the mathematics are more than I want to wade into) further, and that gives me a new handle on thinking about designing transformative experiences. It’s about the value of exploration to accompany surprise.

The problem with the original story of us just minimizing surprise is that this leads to another inference. Why wouldn’t we want to just hang in a dark warm room?  The notion of minimizing surprise did explain people who don’t seem keen to learn, but many of us are.  And, as Raph Koster told us in  A Theory of Fun, the drive to play games seems to be learning! We want exploration, and the outcomes aren’t certain. This is in conflict.

The new article posits that there’s another factor, the expectation of value. We also want the optimal outcome. The theory says that we’ll be willing to try several relatively equal predicted value outcomes to learn which to choose in the future (if I’ve understood the article correctly). So we  will  explore even under uncertainty if there’s a benefit to learning.

This doesn’t quite explain things to me. I think it’s missing some emotional aspect.  Why would we do things like try out Escape Rooms or The Void (as I’ve done with colleagues)?  There’s no real outcome, except perhaps to know about such experiences. But horror movies or thrillers? All we know is that we’ll have our emotions raised and then settled. But maybe that fits into a good outcome.

Still, this gives me a new handle. When I was preparing the Learning Experience Design workshop I gave at Learning Solutions last month, I was talking about ensuring surprise. That is, the learning experience should make learners aware that they didn’t know what the outcome would be. But I knew, and suggested, that there had to be more. They had to  care about the outcome. And now we have the hook.

They care about the outcome, because it’ll be a higher value situation once they do!  If we do this right, we let them know that they care about the outcome, and they can’t do it now (either they know already, or we have them fail). Then, we can offer them the path to achieve this outcome. If they explore, they’ll learn? If we’ve got a truly meaningful outcome (you’ll now be able to do X) that they truly care about (you  do want to be able to do X), you’re now set with emotionally ready learners. Cognitive science models suggest that this should work!  :)

To turn it around. the point is that you should create a goal that they  should desire, and then demonstrate that they don’t already know it. It’s simplistic, but I think it’s part of creating a transformative experience, one where they are not just ready for the outcome, but eager. And I think that’s desirable.  What do you think?

 

 

 

It’s hard to think of now, but last week I was at the Learning Solutions conference. And I had a really great time. I didn’t see as much as I’d like (as you ‘ll see, I was busy), but there were some really worthwhile learnings, and some fun as well. Here are my conference reflections.

For the first time, I rented a scooter. That was a learning all in itself. I’d been having pain, and walking was the  worst. The scooter was a way to address that, and it did. I scooted around and avoided much walking. Not all, but a lot. And it was fun to zoop around, but…it was hard to maneuver in small spaces. Like the necessary elevators. And my room. I tried to slow down and do it carefully, and that worked to an extent, but it wasn’t pretty.

The great part was that, having heard of my plight, some friends descended upon my ride and tarted it up with glitter and dangly things. And, best of all, caution tape. Very appropriate. Very much appreciated!  And it wasn’t even too hard to take off at the end.

Thus, I was happy to zoom to my room to run my pre-conference workshop on learning experience design. It was designed as an integration of Engaging Learning and the Serious eLearning Manifesto.    I snuck a bit of ‘transformation‘ in there as well.  The evaluations aren’t back yet, but I think overall it achieved the purpose. One attendee later suggested an improvement that I’d agree on (allowing learners to choose from the topics to workshop on). Always learning!

That evening, we did something I’d never done, Presentation Roulette. The speakers (I agreed to be one, without having seen it before; I do like experimenting [read: living dangerously]) choose a random title out of a sock (well, it was clean) and are then given a deck that Bianca Woods of the Guild had developed for that title, including the silliest pictures she could find on the web. As she describes it, a mashup of presentations and improv comedy.  It was very fun, and in particular extremely funny; the other presenters did great jobs. I’ll attend again even if I don’t present!

Tuesday was a normal day (e.g. I didn’t present). As usual, I mindmapped the keynotes (several posts back), cruised the floor, and attended some sessions. The panels were good. I attended the one on the Future of ID, and the comments were insightful about how the tools and goals were changing. Similarly the one on the Future of Work had a convergent message I resonated with, that we need to focus on using tech to augment us on the stuff we’re good at, not try to fight off automation of rote tasks. I also took some time off for calls and work.

That evening, after dinner, some friends and colleagues (they’re the same folks) came over to my suite. (I have gotten lots of accommodations for my situation; and I’m  very grateful.)  Fueled by libations, we proceeded to gin up an evil plan to control the world (or at least the market).  Politically correct it wasn’t, fun it was.  Too late to bed.

