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Clark Quinn’s Learnings about Learning

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The (Post) Cognitive Perspective

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I’m deeply steeped in the cognitive sciences, owing to a Ph.D. in cognitive psych. Fortuitively, this was at the time my advisor was creating the cognitive science program (and more). So I’ve a bias. Yet I also have a fair bit of empirical evidence that taking a cognitive perspective accomplishes things that are hard to do in other ways. So let me make the case that the cognitive perspective is more than just a useful one, but arguably a necessary one.

I‘ll start by reflecting back on something I wrote before, about virtual world affordances. At the time, platforms like Second Life were touting the advantages of an immersive navigable world. Of course, the promises were all-encompassing: everything would move to virtual worlds. In retrospect, it didn‘t eventuate. Why? I argue it’s because the cognitive overhead of virtual worlds means that there has to be a sustained value proposition, and that came from when you truly need 3D immersion and social.  

Similarly, when I wrote my books on games and mobile, I focused on the cognitive impacts. The first reason was because technology was changing so fast that anything hardware-specific would be out of date before the book was published. The second is because our brains don‘t change that fast, so what works will work regardless of the technology .  

Note that our understanding of cognition has changed. We‘re now in a ‘post-cognitive‘ era, where the notion that all our formal, logical thinking is done in our heads is wrong. Research is showing that we‘re far more ‘situated‘ than we think, and distributed as well. That includes distributed across external representations and other people! It’s very contextual, and it’s not all in our heads!

So these days, when I look at things, I try to look with a cognitive (ok, post-cognitive) perspective. I look to see how things align, or not, with how our brains work. When I evaluate learning technologies, for instance, I look to see how well they do things like provide meaningful practice: active and contextualized. You can also see when particular technologies (e.g. VR/AR/AI) will be valuable, and not. Similarly, when I look at workplace change proposals, I look at how well they reflect our mechanisms for adapting to change.  

I‘ll argue that these perspectives are valuable. You can quickly see why most training doesn‘t work, cut through hype from vendors, create explanations about why myths are mythtaken, etc. You can save money, be more effective, etc when you align with how our brains work. I‘ve talked before about how there are gaps. This is the flip side, how to avoid those gaps, and do better.   In short, you‘re better able to assist your organization in being more effective (and efficient).  

That‘s why I‘m pleased that I am able to put these basics into the learning science book, and workshops. It‘s possible to get better at this sort of perspective. It‘s also possible to get it on tap as needed. However, it does take both the cognitive understanding and the experience in applying it. So, how‘s your cognitive perspective?

On a side note, I want to encourage you to consider my workshop at DevLearn on Make It Meaningful, a full day exploring how we make learning experiences deeply engaging (adding to effectiveness). This is also the topic of my online workshop through the Learning Development Accelerator. This is, to me, the most important topic to  complement  learning science. (Available as a book and workshop. ;) In both cases, I’m trying  to help us  stop making boring courses that people want to avoid, and suggest that this  can be done for most any topic. It also leads to more effective learning outcomes! Hope to see you at one! (Of course, if your organization would like your own private version, let me know!)

Complexity in Learning Design

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a fractalI recently mentioned that one of the problems with research is that things are more interconnected than we think. This is particularly true with cognitive research. While we can make distinctions that simplify things in useful ways (e.g. the human information processing system model*), the underlying picture is of a more interactive system.  Which underpins why it makes sense to talk about Learning Experience Design (LXD) and not just instructional design. We need to accommodate complexity in learning design.  (* Which I talk about in Chapter 2 of my learning science book, and in my workshops on the same topic through the Allen Academy.)

We’re recognizing that the our cognition is more than just in our head. Marcia Conner, in her book  Learn More Now  mentioned how neuropeptides passed information around the body. Similarly, Annie Murphy Paul’s  The Extended Mind talks about moving cognition (and learning) into the world. In my Make It Meaningful workshops (online or F2F at DevLearn 19 Oct), I focus on how to address the emotional component of learning. In short, learning is about more than just information dump and knowledge test.

