Learnlets

Last week, Donald Taylor wrote an interesting post, wondering about ‘learner engagement’. That’s a topic I do talk a wee bit about ;). He closed with a call for feedback. So, while I did comment there, I thought it potentially would benefit from a longer response. I think it’s more general than learner engagement, so I’m talking about engaging people at work. (But it’s still relevant to his thesis without quibbling about that!)

In his post, he talked about three levels: asset, culture, and environment. I’m not sure I quite follow (to me, culture is an environmental level), and I’ve talked about individual, team, and organizational levels. To his point, however, there are steps to take at every level.

He starts at the individual level, talking about designing learning experiences. I agree with his ‘do deeper analysis’ recommendation, but I’d go further. To me, it’s not just if they recognize that content’s valuable, it’s about building, and maintaining, motivation while controlling anxiety (c.f. Make It Meaningful!). I don’t think he’d disagree.

At the next level up, it’s about making sure people are connected. Here, I’d point to Self-Determination Theory (SDT), and ‘relatedness’. I don’t mind Dan Pink’s reinterpretation of that to ‘purpose’, in that I think people need to know how what they’re doing contributes to something bigger, and that something bigger supports society as a whole.

Finally, to me, is culture. You want a ‘learning organization‘, as Don agrees. He says to start with a sympathetic manager, but I think L&D needs to create that culture internally first, then take it to the broader organization (and starting with said manager is a good next step).

I think that latter step solves Don’s final step of breaking down barriers, but he’s a smart guy and I’m willing to believe I’m missing some nuance. I do like his focus on ‘find a measure’ to use. However, ultimately, it should improve a lot of measures around adapting to change: innovation, retention, and success.  That’s my take, I welcome yours!

I maintaining a fascination in design, for several reasons. As Herb Simon famously said: “The proper study of mankind is the science of design.” My take is to twist the title of Henry Petroski’s book, To Engineer is Human into ‘to design is human’. To me, design is both a fascinating study in cognition, and an area of application. The latter of which seems to be flourishing!

I’ve talked in the past about various design processes (and design overall, a lot). As we’ve moved from waterfall models like the original ADDIE, we’ve shifted to more iterative approaches. So, I’ve mentioned Michael Allen’s SAM, Megan Torrance’s LLAMA, etc.

And I’ve been hit with a few more! Just in the past few days I’ve seen LeaPS and EnABLE. They’re increasingly aware of important issues in learning science. All of this is, to me, good. Whether they’re just learning design approaches, or more performance consulting (that is, starting with a premise that a course may not be the answer), it’s good to think consciously about design.

My interest in design came in a roundabout way. As an undergrad, I designed my own major on Computer-Based Education, and then got a job designing and programming educational computer games. What that didn’t do, was teach me much about design as a practice. However, going back to grad school (for several reasons, including knowing that we didn’t have a good enough foundation for those game designs) got me steeped in cognition and design. Of course, what emerges is that they link at the wrists and ankles.

So, my lab was studying designing interfaces. This included understanding how we think, so as to design to match. My twist was to also design for how we learn. However, more implicitly than explicitly perhaps, was also the topic of how to design. Just as we have cognitive limitations as users, we have limitations as designers. Thus, we need to design our design processes, so as to minimize the errors our cognitive architecture will introduce.

Ultimately, what separates us from other creatures is our ability to create solutions to problems, to design. I know there’s now generative AI, but…it’s built on the average. I still think the superlative will come from people. Knowing when and how is important. Design is really what we want people to do, so it’s increasingly the focus of our learning designs. And it’s the process we use to create those solutions. Underpinning both is how we think, work, and learn.

To design is human, and so we need to understand humans to design optimally. Both for the process, and the product. This, I think, makes the case that we do need to understand our cognitive architecture in most everything we do. What do you think?

FWIW, I’ll be talking about the science of learning at DevLearn. Hope to see you there. 

Ok, so I admit that I’m a bit of a pedant (and I hear you, saying “a bit?”). So, when I see categorizations, I should be more accepting of pragmatic approaches. Yet, I still get upset when I see same, when there are clear conceptual breakdowns that could be used instead. My hypothesis is that the good conceptual ones end up making the discriminations (eventually), with perhaps a bit more explanation needed, but…they don’t leave misconceptions as likely to occur. Thus, I’m not sure I’m happy with sloppy thinking.