The next day I was part of the Guild Master panel with about 14 participants. Too many!  Great thoughts, and I tried to stifle myself and only make the most cogent points. Apparently I still spoke a little too much. I blame it on this blogging, it gives me lots of thoughts. :) The points I wanted to make were, not surprisingly, about the need for getting back to basics in learning design, and to look beyond optimal execution to continual innovation.

I also sat in an ARK Kit presentation. It made AR seem almost within reach. At this time you still do need some coding, but if it progresses like many tools, much will soon become at a higher level of ability to describe what you want and make it so.

I still wasn’t done, as later that day I also gave my ‘professionalism and myths’ talk. The audience was small but enthusiastic. I do believe we made some converts. I added in not just debunking myths, but how to talk to folks who buy into it. There’s a little learning science in it as well. We really do need to be on a sound basis before we can have credibility.

I have to say, delightedly, that I continue to have folks say that my books have helped them. Different books for different folks, but something I love to hear. As an author, you get some idea of the sales, but none of the impact. Some of these were small effects, and some were “I’ve used this to change my/our practice.”  That’s what it’s about, after all, you write a book to effect change. I’m grateful for those who share this insight!  In particular, I hear lots of folks using the Myths book in their orgs to counter employees/customers’ misguided intentions. The Revolution book still (or, perhaps,  now) has influence. And I still hear about the Games book!

I also slipped away with some more conspirators and experienced  The Void. It  was  hard on my legs (I went with cane, not scooter), mostly because they didn’t have anywhere to sit while you waited!?!?!  (I gave them a serve in the too-long post-experience survey.) However, it’s very cool: a compelling experience and great implications for learning. Embedded performance? That would be ‘yes’.

The keynotes, by the way, were excellent  AND…  I’ve heard over the years that conference organizers say it’s hard to have diversity in speakers. All white males (e.g. me ;), or at least white.  This time, there were two women, and two blacks, out of three people. With good messages.  It was inspiring to hear and to see!  Kudos to David Kelly and the Guild for managing to debunk the barrier.

There was some discussion of whether there was a place for those who proselytize learning science or it was all going commercial and cheap. I feel like there’s a growing interest in the science, but I’m frequently a year or several ahead of the market. In this case, I want to yell “make me right!”  This is a field I care about, and we can be doing so much good. I want us to capitalize on that potential. There were new folks looking for solutions and the opportunity to grow. I hope we can make that happen in a positive direction.

Overall, it was a success. I had time with smart colleagues, saw interesting sessions, and met new folks. I presented and got feedback, which is a great cycle. And it was another chance to immerse myself in the state of the industry. Here’s to continual improvement.

 

 

As some of you may know, last week I had a surgical procedure. I don’t want to share details, but while it was non-trivial, it went fine. (I’ve talked earlier about the situation beforehand.) What did  not go fine was the recovery. I’m good now, but there were a harrowing few days. And I think the reason is of interest, and there’s a lesson. So I thought I’d share.

Now, my only previous experience with surgery was outpatient knee surgery. And it was amazing; I went off pain killers the 2nd day, and recovery was rapid. This, too, was outpatient, and while not as ‘micro’ as the knee surgery, I had no other frame of reference. And that caused a problem.

So, the day of the surgery went about as you might expect. I went in, lay down, woke up somewhere else, and was told things went well. With the benefit of meds, I let folks know I’d lived :), and proceeded to sleep away the afternoon. Come the evening, I was more clear-headed. With good meds, I looked forward to a night’s sleep, and better in the morn.

That night’s sleep was  not good. I couldn’t get comfortable, and so couldn’t sleep. Specifically, my left (not bad) side was uncomfortable and so was my right side  that was supposedly fixed. I was awake all but maybe 2 hours. Yet, I’d gotten used to sleep deprivation.

I was bothered that the side that had had the surgery, that was now supposed to be free of the cause, still hurt. Differently, perhaps, but still hurt. This was dismaying (to put it mildly). I called Saturday night, and was told that the right side could still hurt for some days. Er, okay…

Saturday night wasn’t really better. I slept maybe 3-4 hours, but lack of comfort meant I was still worried and in addition now sleep-deprived. This wasn’t all, but worth recounting is by Sunday, my whole right leg wasn’t working. Any sort of moving but standing hurt.  Not good.

This continued into Monday. Little and bad sleep meant I was going into a mentally challenging state of sleep-deprivation. The lack of right leg action began to make me feel like the whole experiment had failed, and I was going to have to face this again. I put in a call, but my doctor was in surgery. You can imagine I was discouraged and distressed. I was headed to bed when my doctor finally called. They’d scheduled me to see him the next day, and I hung on to that.