Scientifically, we’re finding there are lots of complex interactions between the current context, our prior experience, and our cognitive architecture. We’re much more ‘situated’ in the moment than the rational beings we want to believe. Behavioral economics and Daniel Kahneman’s research have made this abundantly clear. We try to avoid the hard mental work using shortcuts that work sometimes, but not others. (Understanding when is an important component of this).

We get good traction from learning science and instructional design approaches, for sure. There are good prescriptions (that we often ignore, for reasons above) about what to do and how. So, we should follow them. However, we need more. Which is why I tout LXD  Strategy! We need to account for complexity in learning design approaches.

For one, our design processes need to be iterative. We’ll make our best first guess, but it won’t be right, and we’ll need to tune. The incorporation of agile approaches, whether SAM or LLAMA or even just iterative ADDIE, reflects this. We need to evaluate and refine our designs to match the fact that our audience is more complex than we thought.

Our design also needs to think about the emotional experience as well as the cognitive experience. We want our design processes to systematically incorporate humor, safety, motivation, and more. Have we tuned the challenge enough, and how will we know?  Have we appropriately incorporated story? Are our graphics aligned or adding to cognitive load? There are lots of elements that factor in.

Our design process has to accommodate SMEs who literally can’t access what they do. Also learner interests, not just knowledge. We need to know what interim deliverables, processes for evaluation, times when we shouldn’t be working solo, and tools we need. Most importantly, we have to do this in a practical way, under real-world resource constraints.

Which is why we need to address this strategically. Too many design processes are carry-over from industrial approaches: one person, one tool, and a waterfall process. We need to do better. There’s complexity in learning design, both on the part of our learners, and ourselves as designers. Leveraging what we know about cognitive science can provide us with structures and approaches that accommodate these factors. That’s only true, however, if we are aware and actively address it. I’m happy to help, but can only do so if you reach out. (You know how to find me. ;) Here’s to effective and engaging  learning!

A message to CxOs 2: about org learning myths

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When I wrote my last post on a message to CxOs about L&D myths, I got some pushback. Which, for the record, is a good thing; one of us will learn something. As a counter to my claim that L&D often was it’s own worst enemy, there was a counter. The claim was that there are folks in L&D who get it, but fight upward against wrong beliefs. Which absolutely is true as well. So, let‘s also talk about what CxOs need to know about the org learning myths they may believe.  

First, however, I do want to say that there is evidence that L&D isn‘t doing as well as it could and should. This comes from a variety of sources. However, the question is where does the blame lie. My previous post talked about how L&D deludes itself, but there are reasons to also believe in unfair expectations. So here‘s the other side.  

