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Clark Quinn’s Learnings about Learning

Still the myths

11 November 2025 by Clark Leave a Comment

Over on LinkedIn, about the last site worth visiting (I do use Bluesky and Mastodon, but they’re not really ‘sites’ so much as channels), I am still seeing quotes about people believing in misinformation. Learning styles, generations, attentions spans dropping, etc, all these things that aren’t valid are still being touted. Despite our debunking efforts, it’s still the myths!

To be fair, we do seem to be seeing a bit of an ‘anti-science’ movement. Which would be not only silly, but sad! Sure, there are problems with science, but it still beats every other process we have. Anecdotes don’t surpass real evidence, and personal opinion isn’t superior to what proper research tells us.

For one, as Naomi Oreskes makes clear in her book Why Trust Science, what makes science work isn’t just the process. So, yes, scientists conduct experiments, and others review them, and it’s a collective decision to publish them. And, yes, bad papers are still submitted (I used to serve on editorial boards, and my rejection rate was about 95%; but it was a good journal ;). Also, it’s hard to bring in new viewpoints. What Oreskes points out, however, and aptly, is that over time, these processes advance our understanding. We may have fits and spurts, but for the long game we win. For instance, how are you able to read this offering of mine, over miles and minutes? Because science.

So, science denial is counter-productive, but it exists. Gale Sinatra and colleague Barbara Hofer, in their book Science Denial, outline the reasons how this happens. Based upon research into the situation, they document our minds have biases, and how we can be swayed. We can also have our own beliefs, and our tendency to confirmation bias means we only look for evidence that supports our views. Fortunately, they discuss ways to address these problems, but we need to put some of these into place (as with Brian Klaas’ recommendations for fighting corruption).

We have good data that there are things we should avoid. There really aren’t any psychometrically valid instrument for learning styles, and no evidence that should use them if we did. Categorizing people by generations is, basically, a form of stereotyping. Our attentions spans can engage for hours even, as we play games, read novels, watch movies, etc. And so on!

Sometimes, it feels hopeless. But I look and see that we’re getting more attention to learning science. It really is about communication, and it seems we’re (slowly) making headway. So, I’ll keep keeping on (heck, I wrote the book!), despite ‘still the myths’. Hopefully, fewer and less over time. Fingers crossed!

Conference season

28 October 2025 by Clark Leave a Comment

Conference season has commenced. Two are already in the books. Three I know about are coming up, and I’m playing a role in two. So, what’s up, and when? Here’s what I know.

So, first, the Learning Development Accelerator (LDA) is running the Creating a Motivating Work Environment Summit. This is in conjunction with the Center for Self-Determination Theory, so it’s scrutable. I’m not part of this, except as a participant. It follows the usual LDA format: access to videos created by the presenters, followed by live sessions at two different times. The videos are already up, and the live sessions are coming soon, Nov 3 – 7!  It’s all online, which makes it easy to attend, and the live sessions will be recorded. There’s a stellar lineup of speakers, naturally! I’m increasingly finding the value in the theory, so I look forward to the session. Caveat: I’m a Co-Director of the LDA, so I have a vested interest in the success, but I still think it’s of interest (at least to me).

Then, the Learning Guild is holding the next DevLearn conference, and I’ll be doing several things. My Wed is pretty full, as I’m starting by hosting a Morning Buzz on building a learning culture. Hosting isn’t the same as presenting, but instead just facilitating the conversation.  Then I’m presenting on the spacing of learning. I’ve been actively engaged in developing a spaced learning strategy, and will be sharing the key principles from learning science research. As well as what’s not (yet) known! I’ll be signing books right after that at the event bookstore. On Thursday, I’m part of a panel on AI (which will probably be interpreted as Generative AI), and will be my usual critical self ;). Of course, I’ll also be wandering the halls and expo. If you’re there, say hello!

Finally, the LDA is also running our second Learning Science Conference. (If you attended last year, you get a big discount!). It uses the same format asa the Motivation Summit, above, that is with specifically curated content in presentations, and live sessions Dec 8 – 12. It starts 3 Nov, and I’m active in this one too. I’ll again be presenting two sections. The first will be on getting information into, and out of, long-term memory, specifically generative and retrieval practice. I talked about the latter, last year, so I’m refining that (my own understanding evolves as does the field), and adding more on generative. Similarly with social and informal learning, which I’ll be presenting again. That is, I’ll be rehashing the old, and adding a bit new.