When I got to see him on Tuesday morning, I was a wreck. Spaced out from lack of sleep, distressed about my leg, and so on. I first talked to the PA, and then the doc came in. And, I found out a lot more. They’d completely removed the material pressing on the disk, but in so doing they’d likely irritated the nerve. And there could be some bleeding doing that, too. So, my leg hurting was explained. When we talked about meds, they were reminded what I  had  been on, and how the sudden cessation of that could be problematic. With explanations, and revised recommendations for medications going forward, it seemed promising.

Low and behold, after the visit, things began to fall into place. The medication revisions kicked in, and I felt a  lot better. Not good, mind you, but many times better. Finally, I could see how this was all working, and I  was progressing!

I awoke this morning and verified that yesterday wasn’t a fluke; I’m on a path to recovery. I still have a backlog of things to deal with, but I can get on that now.  And I still hurt in various places. But it’s the right hurt, I now know.

The short version of all this is that expectations matter. Stephanie Burns did her Ph.D. research on the people who succeeded with their goals (vs those who don’t), and found it was the ones who managed their expectations appropriately. Set goals, rewarded them, realized it was a long haul, etc. Similarly for learning; you want expectations to match experience. A mismatch can induce barriers to successful learning. If the experience will be typical, it may not matter so much, but you want to be wary of any ways in which people can find their expectations mismatched. Yes, you want some surprise, but you don’t want people to lose their comprehension of who they are and where they’re going.

I don’t actually blame the doctor. I think they could’ve set my expectations better, but I fear I come across as someone who has an idea of what’s going on. And I should’ve asked more questions. Further, I think there weren’t any flags that I needed such support. Still, it perhaps ought to be automatic. So consider setting expectations. Deliberately. Systematically. You can let them know there might be some surprise, without giving it away. Don’t leave people open to making inappropriate expectations, or you might be unpleasantly surprised.

Recently, 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!

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 ;).

I was listening in to a webinar on trends in higher education. The speakers had been looking at different higher ed pedagogy models, within and external to institutions. It became clear that there was a significant gap between a focus on meeting corporate needs and the original goals of education. Naturally, it got me to think, and one link was, not surprisingly, wisdom. So what does that mean?

In the ‘code academy’ models that are currently challenging to higher education, there’s very much a ‘career’ focus. That is, they’re equipping students to be ready to take jobs.  Which is understandable, but there’s a gap. A not-for-profit initiative I was involved with wanted to get folks a meaningful job. My point was that I didn’t want them to get a job, I wanted them to  keep a job!  And that means also learning about learning to learn skills, and more. That more is where we make a substantial shift.

The shift I want to think about is not just what corporations need, but what  society needs. The original role of institutions like Oxford and Harvard was to create the next generation leaders of society. That is, to give the philosophical (in the broad sense) and historical perspective to let them do thinking like what delivered the US Constitution (as an example). And there’s plenty of lip service to this, but little impact. For example, look at the success of teaching ethics separately from other business classes…let’s move on.

It seems like there’s several things we need to integrate. As pointed out, treating them separately doesn’t work. So how do we integrate them and make them relevant.  Let’s take Sternberg’s model of Wisdom, where you think about decisions:

• for the short term  and long term
• for you, yours,  and society as a whole
• and also explicitly discuss the value assumptions underpinning the decision.

This gives us a handle. We need to find ways to naturally embed these elements into our tasks. Our tasks need to require 21C skills and understanding the societal context as well.

In my ‘application-based instruction’ model, I talk about giving learners challenges that do require 21 C skills in natural ways. In this model, tasks mimic world tasks, asking for things like presentations, RFPs, problem recommendations, and more.  Then, how do we also include the societal aspects?  I suppose by putting those decisions in situations where there are implications not just for the business but for society.

Ok, it may be too much to layer this on every assignment (major assignment, not the accompanying knowledge check), but it should be covered in every subject (yes, even introductory) in some way. This thinking has already led me to create a question on evaluating policy tradeoffs for the mobile course I’m developing.

We need to keep the societal implications involved. Ensuring that at least a subset of the assignments do that is one approach. Doing so in a natural way requires some extra thinking, but the consequences are better. Particularly if the instructor actually makes a point of it (making a note to myself…).  A separate course doesn’t do it. So let’s get wise, and develop in deeper ways that will deliver better outcomes  in the domain, and for the greater good. Shall we?