  1. If it looks like schooling… I used this same one against L&D, but it‘s also the case that CxOs may believe this. Further, they could be happy if that‘s the case. Which would be a shame just as I pointed out in the other case. Lectures, information dump & knowledge test, in general content presentation doesn‘t lead to meaningful change in behavior in the absence of activity. Designed action and guided reflection, which looks a lot more like a lab or studio than a classroom, is what we want.
  2. SMEs know what needs to be learned. Research tells us to the contrary; experts don’t have conscious access to around 70% of what they  do (tho’ they do have access to what they know). Just accepting what a SME says and making content around that is likely to lead to a content dump and lack of behavior change. Instead, trust (and ensure) that your designers know more about learning than the SME, and have practices to help ameliorate the problem.
  3. The only thing that matters is keeping costs low.  This might seem to be the case, but it reflects a view that org learning is a necessary evil, not an investment. If we’re facing increasing change, as the pundits would have it, we need to adapt. That means reskilling. And effective reskilling isn’t about the cheapest approach, but the most effective for the money. Lots of things done in the name of learning (see above) are a waste of time and money. Look for impact first.
  4. Courses are the answer to performance issues.  I was regaled with a tale about how sales folks and execs were  insisting that customers wanted training. Without evaluating that claim. I’ll state a different claim: customers want solutions. If it’s persistent skills, yes, training’s the answer. However, a client found that customers were much happier with how-to videos than training for most of the situations. It’s a much more complex story.
  5. Learning stops at the classroom. As is this story. One of the reasons Charles Jennings was touting 70:20:10 was not because of the numbers, but because it was a way to get execs to realize that only the bare beginning came from courses, if at all. There’s ongoing coaching with stretch assignments and feedback, and interacting with other practitioners…don’t assume a course solves a problem. A colleague mentioned how her org realized that it couldn’t create a course without also creating manager training, otherwise they’d undermine the outcomes instead of reinforcing them.
  6. We‘ve invested in an LMS, that‘s all we need. That’s what the LMS vendors want you to believe ;)!  Seriously, if all you’re doing is courses, this could be true, but I’m hoping the above
  7. Customers want training.  Back to an earlier statement, customers want solutions. It is cool to go away to training and get smothered in good food and perks. However, it’s  also known that sometimes that  goes to the manager, not  the person who’ll actually be doing the work! Also, training can’t solve certain types of problems.  There are many types of problems customers encounter, and they have different types of solutions. Videos may be better for things that occur infrequently, onboard help or job aids may meet other needs to unusual to be able to predict for training, etc. We don’t want to make customers happy, we want  to make them successful!
  8. We need ways to categorize people. It’s a natural human thing to categorize, including people. So if someone creates an appealing categorization that promises utility, hey that sounds like a good investment. Except, there are many problems! People aren’t easy to categorize, instruments struggle to be reliable, and vested interests will prey upon the unwary.  Anyone can create a categorization scheme, but validating it, and having it be useful, are both surprisingly big hurdles. Asking people questions about their behavior tends to be flawed for complex reasons. Using such tools for important decisions like hiring and tracking have proven to be unethical. Caveat emptor.
  9. Bandwagons are made to be jumped on. Face it, we’re always looking for new and better solutions. When someone links some new research to a better outcome, it’s exciting. There’s a problem, however. We often fall prey to arguments that appear to be new, but really aren’t. For instance, all the ‘neuro’ stuff unpacks to some pretty ordinary predictions we’ve had for yonks. Further, there are real benefits to machine learning and even artificial intelligence. Yet there’s also a lot of smoke to complement the sizzle. Don’t get misled. Do a skeptical analysis.  This holds doubly true for technology objects. It’s like a cargo cult, what’s has come down the pike must be a new gift from those magic technologists! Yet, this is really just another bandwagon. Sure, Augmented Reality and Virtual Reality have some real potential. They’re also being way overused. This is predictable, c.f. Powerpoint presentations in Second Life, but ideally is avoided. Instead, find the key affordances – what the technology uniquely provides – and match the capability to the need. Again, be skeptical.

My point here is that there can be misconceptions about learning  within  L&D, but it can also be outside perspectives that are flawed. So hopefully, I’ve now addressed both. I don’t claim that this is a necessary and complete set, just certain things that are worth noting. These are org learning myths that are worth trying to overcome, or so I think. I welcome your thoughts!

Performance Support and Bad Design

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Here’s a story about where performance support would’ve made a task much easier.

And, as always, the text.

The other day, I had a classic need for performance support. Of course, it didn‘t exist. So here‘s a cognitive story about when and where a job aid would help.

Our Bosch dishwasher stopped near the beginning of the cycle, and displayed an icon of a water tap. The goal was to get the dishwasher running again. What with the layer of undrained water, we figured there was some sort of problem with the drain, clogged or the pump broken. M‘lady had cleaned the drain, but the icon persisted. What now? Of course we could call a service person, but trying to be handy and frugal (and safe), we wanted to find out if it was something I could deal with. So, off to the manual.

Well, in this case, since I didn‘t know where the manual was, I went online. I accessed the site and downloaded the manual. Only to find no guide to what the icons mean. What?!? This violates what we know about our brains, in this case that our memory is limited. The support section of the site did list the error codes, but numerically, not by icon.  So, I had an indication I couldn’t map to a problem, let alone a  solution.  

