I was on LinkedIn, and noted this list of influences in a profile: “complex systems, cybernetics, anthropology, sociology, neuroscience, (evolutionary) biology, information technology and human performance.” And, to me, that’s a redundancy. Why?

A while ago, I said “Departments of cognitive science tend to include psychologists, linguists, sociologists, anthropologists, philosophers, and, yes, neuroscientists. ” I missed artificial intelligence and computer science more generally. Really, it’s about everything that has to do with human thought, alone, or in aggregate. In a ‘post-cognitive’ era, we also recognize that thinking is not just in the head, but external. And it’s not just the formal reasoning, or lack thereof, but it’s personality (affect), and motivation (conation).

Cognitive science emerged as a way to bring different folks together who were thinking about thinking. Thus, that list above is, to me, all about cognitive science! And I get why folks might want to claim that they’re being integrative, but I’m saying “been there, done that”. Not me personally, to be clear, but rather that there’s a field doing precisely that. (Though I have pursued investigations across all of the above in my febrile pursuit of all things about applied cognitive science.)

Why should we care? Because we need to understand what’s been empirically shown about our thinking. If we want to develop solutions – individual, organizational, and societal –  to the pressing problems we face, we ought to do so in ways that are most aligned with how our brains work. To do otherwise is to invite inefficiencies, biases, and other maladaptive practices.

Part of being evidence-informed, in my mind, is doing things in ways that align with us. And there is lots of room for improvement. Which is why I love learning & development, these are the people who’ve got the most background, and opportunity, to work on these fronts. Yes, we need to liase with user experience, and organizational development, and more, but we are (or should be) the ones who know most about learning, which in many ways is the key to thinking (about thinking).

So, I’ve argued before that maybe we need a Chief Cognitive Officer (or equivalent). That’s not Human Resources, by the way (which seems to be a misnomer along the lines of Human Capital). Instead, it’s aligning work to be most effective across all the org elements. Maybe now more than ever before! At least, that’s where my thinking keeps ending up. Yours?

So, I’m writing, again. Not a book (at least not initially ;), but something. I’m not sure exactly how it’ll manifest, but it’s emerged. Rather than share what I’m writing (too early), I’m reflecting a bit on the process.

As usual, I’m writing in Word. I’d like to use other platforms (Pages? Scrivener? Vellum?), but there are a couple of extenuating circumstances. For one, I’ve been using Word since I wrote my PhD thesis on the Mac II I bought for the purpose. I think that was Word 2.0, circa late 80’s. In other words, I’ve been using Word a long time! Then, the most important thing besides ‘styles‘ (formatting, not learning) is the ability to outline. Word has industrial-strength outlining, and, to use an over-used and over-emphatic point, I live and die by outlines.

I outline my plan before I start writing, pretty much always. Not for blog posts like this, but for anything of any real length beyond such a post. Anything with intermediate headings is almost guaranteed to be outlined. I tend to prefer well-structured narratives (at least for non-fiction?). It likely will change, of course. When my very first book was written, it pretty much followed the structure. Ever since then…  My second book had me rearranging the structure as I typed. My most recent book got restructured after every time I shared it with my initial readers, until suddenly it gelled.

In this case, and not unlike most cases, I move things around as I go. This should be a section all its own. That is superfluous to need. This other goes better here than where I originally put it. And so on. I do take a pass through to reconcile any gaps or transitions, though I try to remedy those as I go.  The goal is to do a coherent treatment of whatever the topic is.

I throw resources in as I go. That is, if I find myself referring to a concept, I put a reminder in a References or Resources section at the end to grab a reference later. I have a separate (ever-growing) file of references for that purpose. Though I may not always include the reference in the document (currently I’m trying to keep the prose lean), but I want folks to have a resource at least.

I also jump around, a bit. Mostly I proceed from ‘go to whoa’, but occasionally I realize something I want to include, and put a note at the appropriate place. That sometimes ends up being prose, until I realize I need to go back to where I was ;). I hope that it leads to a coherent flow. Of course, as above, I do reread sections, and I try to give a final read before I pass on to whatever next step is coming. Typically, that means sending to someone to see if I’m on track or off the rails.

I also am pondering that I may retrofit with diagrams. Sometimes I’ve put them in as I go. At other times, I go back and fill them in. I do love me a good diagram, for the reasons Larkin & Simon articulated (Connie Malamed is doing a good job on visuals over at LinkedIn this month). Sometimes I edit the ones I have as I recognize improvements, sometimes I create new ones, sometimes I throw existing ones in. It’s when I think they’ll help, but I can think of several I probably should make.

The above holds true for pretty much all writing I do beyond these posts. This is for me, first, after all! Otherwise, I solicit feedback (which I don’t always get; I think folks trust me too much, at least for shorter things). I’m sure others work different. Still, these are my thoughts on writing, again. I welcome your reflections!

