design Archives - Learnlets

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!

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, …?

Learning science on tap

11 September 2025 by Clark Leave a Comment

In the interest of the continuation of Quinnovation, Learnlets, and me, this is a solicitation post. If it’s not for you, kindly ignore. However, it may be for your boss; if so, please pass it on!

Do you run an L&D department, or make L&D decisions, and don’t have sufficient learning science background? You know, you get asked to make decisions that involve learning – responding to vendors, stakeholders asking “why”, etc – and you’re not sure how to respond. That’s not uncommon! While you know how to select technologies, design solutions, create strategies, etc in other areas, you don’t necessarily know how to do that with an enlightened view of how we think, work, and learn. L&D is unique because it deals with learning – skills, social, informal, and more. And your school experience is not a good guide. How do you cope? Learning science on tap!

Let me offer this solution, specifically Clark Quinn, Ph.D., on tap. There are reasons why: I’ve been recognized for my depth of knowledge and breadth of experience in translating learning science into practical terms. That includes writing books, keynoting, awards, and, of course, consulting. I’ve applied that background for literally decades in the design of solutions: games, mobile, strategy, processes, policies, and more. So, that’s available. For instance, you could send me something that needs a learning science perspective – an RFP, a memo, an organizational initiative, and I’ll break it down from a learning science perspective, and provide you with same. Or we can talk on a call. What’s more, as I’m wont to do, I’ll provide the underlying thinking. That is, you learn as you go, too! (Just how I roll.)

Of course, you don’t have to take my advice. You’ll have it, and can factor it into your thinking. And, I can adapt my thinking to specific constraints. I am known to come up with better ideas than had been proposed initially. But it’s up to you. I’ll give you my feedback, and you can do with it as you will. This service is for those that can’t come up with that advice on their own, and it’s an important perspective. What I’ll suggest as recommendations will be grounded in evidence-based approaches. I’ll research anything I need to know and don’t (no extra charge), so I learn too. But I have been involved in thinking at most levels and areas of an organization, in a multitude of roles.

I won’t be an employee (nor want to become one). And, I’m not generating new things (that’s a different engagement, we can talk about it), but I’ll review and opine, to your needs. So, I won’t write an RFP or a whitepaper for you; I won’t design a learning experience; nor will I read an article and summarize it for you. Those’d be different engagements. But I’ll review an RFP or whitepaper (incoming or outgoing) for the necessary learning science. I will review the rules and practices around such a design. If someone sends you an article and asks your opinion, I’ll give you the perspective on that. In particular, I’ll help evaluate any claims that you’re faced with, again either coming from inside or outside.

In short, I’m your learning science advisor. Anything you need. Of course you’ll also get any other thoughts my experience provides: how to deal with issues or people, possible solutions, and more. Comes with the territory.

I also know to respect confidentiality. Heck, my IP has been used to train LLMs, and that doesn’t sit well with me. I will also likely want to write up any learning I attain. I can anonymize it or profile you, your choice. Obviously, I won’t share anything proprietary. And my advice is yours, and you can choose to acknowledge me or keep my participation out of it; I really don’t care.

I’ve, over time, learned to be efficient. One of the benefits of knowing how our minds work is that I know what we’re not good at, and have developed practices to ensure that I don’t fall down on commitments. I have my own project management approach, which, coupled with my natural “just do it” inclination, means that you won’t be waiting weeks for a response. I’ll commit to 48 hours max on anything less than ebook length, and as folks who are using me in other ways (*cough* LDA and Elevator 9 *cough*) will tell you, I tend to do things in a matter of hours if it’s not too long.

So, what would such an engagement entail? I’d like to keep it simple and fair. I reckon there’s anywhere from 3 to 10 such things a month. Some will be short, some will be longer. Some months more, some less. My initial ask is $1K per month, and an initial $500 retainer (just to make sure payment systems work, and that’ll cover a call to set the context). If you want to sign up for a year, it’s $10K (9999.99 if necessary to stay under a cutoff ;). Either of us can terminate at any time; in the case of a year purchase, I’ll prorate. What I do for you is yours, what I know and learn is mine. I’ll prod you weekly to remind you to take advantage, and you don’t have to. (Heck, you can always think of it as supporting your friendly neighborhood research translator!)

This may not be you, but if it is, think through the tradeoffs. No overhead – taxes, benefits, etc – the cost is the cost. What you get is yours and your department’s. It’s an investment in learning, for that matter, because you will have the opportunity to improve your understanding as we go. My goal in this (and every) engagement is to remove the need for me in the loop, and learning about learning isn’t just for those developing learning, it’s a good practice for everyone. It’s even a competitive advantage.