There’re new speakers, too. We’ve the honor of having Gale Sinatra and Jim Hewitt, and Rich Mayer will be doing a special session with Ruth Clark. Other presenters include my fellow co-Director, Matt Richter, along with Stella Lee and Nidhi Sachdeva. There’ll be special sessions, such as with Will Thalheimer.  Of course, we’ll have a debate, here with me going head to head with authors Bianca Baumann and Mike Taylor on marketing and motivation.  We also will have a panel with greats Julie Dirksen, Jane Bozarth, and Koreen Pagano. And more.

Sure, there’re lots of ways to get on top of learning science and good design. There’s the Serious eLearning Manifesto, books (e.g. my recommended reading list), blogs (like this one), magazines likeTraining, eLearn, journals, and more. However, getting together with your fellow practitioners, live or online, is a real boon, and so conference season is a great opportunity. Hope to see you somewhere soon!

Generative visualized?

21 October 2025 by Clark Leave a Comment

Ok, so I shared that I was trying to visualize the generative process. Which is, to be fair, aka elaboration. And, I did take a stab. So I thought I’d share what I’d come up with for generative visualized. Two reasons: 1) for you to quibble with what I came up with, and 2) learning out loud. I reckon if you can see my process, you may learn, you may improve it, all the good things that happen from sharing. So…

First, I was looking to do a higher build than the neural level. Yes, at the neural level we’re strengthening patterns across neural networks. We’re taking two patterns and putting them into conjunction, basically, activating both. That activating in conjunction strengthens the links between them, associating them more. (I’ve a diagram on that, actually, emphasizing that they need time to recover before the next strengthening. If you’re interested, let me know and I’ll share that, too.) But the way we activate patterns is by using words or images, semantically. So, I was looking for words.

They also should be ideas that are familiar enough that I’m not requiring knowledge you don’t know. Further, I need to be making associations that you’d get. So, something familiar. In this case, animals and pets. (Perhaps that’s salient to me, for some reason.) And I needed a relationship between them. I chose, rightly or wrongly, the notion of how wild animals don’t make good pets. So, what’s this look like?

Now, I’m showing the final build, not the whole process. You start with something you’re talking about, like how there are good and bad pets (“do raccoons make good pets?”). And you ask the learners to find some personal or conceptual basis for that distinction. They can find examples, like that good pets are domesticated animals, and bad pets are wild, drawing on their previous knowledge. Or, they might talk about someone who had a bad pet (“my friend’s parents had this pet monkey, but it was always doing bad things”). Of course, pets are a subset of animals, so this becomes confusing at the top level, but that’s okay, as the structures are similar but not exactly the same.

The point is that they’re generating this information, actively connecting their own pre-existing knowledge to the information you’d like them to acquire. It’s causing them to elaborate, and so strengthening the links in their mind. Which is what we want. So, that’s my attempt to capture generative visualized. Does it work, or do you have ideas to improve or replace?

FWIW, this is part of what I’ll be presenting at the LDA’s Learning Science Conference, starting Nov 3 to review the presentations and discuss, with live sessions with the presenters Dec 8-12. Same format as last year (with recognition of that in pricing, for those that attended), but with some new content and presenters. It’s still the things we think you need to be an informed learning designer. 

How to visualize generative?

14 October 2025 by Clark Leave a Comment

I’ve been thinking a fair bit about generative learning of late. Not least, because it’s one of the things I’ll be talking about at our LDA Learning Science Conference, coming up (Nov for the background vids and discussion, early Dec for the week of live with presenters). It’s a refresh of the successful event we held last year, but keep what worked, and adding what’s new! And, I’m still wrestling with it, particularly how to represent it!

First, generative learning is the complement to retrieval practice. Research by luminaries such as Robert Bjork, Henry Roedigger, Ericsson, etc, have told us of the value of retrieval practice for memory. Which is all about strengthening our ability to get information out of long-term memory to solve problems. However, we first need to get our models and examples into long-term memory first. I’ve previously termed this elaboration, but generative activities may be a more proactive way of thinking about it.