This is a real flaw! If you‘re gonna use icons, provide a guide!  Don’t assume they’re interpretable. (This had happened once before with this same appliance, with an impenetrable icon and no clue.) As a result, I had to call the service line. That wait took awhile (with more people staying home, they‘re using their dishwashers more, and the appliances are therefore breaking down more). Once, the call dropped. The second time I had to stop because I had an upcoming call. The third time, however, I got through.

And a perfectly nice person listened, asked some questions, and then instructed me through a process. After hitting cancel (which automatically tries to drain everything and reset to zero) by simultaneously pressing two buttons linked by a line on the control panel, I heard noises in the sink like it was draining. After a minute, I was told to go ahead and open it up (yep, drained), turn it off and on, and then try running the cleaning cycle again. And, voila, it worked! (Yay!)

So, what‘s wrong with this picture? First of all, there should be a clear explanation of what the icon means, as indicated above. Second, it should be clearly tied to a process to address the problem, including intermediate steps.This is so common, I am quite boggled that the great engineers that made our (very good) dishwasher aren‘t complemented with a great technical communications team who write up a useful manual to support. It. Is. Just. Silly!

Note: this isn‘t a learning experience. It‘s just fine that I don‘t recall what the last time‘s icon was or what it meant, and maybe what this icon meant and what I should do. It should be infrequent enough that it‘d be unreasonable for me to have to recall. Instead, I should be able to look it up. Put information in the world!  In the long term, this should save them buckets of money because most people could self help. Clearly, they‘ve gone to numeric codes, but they could‘ve just added in the associated icons, or given a mapping from icon to numeric code. Something to help folks who have the pics.  

This is just bad design, and it‘s so obvious how to ameliorate it. People will self-help many times, but only if they can!   Just as you shouldn‘t be creating a training course when a job aid will do, you can save a help call when a job aid can address most of the problems. Use performance support when it makes sense, and doing so comes from understanding how we actually think, work, and learn. When you do, you can design solutions that meet real needs. And that‘s what we want to do, no?

Update on my webinars

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I know, I know, I’ve been doing a lot of updates: books, workshops, and now webinars. I promise I’ll get back to my regular posting on learning things, but the benefit of these, unlike books or courses, is that they’re free. And several are coming up! So I thought I’d at least let you have a chance. So, here’s an update on my webinars.

First, I’ll be talking for eLearning Learning on the 27th of January at 11AM PT (2PM ET). They were interested in discussing about the impact on Covid, and of course I’m taking it in an aspirational direction. I’m presenting about how we’re not well aligned with how we think, work, and learn, and what that looks like in general, and in particular online.

Then, I’m doing a ‘make it meaningful’ presentation for iSpring on 25 Feb at 9AM PT (noon ET). The coordinates to sign up are here.   It aligns with their theme and I’ll get into some top-level issues.

Then, on 18 March, at 10AM, I’ll talk with Barbara Covarrubias Venegas on facilitating innovation. Since here topic is on virtual space, I suspect we’ll focus there. It’s a LinkedIn Live event, you can see it as one of her list of interviews.

Finally, at 10 AM PT (1PM ET) on Thursday the 13th (not Friday), I’ll be talking learning science for ATD.  That, as yet, doesn’t have a page AFAIK. More info as it emerges.

(BTW, there’s a recording of my webinar last week on learning science.)

This actually presents a pretty fair coverage of my areas of focus, so if any one (or more) is of interest, here’s a chance to see my thoughts. My general focus, as I like to quip, is on those things L&D isn’t doing, and what they’re doing badly. Which is most everything! 😁  I’m sure more webinars will eventuate, but that’s it for now. So there you go, an update on my webinars. Hope to see you there!

Habits and variety

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Having heard it’s good for maintaining cognitive ability, I like to vary things. And, to keep doing things right, I like habits. Are these mutually exclusive? Maybe, but here’re some thoughts on habits and variety.

It’s been touted that a great way to fend off the diminishment of cognitive capability is to do things differently. So, for instance, turning off the hall light before going down the hall on your way to bed. That is, finding your way in the dark. And, in general, trying things different ways. The notion is, this continual active cognitive challenge keeps your thinking ability from decaying. And that’s a good thing.