Oh, one other thing. I reckon, what with my other commitments, I can only take on 10 such relationships. So, first come, first served. Learning science on tap. Your move! You can reach out here.

We now return you to your regularly scheduled day, already in progress.

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.

Announcing my mini-scenario workshop

28 August 2025 by Clark Leave a Comment

I try not to commercialize this blog. It doesn’t cost, you can get ad free updates in your email, and of course it’s really for me ;). Still, once in a while there’s something I do want to draw your attention to. And, of course, you can stop here. However, I’ll suggest you at least give this a look. What I’m talking about are the whys and whats of an upcoming mini-scenario workshop I’ll be running on 9/11 from 11-3:30 ET. (Yes, I know, that date, but really, we don’t want to let them win, right?) So, I’m announcing my mini-scenario workshop.

First, why? Well, I argue that there are strong reasons to lift our practice game. Retrieval practice is, I believe, the most important thing we can do help our learning actually develop skills. Such practice is really integral to, for instance, the Serious eLearning Manifesto. And it’s more than just better-written multiple choice questions (MCQs). Patti Shank has told us how to do that, and what I am talking about is a bit of that, but more focused. And we can go beyond, to branching scenarios. For that, you should pay attention to Christy Tucker. Instead, I’m talking the sweet spot in between. The one that’s well within our reach, but not our grasp.

Short of branching scenarios, but beyond good MCQs, are what I call mini-scenarios. They’re MCQs, but specifically written to be retrieval practice. What we’re doing is using the base capability of our authoring tools, but taking them to the best place they can be. And, previous experience tells me that you can get the idea, but you really need feedback to fine-tune your understanding. Not a surprise, really, it’s learning after all! Still, a strong argument.

And, being immodest, I have really sweated the details about how to make this workshop, well, work. First, a quick refresh on ‘why’. Then, we take apart the idea into the constituent parts, and talk about the essential criteria for each. We reinforce this by identifying bad examples. Then, we work through two different ways of doing these. In groups, you’ll work with the ideal: given good objectives. But we’ll also work through the likely real: working from knowledge questions. In addition, I’ve created a job aid: a checklist that uses the structure to help make sure you’re developing a useful mini-scenario. We’ll use it in the exercises.

While this is the first live run, I’ve iterated on it numerous times. I’ve even developed a follow-on just to refine the design (tho’ we may have it as an extra-value no-extra-cost option)! So, if you want to get serious about writing questions that will scaffold your learners to developing real new abilities, not just knowledge, this is the place to come. So that’s why I’m announcing my mini-scenario workshop. I hope to see you there!

Training Organization Fails

19 August 2025 by Clark Leave a Comment

I’ve worked with a lot of organizations that train others. I’ve consulted to them, spoken to them, and of course written and spoken for them. (And, of course, others!) And, I’ve seen that they have a reliable problem. Over the years, it occurs to me that these failures stem from a pattern that’s understandable, and also avoidable. So I want to talk about how a training organization fails. (And, realize, that most organizations should be learning organizations, so this is a bigger plea.)

The problem stems from the orgs’ offering. They offer training. Often, certification is linked. And folks need this, for continuing education needs. What folks are increasingly realizing is that much of the learning they’re offering is now findable on the web. For free. Which means that the companies not seeing the repeat business. Even if required, they’re not seeing loyalty. And I think there’s a simple reason why.

My explanation for this is that the orgs are focusing on training, not on performance solutions. People don’t want training for training’s sake, by and large. Sure, they need continuing education in some instances, so they’ll continue (until those requirements change, at least). Folks’ll take courses in the latest bizbuzz, in lieu of any other source, of course. (That’s currently Generative Artificial Intelligence, generically called AI; before that as an article aptly pointed out it was the metaverse, or crypto, or Web 3.0, …)

What would get people to do more than attend the necessary or trendy courses? The evidence is that folks persist when they find value. If you’re providing real value, they will come. So what does that take? I posit that a full solution would be comprised of three things: skill development, performance support, and community.

Part 1: Actual learning

The first problem, of course, could be their learning design. Too often, organizations are falling prey to the same problems that belabor other organizational learning; bad design. They offer information instead of practice. Sure, they get good reviews, but folks aren’t leaving capable of doing something new. That’s not true of all, of course (recently engaged with an organization with really good learning design), but event-based learning doesn’t work.

What should happen is that the orgs target specific competencies, have mental models, examples, and meaningful practice. I’ve talked a lot about good learning design, and have worked with others on the same (c.f. Serious eLearning Manifesto). Still, it seems to remain a surprise to many organizations.