It’s really about connecting new information to old. We know that’s valuable! And we can present it, but generative activities have learners actively processing information. So, for instance, what Craik & Lockhart talked about as elaborative processing. We can connect it to personal experience, such as asking what this explains that we previously had observed. Or, we can (and must) connect it to previous information, so we can integrate it more tightly into our understanding. So, we can diagram it via a mindmap or otherwise, draw it, write it in different terms, etc. . I suggest that many of Thiagi and Matt Richter’s activities do just this!

Then, as you have probably know, I’m fond of diagrams. And so, I want to find a way to represent the value of generative learning, in ways we can remember and apply. What I’m struggling with is representing the process of elaboration. It could be a sequence of networks, but I’ve been somewhat loath simply because it seems like too much trouble! Which, of course, isn’t a good reason. Another reason (as he reaches for justification), is that networks are a level of abstraction away, and not really cognitive. So maybe I need to show concept relationships being formed?

As you can tell, I’m not really there yet. But, in the spirit of ‘learning out loud’, I thought I’d share where I am, not least to prompt some responses with ideas!  So, what ideas or pointers can you share?

The full story?

7 October 2025 by Clark Leave a Comment

As I continue exploring learning, I’m beginning to realize that the picture’s incomplete. Which shouldn’t be a surprise, but it’s a bit of a concern. Of course, I don’t have the answers, but if I point out some of the elements, maybe we’ll identify the gaps. And, I’m sure, there are likely initiatives and results I’m unaware of, and hopefully folks will help fill in the full story.

So, our endeavor is to start with people, with whatever experience and abilities they bring to the table. Then, ultimately (after our ministrations) have them capable of dealing with the situations we’ve identified are important. That includes what needs to be in long-term memory, and having responses aligned to triggers that activate the appropriate actions. Along the way, we have the analysis, the learning science, the coaching, and …?

I talked earlier about how most of our focus has been on getting folks up to some level of initial speed. But we do want folks to ultimately acquire the full range. And, I think, we too often abandon our efforts before getting the full way.

That makes sense for organizational learning, where we have to balance the costs with the value. When lives are on the line (aviation, medicine, military), we probably need to go a very long way. When it’s just inventory, we may allow some checks along the way to catch mistakes, and hope that people will eventually internalize the elements. (There are practices we spend on that are entirely worthless, of course.) For education, when we have kids in schools for years, it is clear that our pedagogy, driven by a wrong curriculum and values, falls far short of actually applying knowledge. But that’s another rant ;).

And we have pretty good guidance for many elements. We know about retrieval practice, with spacing, deliberate choices of next steps, desirable difficulty. We also know about generative activities. I’m not sure we’ve reconciled, however, how much of each. We also have cognitive load theory, which guides us in many ways, but doesn’t necessarily talk about acquisition versus application. The power law of learning suggests that we go from conscious to unconscious, but it assumes doing the right practice. The list goes on: multimedia learning, four component ID, cognitive apprenticeship, …; we have lots of pieces.

And yet, that’s still getting people up to a certain beginning level. How do we go beyond? The aforementioned is all about formal learning, and not about moving on. So we kind of have a hiccup between learning and coaching. How do they segue? We also have the issue of assessment. I have suggested that maybe we need to consider our commitment to apply as well as our ability. And that’s still before actually starting, yet we’re not done then.

Folks are talking about dispositions, I note, but when I look at it, it’s about the broader picture of persistence, etc, not specific to the particular outcome. Happy to be wrong here. But we really want to understand what we do initially, for instruction, for reactivation and continuation, to the final picture. My intuition is that there’s a more systematic structure that we’re not applying.

I don’t have an answer. Certainly not yet! I just think it’s time that we start thinking about it. Well, I guess that’s an open question: do we need an overarching approach? If so, what do we have. Can we extend something like Cognitive Apprenticeship to coaching on the job, and link to community to continue and ultimately own the final development? I welcome feedback!

 

Is assessment of capability enough?

23 September 2025 by Clark Leave a Comment

In a conversation with a colleague (a few weeks ago as I write this), I had a thought. She’s contemplating an evaluation book, and I was talking about evaluating competencies. It occurred to me that there may be more than just the ability needed. Which leads me to ask, is assessment of capability enough?