Last week, I expressed my gratitude for folks from this past year. That’s looking back, so it’s time to gaze a touch ahead. With some thoughts on the whole idea! So here’s looking forward to 2025. (Really? 25 years into this new century? Wow!)

First, I’m reminded of the talk I heard once. The speaker, who’d if memory serves had written a book about predicting the future, explained why it was so hard. His point was that, yes, there are trends and trajectories, but he found that there was always that unexpected twist. So you could expect X, but with some unexpected twist. For instance, I don’t think anyone a year ago really expected Generative AI to become such a ‘thing’.

There was also the time that someone went back and looked at some predictions of the coming year, and evaluated them. That didn’t turn out so well, including for me! While I have opinions, they’re just that. They may be grounded in theory and 4+ decades of experience, but they’re still pretty much guesswork, for the reason above.

What I have done, instead, for a number of years now is try to do something different. That is, talk about what I think we should see. (Or to put it another way, what I’d like to see. ;). Which hasn’t changed much, somewhat sadly. I do think we’ve seen a continuing rise of interest in learning science, but it’s been mitigated by the emergence of ways to do cheaper and faster. (A topic I riffed on for the LDA Blog.) When there’s pressure to do work faster, it’s hard to fight for good.

So, doing good design is a continued passion for me. However, in the conversations around the Learning Science conference we ran late this year, something else emerged that I think is worthy of attention. Many folks were looking for ways to do learning science. That is, resolving the practical challenges in implementing the principles. That, I think, is an interesting topic. Moreover, it’s an important one.

I have to be cautious. When I taught interface design, I deliberately pushed for more cognition than programming. My audience was software engineers, so I erred on getting them thinking about thinking. Which, I think, is right. I gave practical assignments and feedback. (I’d do better now.) I think you have to push further, because folks will backslide and you want them as far as you can get them.

On the other hand, you can’t push folks beyond what they can do. You need to have practical answers to the challenges they’ll face in making the change. In the case of user experience, their pushback was internal. Here, I think it’s more external. Designers want to do good design, generally. It’s the situation pragmatics that are the barrier here.

If I want people to pay more attention to learning science, I have to find a way to make it doable in the real world. While I’m finding more nuances, which interests me, I have to think of others. Someone railed that there are too many industry pundits who complain about the bad practices (mea culpa). That is, instead of cheering on folks that they can do better. And I think we need both, but I think it’s also incumbent to talk about what to do, practically.

Fortunately, I have not only principle but experience doing this in the real world. Also, we’ve talked to some folks along the way. And we’ll do more. We need to find that sweet spot (including ‘forgiveness is easier than permission’!) where folks can be doing good while doing well.  So that’s my intention for the year. With, of course, the caveat above! That’s what I’m looking forward to. You?

The good news is, the Learning Science Conference has gone well. The content we (the Learning Development Accelerator, aka LDA) hosted from our stellar faculty was a win. We’ve had lively discussions in the forum. And the face to face sessions were great! The conference continues, as the content will be there (including recordings of the live sessions). The open question is: what next? My short answer is going beyond learning science.

So, the conference was about what’s known in learning science. We had topics about the foundations, limitations, media, myths, informal/social, desirable difficulty, applications, and assessment/evaluation. What, however, comes next? Where do you go from a foundation in learning science?

My answer is to figure out what it means! There are lots of practices in L&D that are grounded in learning science, but go from there to application. My initial list looks like this:

1. Instructional design. Knowing the science is good, but how do you put it into a process?
2. Modalities. When you’re doing formal learning, you can still do it face to face, virtually, online, or blended. What are the tradeoffs, and when does each make sense?
3. Performance consulting. We know there are things where formal learning doesn’t make sense. We want gaps and root causes to determine the right intervention.
4. Performance support. If you determine job aids are the answer, how do you design, develop, and evaluate them? How do they interact with formal learning?
5. Innovation. This could (and should; editorial soapbox) be an area for L&D to contribute. What’s involved?
6. Diversity. While this is tied to innovation, it’s a worthy topic on its own. And I don’t just mean compliance.
7. Technology. There are lots of technologies, what are their learning affordances? XR, AI, the list goes on.
8. Ecosystem. How do you put the approaches together into a coherent solution for performance? If you don’t have an ‘all singing, all dancing’ solution, what’s the alternative?
9. Strategy. There’s a pretty clear vision of where you want to be. Then, there’s where you are now. How do you get from here to there?

I’m not saying this is the curriculum for a followup, I’m saying these are my first thoughts. This is what I think follows beyond learning science. There are obviously other ways we could and should go. These are my ideas, and I don’t assume they’re right. What do you think should be the followon? (Hint: this is likely what next year’s conference will be about. ;)