On the other hand, habits are helpful. For instance, having a regular approach to brushing your teeth. If you’ve established a good approach regularly, muscle memory can carry you through a late bedtime. And, in general, habits can help us make sure we do certain things that are good for us.

Is there a reconciliation? Here’s my just brainstorming, but I think that  when you have a good awareness of the habit, varying it is a good procedure. You’re actively problem-solving, versus throwing yourself off balance at a bad time. So, taking on a challenge clear-headedly is good.

Now, we know that, for instance, training for emergencies and unexpected situations leads to better learning. That’s why varying practice is helpful. So wouldn’t unexpected challenges be even better? Probably, but I reckon we get enough of these in life anyway!  That time you find out that you’re out of tea unexpectedly. Or when your car won’t start. Then we have challenges. And despite our best habits, the world seems to find ways to thwart our plans.

Now, changing bad habits to good ones is even harder. And then there’s the difference between habits and ritual. But those’er topics for another time.

So there are my thoughts on habits and variety. Do it, when you can devote enough cognitive resources to still be successful. That’s my approach, at least. There’s enough randomness in my life otherwise!

(And, yes, I’m not filming this one. Got to it too late! The world, thwarting my plans…)

The plusses and minuses of learning science research

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A person who I find quite insightful (and occasionally inciteful ;) is Donald Clark. He built and sold Epic, an elearning company, and now he leads a learning AI company, Wildfire. He’s knowledgeable (for instance, having read up and summarized centuries of learning theorists), willing to call out bad learning, and he’s funny. And so, when he reported on a new study, I of course looked into it. And I find that it points out the plusses  and  minuses of learning science research.

To be clear, this is about his product, so there’s a vested interest. However, he’s got integrity; he’s not going to sully his reputation with a bad study. And, it’s a good study. It rightly demonstrates an important point. It’s just that it stops short of what we need for full  learning.

So, his product does something pretty amazing. You give it content, and it can not only answer questions about the content (as, for instance, some chat tools do), it can turn the tables and ask  you questions about the content. That is, it can serve as a sort of tutor. Which is all to the good.

What it can’t do, of course, is design meaningful practice. As Van Merriënboer’s Four Component Instructional Design (4C/ID) points out, you need to know the information, and you also need practice applying it. And I reckon we’re still far from that. So, while this is part of a whole solution (and Donald knows this), it’s not the full solution. He’s subsequently let me know it can do language tasks, which is impressive. I’m thinking more of contextualized scenarios, however.

The study demonstrates, as you might expect, that breaking up a video into reasonable chunks, and having system-generated questions asked in-between, led to 61% better retrieval, going from getting 8 to 14 questions right. That is a big improvement. it’s also impressive, since it’s generating those questions from video! That is, it parses the video, establishes a transcript, and then uses that to generate a knowledge base. Very cool.

And it’s a well-designed study. It’s got a control group, and a  reasonable number of subjects. It uses the same test material, for an AB comparison. Presumably, the video chunking was done by hand, into four pieces. The chunking and break might account for the difference, which wasn’t controlled for, but it’s still a big improvement. Granted, we know that watching a video alone isn’t necessarily going to improve retention (except, perhaps, over some other non-interactive way of dumping content). But still, this is good as it’s an improvement and a lot of work was saved.

What I quibble about, however, is the nature of the retrieval. The types of questions liable to be asked (and it’s not indicated), are knowledge questions. As suggested above, knowledge is a necessary component. But using that knowledge to make decisions in context is typically what our goals are. And to achieve such goals, you basically have to practice making decisions in context. (Interestingly, the topic here was equality and diversity, a topic he has complained about!)

Knowledge about a topic isn’t likely to impact your ability to apply it. What will  make a difference are actually doing things about it, like calling it out, having consequences, and actively working to remedy imbalances. And that requires separate practice. Which he’s acknowledged in the past, and rightly points out that his solution means you can devote more resources to that end.