So, we should be looking at competencies. Ideally, we’re stepping away from norm-referenced assessment, that is comparing to others. We should have an absolute criteria which says that they now can do this. For instance, Mager-style objectives: what they need to be able to do, in what context, and to what level of capability. This is part of the shift away from roles, since orgs break up tasks differently. That is, some orgs have folks who do analysis separate from those who do design, and those who develop. Others have people do the whole thing go to whoa.

However, is competency enough? That was the question that occurred to me. I was thinking that maybe the only thing that really mattered was that they felt confident enough to give it a go after the learning experience. That is, folks have to feel like they are ready to give it a go.

I realized, thinking more about it, that it’s not just confident. Taking Dunning-Kruger into account, we don’t want folks who are confident but aren’t really ready. That’s not a recipe for success!  So…I am thinking that it’s willing and able! So, you probably need to indicate readiness to give it a go as well as the competence. So how do we assess that? We can ask, but folks might say they’re ready, but they’re not. I’m wondering if them actually having a plan for how and when they’ll apply makes sense. As a complement to a skill demonstration as well.

I’m not fully convinced, but I do believe that just competence isn’t enough. Folks may know how to do something, but they may not intend to do it. There are lots of reasons why folks don’t actually do what they’ve learned! Of course, the best test is if they are doing it sometime later. E.g. they’ve learned, did, and persisted. But we may want a gateway test first, and I think it’s more than just competence. At any rate, that’s my answer to the question of whether assessment of capability is enough. What’s yours?

After writing this, and before it’s published, I came across IBSTPI’s Competency-Based Education webinar slides, and realized that they’re talking about dispositions in this role. Interesting…though really the proof is what happens when they can apply it, not what they say beforehand. However, if we track that, we might start getting criteria about what other clues we need.

Transforming from knowledge to performance

16 September 2025 by Clark Leave a Comment

As I’ve mentioned, I’m working with a startup looking at extending training through small LIFTs. The problem is that most training is ‘event’ based, where learning is in a concentrated time. Which is fine for performing right after. However, much of what we train for are things that may or may not happen soon. What we want is to go from the knowledge after the event to actually performing in new ways after the event, possibly a long time. We need retention from the learning to the situation, and transfer to all appropriate (and no inappropriate) situations. Thus, we need to think differently. And, as I suggested, we’re looking at supporting people not just with formal learning, but beyond, to developing their ability over time. We really want to be transforming from knowledge to performance. So, what’s that look like?

As usual, when I’m supposed to be sleeping is one of the times I end up noodling things over. And, so it was some nights ago. I was thinking about (as I’m wont to do) the cognitive roles that we need. I talk about practice, and models, and examples, and more recently, generative activities. But that’s formal learning, and we have a good evidence base for that. But what about going forward? What sorts of activities make sense?

Here I’m going out of my comfort zone. Yes, I’ve been doing some reading about coaching, particularly domain-independent vs domain-specific coaching. Now, here I don’t necessarily know what the research says specifically, but I do see the convergence of a variety of different models. So, I can make inferences. And post them here to get corrected!

Stages of early, middle, and late, with reflection (personal, conceptual) and reactivation (reconceptualization, recontextualization, reapplication) in early . Planning (initial is at the intersection of early mid, revision is in mid) and barriers (internal, external) are in mid. Impact (internal at boundary of mid and late, external) and survey are in late. As you might expect, I made a diagram to help me understand. So, I reckon there’s an early, mid, and late stage of development of capability. Formal learning should really be about getting you ready to apply.

That is the early phase which includes reflection (really, a generative activity), which can be personal (ala scripts) or conceptual (schemas). Also, reactivation. That is, seeing different ways of looking at it (new models), more examples in context, and of course more practice. (Retrieval practice, of course, where you’re applying the knowledge.)

Then, in mid-phase, your learners are applying, but to real situations, not simulations. Their initial plan on how to apply the knowledge might be part of the end of the early stage, but then it’s time to apply. Which could (should?) lead to revisions of the plan, and on reflecting on any barriers. Those barriers could be internal (their own understanding or hangups), or external (lack of resources, situations, tools, etc). The former are grounds for discussion, the latter for action on the part of the org!