One example comes from a textbook I’m reviewing. They’re talking about performance support, and differentiate between EPSS (electronic performance support systems), PSS (performance support systems), and MPSS (mobile performance support systems). First, wouldn’t you start with PSS as the beginning point? The definition used is online and offline. OK, so I can see EPSS as a subset of that. It’s only online, right? So why does it lead the list?

Then, MPSS is a separate category. Isn’t it a subset of EPSS? They note that it is, in fact, an EPSS on a mobile device. So it’s a subset of the first category. You’re going from the middle category to the broader and then to the narrower. That confounds a general trend to follow an order, increasing or decreasing, rather than apparently random. They do note that MPSS can do location-specific things, but that’s also a subset of doing contextually-based things. So, a wee bit facile, it seems to me.

Similarly, I’ve seen a categorization of game technologies, including having spreadsheet-based as a different category from branching. Yes, but spreadsheets are just a mechanism to implement a formal model. It can be in a spreadsheet, or code. Why does the implementation matter? Pragmatically, yes, it matters, but then have spreadsheets and code-implemented as subsets of programmed models. For that matter, you could have an analog implementation of the model!

These are fairly rigorous criteria, whereas all too often I’ll see a list of things (e.g. things you should/never do for X) that aren’t of the same type. Clearly, it’s a marketing person just aggregating a list of things, without a true understanding. I think it’s problematic, however. For one, it’s a missed opportunity to reflect important conceptual distinctions (can you tell I’ve been an educator?). For another, it might lead people to think that being scattershot is ok. Finally, it might undermine the actual development of important categorizations.

I’m willing to believe that, for practical reasons, people do need the pragmatic distinctions. I just feel that the conceptually clear ones can yield that, too. Yes, again, it may take a little more exposition, but isn’t educating folks part of the job too (e.g. good marketing is good customer education)? So, while I feel a wee bit of an old man yelling “get off my lawn”, this is the reason why I struggle with sloppy thinking. Am I off base?

I”ve advocated, repeatedly, the importance of practice. Yet, too often, we still see an ‘event’-based model, where it’s one and done. Unfortunately, this doesn’t align with how our brains work! I was looking at one of Elevator 9‘s Liftology videos (caveat: I did the original scripting), where they mentioned ‘practice like we play’. I’d heard it before (in various incarnations), but this time it struck me that perhaps it’s the right vehicle to penetrate complacency about learning design. Should we emphasize “we play as we practice”?

The underlying phenomena is that we need lots of practice, for two reasons. For one, the ‘learning’ mechanism that strengthens our learning can only do so much before it needs sleep. If you want to truly develop a skill, sufficient practice, over time, is required. It’s like building muscle, or training for a sport; occasional practice isn’t sufficient. The right practice, repeated and improved over time, is necessary.

The other is that we are very context sensitive. That is, our consciousness is very much influenced by where and how things are happening. If you want to successfully generate transfer to many different situations (such as sales, or negotiation, or…things that happen in many different contexts with different people and different goals and…), you need sufficient practice across contexts. Our brain abstracts across the contexts seen to determine the space of transfer. Thus, we need widely varied practice to generate a generalized ability to do. 

Yet, too often, we see people getting it right ‘once’, and thinking that’s enough. It might be sufficient to tick a box, but it’s not sufficient to generate a new ability. The problem is, there’s a lot of pressure against this. Folks don’t want to take the time and money, they want to believe that new information will yield a behavior change, it’s just too hard!

So, I’m wondering if rethinking the messaging will help. If we emphasize that what we do is dependent on what we practice, maybe we can get away from the school mentality of ‘study, pass test, forget’. We want to get to the ‘practice practice practice to be good enough to play’ mentality.

I don’t know if “we play as we practice” is the best vehicle, or even one, but I’m kinda desperate, I guess. I’m very very tired of folks not getting that meaningful change requires sustained effort. And I’m really looking for a solution. It seems like this might tap into some useful mental frameworks. Can this help? If not, do you have a better solution? Please?