Further, learning has to extend beyond the ‘event’ model. That is, we need to space out practice with feedback. That’s neglected, though there are solutions now, and soon to be available. (Elevator 9, cough cough. ;) Thus, what we’re talking about is real skill development. That’s something people would care about. While it’s nice to have folks say they like it, it’s better if you actually demonstrate impact.

Part 2: Performance support

Of course, equipping learners with skills isn’t a total solution to need. If you really want to support people succeeding, you need more than just the skills. Folks need tools, too. In fact, your skill development should be built to include the tools. Yet, too often when I ask, such orgs admit that this is an area they don’t address.

There are times when courses don’t make sense. There are cognitive limits to what we can do, and we’ve reliably built ways to support our flaws. This can range from things performed rarely (so courses can’t help), through information that’s too volatile or arbitrary, to things done so frequently that we may forget whether we’ve taken a step. There are many situations in pretty much any endeavor where tools make sense. And providing good ones to complement the training, and in fact using those tools as part of the training, is a great way to provide additional value.

You can even make these tools an additional revenue stream, separate from the courses, or of course as part of them. Still, folks want solutions, not just skill development. It’s not about what you do for them, but about who they become through you (see Kathy Sierra’s Badass!).

Part 3: Community

The final piece of the picture is connecting people with others. There are several reasons to do this. For one, folks can get answers that courses and tools are too coarse to address. For another, they can help one another. There’s a whole literature on communities of practice. Sure, there are societies in most areas of practice, but they’re frequently not fulfilling all these needs (and they’re targets of this strategic analysis too). These orgs can offer courses, conferences, and readings, but do they have tools for people? And are they finding ways for people to connect? It’s about learning together.

I’ve learned the hard way that it takes a certain set of skills to develop and maintain a community. Which doesn’t mean you shouldn’t do it. When it reaches critical mass (that is, becomes self-correcting), the benefits to the members are great. Moreover, the dialog can point to the next offerings; your market’s right there!

There’s more, of course. Each of these areas drills down into considerable depth. Still, it’s worth addressing systematically. If you’re an org offering learning as a business, you need to consider this. Similarly, if you’re an L&D unit in an org, this is a roadmap for you as well. If you’re a startup and want to become a learning organization, this is the core of your strategy, too. It’s the revolution L&D needs ;). Not doing this is a suite of training organization fails.

My claim, and I’m willing to be wrong, is that you have to get all of this right. In this era of self-help available online, what matters is creating a full solution. Anything else and you’ll be a commodity. And that, I suggest, is not where you want to be. Look, this is true for L&D as a whole, but it’s particularly important, I suggest, for training companies that want to not just survive, but thrive in this era of internet capabilities.

Beyond Design

12 August 2025 by Clark Leave a Comment

When you look at the full design process, I admit to a bias. Using Analysis-Design-Development-Implementation-Evaluation, ADDIE, (though I prefer more iterative models: SAM, LLAMA, …), I focus early. There are two reasons why, but I really should address them. So let’s talk beyond ‘design’ and why my bias might exist. (It pays to be a bit reflective, or defensive?, from time to time.)

I do believe that it’s important to get the first parts right. I’ve quipped before that if you get the design right, there are lots of ways to implement it. To do that, you need to get the analysis and design right. So I focus there. And, to be sure, there’s enough detail there to suit (or befuddle) most. Also, lots of ways we go wrong, so there’s suitable room for improvement. It’s easy, and useful, to focus there.

Another reason is that implementation, as implied in the quip, can vary. If you have the resources, need, and motivation, you can build simulation-driven experiences, maybe even VR. There are different ways to do this, depending. And those ways change over time. For instance, a reliable tool was Authorware, and then Flash, and now we can build pretty fancy experiences in most authoring tools. It’s a craft thing, not a design thing.

Implementation does matter. How you roll things out is an issue. As Jay Cross & Lance Dublin made clear in Implementing eLearning, you need to treat interventions as organizational change. That includes vision, and incentives, and communication, and support, and… And there’s a lot to be learned there. Julie Dirksen addresses much in her new book Talk to the Elephant about how things might go awry, and how you can avoid the perils.

Finally, there’s evaluation. Here, our colleague Will Thalheimer leads the way, with his Learning Transfer Evaluation Model (LTEM). His book, Performance Focused Learner Surveys comes closest to presenting the whole model. Too often, we basically do what’s been asked, and don’t ask more than smile sheets at best. When, to be professional, we should have metrics that we’re shooting to achieve, and then test and tune until we achieve them.