Then, at the late stage, learners should be looking at the impact. They can reflect on the impact on them, which could also be a mid-phase action, but ultimately you want to see if they’re having an impact overall. Then, of course, you could want to survey about the learning experience itself. While it’s all data, the org impact is useful data to evaluate what’s going on and how it’s going, and the survey can help you continue to improve either this or your next initiative.

Those’re my initial thoughts on transforming from knowledge to performance. There’s some overlap, no doubt, e.g. you could continue sending reapplications if there aren’t frequent opportunities in the real world. Likewise, your learners should be assessing impact in the need to revise a plan. Still, this seems to make sense in the first instance, at least to me. (Addressing the ‘when’, how much and what spacing, is what I’ll be talking about at DevLearn. ;) Now, it’s over to you. What have I got wrong, am missing, …?

Knowledge or ability?

9 September 2025 by Clark Leave a Comment

As in the last post, I’ve been judging the iSpring Course Contest (over, of course). And, having finished, one other thing I’ve noticed is a clear distinction between ‘knowing’ and ‘doing’. We’re seeing lots of interest in skills, yet the courses are, with one exception, really assuming that if you know about it, you’ll do it right. Which isn’t a safe assumption! Are you trying to develop knowledge or ability? I’ll suggest you want the latter. And, can do it!

So, in 9 of the 10 cases, the questions are essentially about knowing. Some of them better than others, e.g. some seem to follow Patti Shank’s advice about how to write better multiple choice questions. That is, for instance, reasonably balanced prose describing the alternatives, and only 3 options. Not all follow it, of course.

The problem is that knowing about something isn’t the same as knowing how to do it. So, for instance, knowing that you should calibrate after changing the reagent isn’t the same as remembering to do it. We’ve all probably experienced this ourselves. They pretty much all had quizzes, as required, but most were just testing if you recalled the elements of the course. Not good enough!

What the one course did that I laud was that the final quiz was basically you applying the knowledge in a situation. You weren’t asked what this situation was, but instead chose how to respond. They were linked, each continuing the story, so it was really a linear scenario. Which I realize can be just a series of mini-scenarios! Still, you dragged your response from a list of responses. They weren’t all that challenging to choose between, as the alternatives were pretty clearly wrong, but for good reasons, reflecting the common mistakes. This is the way!

I think some designers were aspiring to this, as they did put the learner into a situation. However, they then asked learners to classify the answer, rather than actually make a decision about action to take, e.g. a mini-scenario. There is an art to doing this well (hence my workshop in two days)! Putting people into a context to choose their actions like they’ll have to do in the real world is the important practice. Of course, mentored live performance is better. Or simulations (tuned to games, of course ;). Even branching scenarios. But mini-scenarios are easily doable within your existing practice.

The question of knowledge or ability is easily answered. In how many cases will the ability to recite knowledge versus make decisions be the defining success factor for your organization? I’ll suggest that making better decisions will be the differentiator your organization needs. The ability to write better mini-scenarios seems to me to be the best investment you can make to have your interventions actually achieve an impact. And if you’re not doing that, why bother?

What’s In It For Them?

2 September 2025 by Clark Leave a Comment

I’m judging some submissions from the iSpring conference, and noticing a trend. And, of course, it’s not in the requirements (which focus on using all the capabilities of their tool, not surprisingly). It’s also not in the evaluation criteria. Yet, it’s something I obviously care about. (I mean, I basically wrote a book that was about it as half of the whole picture!) I’m talking about addressing the ‘what’s in it for them’ for the learners.

So, two things to start with. For one, the evaluation does ask “Does the course maintain interest throughout?”  So that’s the other half of the book, but…it doesn’t address the first half. Ok, many times you see the designers deal with it implicitly in the objectives, saying what you’ll be able to do. (Even, some times, in terms you will care about!) But that’s not enough.

What these courses seem to assume (and this is prevalent in much that I see) is that you’ve come to the course because you’ve interest in the topic. Which may be the case, if they’re already practitioners. Where it’s not appropriate is when it’s been assigned by someone else. And, overall, you probably shouldn’t assume the former. Unless you’re just hanging it out there for anyone who’s interested (and who can afford that?).