A colleague recently suggested that I write about how I get so much done. Which is amusing to me, since I don’t think I get done much at all! Still, her point is that I turn around requests for posts the next day, generate webinars quickly, etc. So, I thought I’d talk a bit about how I work (at risk of revealing how much I, er, goof off). It’s all about not working harder! It may be that I’m not doing a lot compared to folks who work in more normal situations, but apparently at least perceived as productive.

So, as background, I have a passion for learning. I remember sitting on the floor, poring through the (diagrams in) the World Book. My folks reinforced this, in a story I think I’ve told about how the only excuse for being excused from the dinner table was looking things up. Actually, while I did well in school, it wasn’t perfect because I was learning to learn, not to do well in school. That was just a lucky side effect. I went on and got a Ph.D. in cognitive science, which I argue is the best foundation for dealing with folks. (Channeling my advisor.)

So, I’ve been lucky to have a good foundation. I do recall another story, which I may have also regaled you with. This is about my father’s friend who succeeded in a job despite having stated to the effect that if it appeared he was asleep, he was working, and he’d still do the work of two. (He did.) The point being, that taking time to learn and reflect was useful. I did the same, spending time reading magazines with my feet up on the desk in my first job out of college, but still producing good work.

That’s continued. Including through my graduate school career, academic life, workplace work, and as a consultant. The latter wasn’t my chosen approach, it was involuntary (despite appearing to be desirable). Somehow, it became a way of life. (And I’ve realized there are lots of things I wouldn’t have been able to do if I had had a real job).  What I do, regularly, are two major things which I think are key.

The first is that I continue to learn. I read (a lot). Partly it’s to stay up on the news in general, but also try to track what happens in our field. I check in on LinkedIn, largely through the folks I follow. I’ve tried to practice Harold Jarche’s PKM, as I understand it. That is, I update the folks I follow (on a variety of media), as well as media (for instance, Twitter is dwindling and I’m now more on Mastodon).

I also allow time for my thoughts to percolate. For instance, I take walks at least a couple of times a week. I can put a question or thought in my mind and head out. To capture thoughts, I use dictation in Apple’s Notes. I also read fiction and play games, to allow thoughts to ferment. (My preferred metaphor, you can also choose percolate or incubate. ;).  I even do household chores as a way to allow time to think. Basically, it looks like I’m spending a lot of time not working. Yet, this is critical to coming up with new ideas!

I also take time to organize my thoughts. Diagramming things is one way I understand them. I blog (like this), for the same reason. These are my personal processing mechanisms. When I do presentations and write articles for others, they’re the result of the time I’ve spent here. If you look at Harold’s process, I set up good feeds to ‘seek’ (and do searches as well), I process actively, through diagramming and posting, and then I share (er, through posting) and presentations and workshops and books and…

Note that it’s not about remembering rote things, but it’s about seeing how they connect. That takes time. And work. But it pays off. I’ll suggest that turning the ideas into models, connected causal stories, helps. So, it’s about understanding how things work, not just ‘knowing’ things. It’s about being able to predict and explain outcomes, not just to tout statistics and facts.

With this prep, I can put together ideas quickly. I’ve thought them through, so I have formed opinions. It’s then much easier to decide how to string them together for a particular goal. The list of things I’ve thought about continues to grow (even if I’ve forgotten some and joyfully rediscover!). I can write it out, or create a presentation, which are basically just linear paths through the connections.

How do I have time to do this? Well, I work from home, so that makes it easier. I also don’t work a regular job, and have gotten reasonably effective at using tools to get things done. For instance, I’m now using Apple’s Reminders to track ‘todos’, along with its Calendar. (I’m cheap, so I’ve used fancier tools, but have found these suffice.) Needless to say, I’m quite serious when I say “if a commitment I make doesn’t get into my device, we never had the conversation.”

Thus, it’s about working smarter. I don’t have an org, so it’s just my practices. If you saw it, you’d see that it’s bursts of productivity combined with lots of ‘down time’. That’s hard to see, as an org, yet that’s the way we work best. As we start having tools that automate more of our rote tasks, we should retain doing creative things like painting, music, and more, not relegate that to AI. Then we can start working more like the creative beings we are, and start recognizing that taking time out for the non-productive is actually more productive. That’s how we work smarter, and are not working harder.