Of course, there’re also my predilections. I find analysis and design, particularly the latter, to be most intellectually interesting. Perhaps it’s my fascination with cognition, which looks at both the product and process of design. My particular interest is in doing two things: elegantly integrating cognitive and ‘emotional‘ elements, and doing so in the best ways possible that push the boundaries but not the constraints under which we endeavor. I want to change the system in the long term, but I recognize that’s not likely to happen without small changes first.

So, while I do look beyond design, that’s my more common focus. I think it’s the area where we’re liable to get the best traction. Ok, so I do say that measurement is probably our biggest lever for change, but we’ll achieve the biggest impact by making the smallest changes that improve our outcomes the most. Of course, we have to be measuring so that we know the impact!

Overall, we do need the whole picture. I do address it all, but with a bias. There are others who look at the whole process. The aforementioned Julie, for one. Her former boss and one of our great role-models, Michael Allen, for another. Jane Bozarth channels research that goes up and down the chain. And, of course, folks who look at parts. Mirjam Neelen & Paul Kirschner, Connie Malamed, Patti Shank, they all consider the whole, but tend to have areas of focus, with considerable overlap. Then we go beyond, to performance support and social, and look to people like Mark Britz, Marc Rosenberg, Jay Cross, Guy Wallace, Nigel Paine, Harold Jarche, Charles Jennings, and more.

All to the good, we benefit from different perspectives. It’s hard to get your mind around it all, but if you start small, with your area, it’s easy to begin to see connections, and work out a path. Get your design right, but go beyond design as well to get that right (or make sure it’s being done right to not undermine the design ;). So say I, what say you?

The ‘right’ level

5 August 2025 by Clark 1 Comment

So, I know I’ve talked about this before (not least, here), but it seems to continue to persist. What I’m talking about is the continuing interest in neuroscience for L&D. And, as has been said by others, it’s the wrong level of analysis. What, then, is the ‘right’ level? Here’re my thoughts, and I welcome yours.

This is not to say neuroscience isn’t valuable. It objectively is. We gain insights that bolster some views, and nuance others. That’s important, for sure. We find out about mirror neurons, important for social learning. And, for instance, we can find that dopamine ramps up more for preferred motivators, and orients us in those directions. That’s interesting. It also suggests that we should make sure we’re involving people’s motivation for learning.

However, my point is that we know this already. Cognitive science tells us this. So, for instance, at the neural level, learning is about reinforcing patterns, strengthening connections between neurons at an aggregate level. That’s great. However, how we do that is by triggering patterns in conjunction, to strengthen them. How do we trigger patterns? With words, images, etc. Things that mean something. That’s cognitive!

There’s a level above, too, the social level. Here, we are presented with what others think. Which is useful to understand. But, for learning, we have to translate back to the cognitive level. That is, we need to think about how seeing how others interpreted the same signs, and what that means for ours. Social learning is valuable, but…while we enact it publicly, our understanding of why and how will depend on what we know.

For instance, brainstorming. Without a cognitive understanding, we won’t know how to do it right. We can learn, empirically, that we get better results when we think alone first before converging (and other aspects, like avoiding premature evaluation). Why? When we get to the cognitive analysis, we recognize that if we haven’t generated our own ideas first, others’ ideas can constrain our thinking.

Sure, I’m biased. I was steeped in the cognitive perspective. Yet, when I look at what works and why, I see the meaningful analysis coming from the cognitive level. Likewise, when I see people tout ‘neuro’ and ‘brain-based’, etc, all the results I hear are really cognitive ones. Certainly, ones that cognitive science has already shown benediction for.

So, I keep learning (another recommendation from cognitive science ;). And I have no doubt that we’ll learn things from neuroscience as that field matures. Still, for good prescriptions for learning design, cognitive is the ‘right’ level for analysis. Which means it’s the right level to study and understand. Please, ensure you do understand learning science before you design for others. That’s so you’ll create experiences that honor our learners by providing learning that works: is meaningful and effective. Which is really what we should be about. Those are my thoughts, what are yours?

Auto-marked generative?

29 July 2025 by Clark Leave a Comment

As I continue to explore learning science, and get ever-deeper, one idea came to me that I had to check out. So, we’re recognizing the difference between elaboration (getting material into long-term memory), and retrieval (getting it out). They’re different, and yet both valuable. However, generative (not Generative AI, btw) activities typically have learners create their own understandings as a goal of having them reprocess the information. Which makes them labor-intensive to evaluate. Sure, you could have GenAI evaluate and respond, but that’s problematic for several reasons. Is there another way? Can you have auto-marked generative activities?