So, you should be addressing, up front, why the learner should care. What’s the context that makes this course of value and of interest? If you (as the learner) are a likely victim, er, audience for this course, what lets you know? Again, it’s not in the requirements, but I certainly wish it was pretty much habitual. There’s one case where it’s partly done, in that they start with the scenario and a question, but it takes some time to get there. This should be the very first thing learners see. Before objectives, before you say what the course will entail. Why should they pay attention to any of that? You haven’t made it visceral. And, motivation helps you learn better

So, please, make it a habit to hook your learners from the get-go. Show them the ‘what’s in it for them” up front. They’ll pay more attention to everything else you do, and that leads to better outcomes. Which is what we all want.

Top 10 Learning Tools 2025

14 August 2025 by Clark 1 Comment

Every year, the inimitable Jane Hart collects what people say are their top 10 tools for learning. The results are always intriguing, for instance, last year AI really jumped up the list. You can vote using this form, or email your list to her via the address on that page. I’ve participated every year I’ve known about it, and do so again. Here’s my list. Realize this is for ‘learning’, not formal education per se. It’s whatever makes sense for you.

Writing

I write, a lot. It’s one way of my making sense of things. So…Microsoft Word remains my goto tool. Less and less so, of course. I’ve been using Google Docs to collaborate with others quite a bit, and am currently using Apple’s Pages for that purpose. Still, I think of Word as my ‘goto’ tool, at least for now. I don’t like Microsoft, and am trying to wean myself away, but I really really need industrial strength outlining, and no one else has measured up.

Apple’s Notes needs a mention. I use it, a lot. Several things are pinned to the top (including my SoMe canned responses, and shopping lists). I also share recipes with family members (on Apple devices), take notes on books and the like, keep a list of ‘to consume’ (books, movies). I also use Notability for biz notes, but it’s not as ubiquitous, and I may just shift everything to notes as there’ve been an increasing number of ‘offers’ to upgrade. Yuck.

And, of course, WordPress for this blog. Here’s where I share preliminary thoughts that end up appearing in articles, presentations, or books. It’s a way to share thinking and get feedback.

Diagramming

I’m still using OmniGraffle. I tried using Google’s Draw, and Apple’s Freeform, but… OmniGraffle’s positives are its user interface. It works the way I want to think about it. Sure, it’s probably changed my thinking to adapt to it too, but from the get go I found using it to be sweet. In fact, as I’ve recounted, I immediately redid some diagrams in it that I’d created in other ways previously just because it was so elegant. The downsides are not only that it’s Mac-only (I work with many other folks), but that it’s not collaborative. Diagramming is one of the ways I make sense of things.

Presentation

Apple’s Keynote remains my preferred presentation tool. I continue to use it to draft presentations. It defaults to my ‘Quinnovation’ theme, tho’ for reasons (working with others, handouts w/o color, builds, etc) I will use a plain white theme. I even have built a deck of diagram builds, so I can paste them into presos but have them to hand rather than having to remake them each time. It’s another way to share.

Connection

Apple Mail, for email, is an absolute necessity. I have to stay in touch with folks, and mail’s critical to coordinate and share.

I use Safari all the time as my browser, tho’ occasionally I have to have Chrome-compatibility, at which time I use Brave; Chrome-compatible but without Google’s intrusiveness. Takes me to Wikipedia, a regular trusted source for looking things up.

Zoom remains my ‘goto’ virtual meeting tool (all my meetings are virtual these days!). I of course use Microsoft’s Teams (but only through the browser now, was able to turf the app), and Google Meet, but only as others request. Of course, connecting with others is critical to learning.

Wow, I’m running out of time and space. Let’s see: Slack is a coordination tool I use a lot with the LDA, and Elevator 9. It’s also a way to share thinking, so it’s a learning tool too.

There’s more, so I guess I’ll use my last slot and aggregate my Social Media tools. That includes LInkedIn, Bluesky, and Mastodon. All three get notification of blog posts, but other than that each has its separate uses. LinkedIn is for biz connections, and reading what others are posting. Bluesky is mostly what Twitter used to be (before it became Xitter), fun, quantity. Mastodon’s more restrained in growth, but the underlying platform is really resistant to political/business corruption.

That’s all I can think of. I welcome hearing your thoughts and seeing the results.

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