Thus, the plusses of learning science research are we nibble away at the questions we need to answer, and find answers about the questions we ask. The minus, of course, is not necessarily asking the most important questions. It’d be easy to see this and say: “we’ve improved retention, and we’re done”. However, it won’t necessarily lead to reducing the behaviors being learned about, or building ability to deal with it.  There are plusses and minuses of learning science research, and we need to know the strengths, and limitations, of it when we hear it.

Thinking Transformation

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This pandemic has led to everyone scrambling to work digitally. And it‘s not really a transformation (which shouldn‘t be ‘digital first‘), but rather just ‘move what we do online‘. And that‘s understandable. Over time, however, I think we want to shift our mindset. And, I think a previous exercise in thinking transformation is valuable here. I‘m talking mobile.

When I originally was talking about mobile, I was doing so from a perspective of augmenting our brains. The 4C‘s framework was a way to think about core mobile affordance from a point of view of what mobile offers. Then I moved on to the role the devices play in our (working) life. It‘s about not just courses on a phone, but:

  • Augmenting formal learning: extending it
  • Performance support: cognitive augmentation
  • Social: tapping into the power of social and informal learning
  • Contextual: mobile‘s unique opportunity

And, I suggest, these are valuable ways to think about using technology in general to support us. On principle, I like to think about how technology supports our thinking (not the other way around ;). To future-proof what I propose is one driver, so tech changes don’t undermine relevance. Further, since mobile is a platform – a strategy not just a tactic – focusing on fundamentals makes sense.

For instance, elearning shouldn‘t look like just a classroom online. That can and arguably should be part of it, but there‘s more. It‘s about extending formal learning, not just delivering it. And aligning with how we really learn, because it really does have to be effective.

Similarly, with folks working from wherever, thinking about the support they need is important. What tools, aids, guides, etc., will help them work more effectively without their prior context? Let’s change workflows to align better with what‘s known about how we work.

And making people available in useful ways for communication and collaboration is important. The demands of online meetings are becoming more prevalent and onerous. Zoom fatigue is a thing!   How can we optimize the experience?

Contextual is more uniquely mobile, taking advantage of where and when you are (and other contextual factors), but we probably do need to account for them more astutely. If your kids are in the other room, what does that do to your ability to work? Here, of course, is the greatest difference from mobile, but the mindset is still relevant.

So, for instance, when I ran a mobile course for the Allen Academy, we had a week dedicated to each of these elements (as well as kicking off a mobile mindset and closing on strategy). Given that it was still early in this new world, I didn‘t really push the thought of how this is a more general tactic. Of course, I now would.

And, given that I‘ll be running the course again, I definitely will! Look, mobile hasn‘t gone away, and we‘re possibly using mobile tools more now even though we‘re not on the road! So mobile‘s still relevant, and the mindset behind ‘thinking mobile‘ is even more relevant. I’ll be talking with Christopher Allen of Allen Interactions about it tomorrow (12 Aug) at 11AM PT, 2 Eastern (see below). And, if you‘re interested in the course, check it out!

Wanna talk meaning, learning science, and more…?

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The L&D conference, starting today, has a wide variety of things going on. I’m actually impressed, because in addition to the asynchronous and synchronous sessions I knew about, there are a number of other things going on. Including things I’m in. So, do you wanna talk meaning, learning science, and more…? Here’s when and how.

In addition to the presenters who have prepared asynchronous learning experiences, and the live presentations by the same and others, there are other things going on. There are panels on, for instance, on diversity & inclusion, state of learning, learning technology, women in learning, as just a few. There are also debates on games, evaluation, to e- or not to e-, at least. Lots of interesting topics. But wait, there’s more!

There are also networking sessions, a quiz show, roundtable breakouts, breakfast/cocktail (depending on timezone) networking, … There are also some interviews with prominent folks, both specifically for the conference and some legacy ones courtesy of Guy Wallace (HPT guru). And there’s either or both of more I don’t know about, and more to come.