Increasingly, from educators I’m hearing more about generative activities. These are elaboration processing, where learners express the material in their own way. I argue that this can be either connecting it to personal experiences, or connecting it to prior knowledge (playing some semantics here ;). The goal, however, is to deepen and extend the patterns across neural activity, increasing the likelihood of their activation.

Whether prose, diagram, or mindmap (yes, a form of diagram, but…), these are free-form, and thus need review. Someone needs to look at them, to ascertain whether they’re right or whether they represent a significant misunderstanding. I remember when Kathy Fisher (of semantic networking fame and software SemNet) talked about how she asked students about how water got from the digestive to the excretory system, and they (many?) ended up positing in their mind-maps an extra tube connecting the two. (Fun fact: no such tube exists, water is absorbed into the blood, and then filtered out via kidneys.) Of course, with this evidence, it’s easy to diagnose misconceptions, at the expense of sufficient human interaction.

I was thinking about writing retrieval practice mini-scenarios, and was led to wonder whether you could do the same for generative activities. That is, present alternatives, perhaps of the most common misconceptions, and have learners choose between different representations. One advantage, then, would be the ability to auto-mark understanding. It seems to me that they’ll still need to process each representation, to be able to choose one, so they’re doing processing. It could be a mindmap, diagram, or prose restatement. You’d also be able to diagnose, and remediate, misunderstandings.

For example, you could ask:

How does water get from the digestive to the excretory system:

- There’s a direct connection between the two, known as the aqueduct.
- Water is absorbed into the blood and then filtered out via the kidneys.
- There’s an organ that processes water from the former to the latter.

(A rough conceptualization; I’m sure a physiologist, could do better!)

I thought that perhaps I could ask someone who both talks about cognitive processing, researches instructional strategies, and in particular talks about generative activity. Professor Rich Mayer, who Ruth Clark introduced to us at the Learning Development Accelerator, was kind enough to respond, and we had a Zoom Chat. Not putting words in his mouth, it was my understanding that he agreed that this was a plausible model. I freely offer anyone to research this (including you, Rich!). Unless such are extant, in which case please point me to existing journal articles or the like.

There’s no telling whether this is useful, of course. Are auto-marked generative activities possible and plausible? Still, better to get the idea out there than not, it may end up being useful! Which, of course, is the ultimate goal. Thoughts?

Context and models

22 July 2025 by Clark Leave a Comment

One of the things I’ve recognized is that we don’t pay enough attention to context. It turns out to be a really important factor in cognition, as our long-term memory interacts with the current context to determine our interpretation. And, as such, makes our interpretations very ’emergent’. Thus, our training needs to ensure that we’re liable to make the right interpretation and so choose the right action. Do we do this well? And can artificial intelligence (AI), specifically generative AI (GenAI), help? Here’re some thoughts on context and models.

So, we’ve gone from symbolic models to sub-symbolic ones as we’ve moved to a ‘post-cognitive’ interpretation of our thinking. What’s been realized is that we’re not the formal logical reasoning beings that we’d like to think. Instead, we’re very much assembling our understanding on the fly as an interaction between context and memory. In fact, our emergent memory can be altered by the context, as Beth Loftus’ research demonstrated. Which means that, if we want specific interpretations and reactions (e.g. making decisions under uncertainty), we should be careful to ensure that we provide training across a suitable suite of contexts.

Now, active inference models of cognition suggest that we’re actively building models of how the world works. Thus, we’re abstracting across experiences to generate ever-more accurate explanations. Research on mental models suggests that they’re incomplete, not completely accurate, and, arguably most importantly, hard to get rid of if they’re wrong. Thus, providing good models beforehand is important, and work by John Sweller further suggests that examples showing models in context benefit learning. You can present the model, but ultimately the learner must ‘own’ it. So, it’s important to know the models and their range of applicability to facilitate that abstraction.

What is important to know, however, is that GenAI doesn’t build models of the world. This was an important (and, sadly, not self-generated) realization for me. The implication, however, is clear. I have maintained that GenAI can’t understand context, and thus can’t generate suitable practice environments. Which, of course, is to the good for designers, since it leaves them a role ;). Importantly, however, this framing also suggests that GenAI also can’t choose an appropriate suite of contexts for practice, since it doesn’t understand models and how they’re applicable (and when not). (Another designer role!)

I am all for using technology to complement our own cognition. However, that entails knowing what the true affordances of the technology are, and also what it can’t do. So, GenAI can help think of great settings for practice. Along with a person (an expert actually) to vet the suggestions, of course. It can think of things we might forget, or ones we haven’t thought of yet. It can, of course, also create ones that aren’t realistic. There’re potentially great opportunities, but we have to know what matters, and what doesn’t. Context and models matter. GenAI can’t understand them. You can take it from there.