A special mention for the CrowdThinking project, in collaboration with IBSTPI. My colleague, Fernando Senior, will be leading an event to understand the current and anticipated requirements for L&D roles. And there’s a survey you’re requested to fill out regardless of whether you’re attending the conference. Please help!

As for me, first, my asynchronous session is on Learning Science 101. I’ve created some short videos that talk about, and illustrate, a number of things our cognitive architecture has to account for. And, hint hint, it presages something hopefully to be announced soon.

My synchronous sessions (two different times; they’re making a serious effort to reach out globally) are 3PM ET (noon PT) Wed July 1, and 11AM ET (8AM PT) on July 8. Here, I’ll be talking about what I think is a huge missed opportunity and addressable (tho’ not simple) element of our learning design. I’ll also be part of the panel on learning science (The State of Learning) 8AM PT July 9 and 11 AM PT July 17. And, a reprise of the great debate on evaluating learning or impact (4PM PT 25 June).

And, importantly, I’ll be holding some office hours where we can truly talk about learning science, meaningfulness, and more! So will the other presenters. (They’re still to be set; I’ll update here when I know!)

Of course, there is a host of other really great speakers. Have a look at this lineup! Also, guests for a variety of things will include people like Charles Jennings & Jos Arets, Paul Kirschner, and many many more. Most of the live sessions have two times, so there’s a good chance you can catch them sometime. And there’s no overlap (so far ;), but things going on every day.

If, by the way, you are thinking about attending the  conference, but have some struggles with cost, get in  touch  with me. I may have a way to help out ;).   I hope to see you there, whether you want to be talking meaningful learning, or for any of the other myriad reasons.

As you can probably infer, I’m interested in this. It’s not surprising, but most online events have mimicked face-to-face events. Webinars, basically. Here there’s more going on. I don’t expect all of it to work (though it all sounds good), but I love that they’re experimenting to find ways to go beyond. We’ll all learn from this initiative. Hope to see you there if you wanna talk meaning, learning science, and more…

 

Adapting to change

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We live in interesting times. And, of course, that means many things have changed. Some for the worse, some for the better. I thought I’d just overview some of ways I’m adapting to change, so you can keep track and take advantage.

I was scheduled to do a number of things. One that wasn’t on the list was a trip to Brazil in May, also to give a talk (at least). And, of course, Boston, Brazil,  and Belgium have all been postponed. Understandably. And, sadly, my Quinnsights column had to cease. That might seem, then, to take away all opportunities for me to educate, but in the meantime, in addition to my ongoing Litmos blog (at least for now!), other things have surfaced.

For one, I’ll be doing a course for the Allen Academy.   I’ll be talking about mobile learning, a topic I’ve had  some experience with ;). It starts soon, 6 May. I’ll be clear: it’s about ‘thinking’ mobile, which means getting your mind around much much more than ‘courses on a phone’. And it’s about design and strategy, not development. No bit spinning. After all, I’ve quipped about the importance of getting the design right.

Another is the upcoming L&D conference. I’ll be talking “Learning Science 101”, which I think is much needed and also doable. This is a new online event conjured up by some colleagues to meet a need. And, I’m happy to say, there’s a lot to like: thinking really hard about how to take advantage of online for conference-style learning, a great lineup of speakers. This starts June 22, and last 6 weeks, so already you can see it’s different.

Two other non-event things to note. My first two books,  Engaging Learning  and  Designing mLearning, were out of print. Fortunately, when that happens, publishing contracts say the rights can revert to the author if they request it. And…they did!   I’ve taken them with minimal modification (had to remove one case study from the latter; some minor tweaks), and made them available through Kindle. At a greatly reduced price!

And, of course, I’m still working in a variety of ways. Including being available to help you with moving courses or working online. And scheming up more things. I’m tentatively scheduled for another tome, and one was already underway. Somewhat under wraps still, but…

So those are the things I’m doing adapting to change. Not to worry, there’ll be more, in this volatile age. I’m trying to practice what I preach about experimentation, so there’ll likely be other new things percolating. Stay tuned!